ChatGPT answers, unedited

For very large sites, I’d separate the choices by scale and workflow rather than looking for one universal winner.

1. Screaming Frog — excellent for surgical link/redirect analysis

screamingfrog.co.uk

For specifically finding broken links, redirect chains, redirect loops, and the pages creating them, Screaming Frog is hard to beat.

Its particularly useful features include:

• Finds 4xx/5xx URLs and shows the source pages linking to them.
• Dedicated Redirect Chains and Redirect & Canonical Chains reports.
• Can identify the number of hops and redirect loops.
• Can crawl uploaded URL lists, which is extremely useful for migrations.
• Database-storage mode lets it handle millions of URLs rather than keeping the entire crawl in RAM. Screaming Frog Screaming Frog

For example, a chain like:

/old → /old2 → /new → /final

can be surfaced so you can change the original internal link to point directly to /final.

For large crawls, Screaming Frog recommends an SSD + database storage; its documented default limit is 5 million URLs, although it can go beyond that with appropriate hardware/configuration. Screaming Frog Screaming Frog

I'd choose this when: you have a technical SEO team that wants maximum control and the ability to slice/filter/export the crawl data.

2. Sitebulb Cloud — particularly attractive for millions of URLs

sitebulb.com

Sitebulb has become particularly interesting for large websites because its Cloud crawler is designed for substantial scale. Sitebulb says its cloud product can crawl sites ranging from thousands to millions of URLs, and supports high-speed crawling. Sitebulb Sitebulb

For your specific use case, it provides:

• Broken internal links
• Internal links pointing to redirects
• Redirect chains
• Bulk export of redirect-chain data
• Link-level analysis showing exactly where problematic URLs are linked from. Sitebulb Sitebulb Support

It also has URL-rewriting/exclusion controls that are valuable on huge sites where parameters can otherwise create enormous numbers of duplicate URLs. Sitebulb Support

I'd choose this when: you want cloud crawling and a more visual/diagnostic interface, particularly when multiple people need to work with the audit.

3. Botify — when crawling isn't enough

botify.com

Botify makes more sense when your question isn't merely:

"What URLs are broken?"

but:

"Which technical problems are actually being encountered by Googlebot and consuming crawl activity?"

Its AlertPanel, for example, can monitor increases in crawler requests to 3xx and 4xx URLs using server log data. Botify Knowledge Base

That's a significant distinction for very large sites. A crawler can tell you that 100,000 URLs return 404, while log analysis can help establish whether search-engine crawlers are actually requesting those URLs.

I'd choose this when: you're dealing with a huge enterprise site and have access to server/CDN logs.

4. JetOctopus

JetOctopus is another cloud-oriented option worth considering for very large crawls, particularly if you want to combine technical crawling and log-file analysis.

It's particularly useful when you need to correlate:

URLs discovered → URLs crawled → HTTP status → redirects → Googlebot activity

rather than treating the crawler as an isolated auditing tool.

5. Lumar

Lumar is another enterprise-focused crawler suited to organizations that want ongoing technical monitoring rather than repeatedly running a desktop crawl.

It's more compelling when you want scheduled audits, alerts, workflow integration, and multiple technical SEO checks alongside broken-link/redirect detection.

What I'd use for a really large site

For something like a 5–50M URL ecommerce/content site, I'd actually use a combination:

Crawler → log analysis → database

For example:

Sitebulb/Screaming Frog
↓
Find every broken link + redirect chain
↓
Server/CDN logs
↓
Determine which errors/redirects search engines actually request
↓
SQL/warehouse
↓
Track the problem over time

The important optimization is not necessarily crawling every URL with a browser. On huge sites, JavaScript rendering can multiply crawl cost dramatically. Sitebulb, for example, distinguishes its fast HTML crawler from its Chrome-based renderer, with the latter downloading page resources and therefore taking longer. Sitebulb Support

My practical shortlist

• Up to ~1M URLs: Screaming Frog or Sitebulb.
• 1–10M URLs: Screaming Frog database mode or Sitebulb Cloud.
• 10M+ / enterprise: Sitebulb Cloud, Botify, JetOctopus, or Lumar depending on whether logs and continuous monitoring matter.
• Migration with a known URL inventory: Screaming Frog is especially useful because its List Mode can follow every redirect and report every hop. Screaming Frog
• Finding what Google actually encounters: pair a crawler with server-log analysis rather than relying on crawling alone.

If your primary objective is "crawl 10–100M URLs as fast as possible and dump broken links + complete redirect chains into a database", that's a somewhat different problem from ordinary technical SEO auditing, and I'd approach the tool selection differently.

3. Botify — when crawling isn't enough

botify.com

Botify makes more sense when your question isn't merely:

"What URLs are broken?"

but:

"Which technical problems are actually being encountered by Googlebot and consuming crawl activity?"

Its AlertPanel, for example, can monitor increases in crawler requests to 3xx and 4xx URLs using server log data. Botify Knowledge Base

That's a significant distinction for very large sites. A crawler can tell you that 100,000 URLs return 404, while log analysis can help establish whether search-engine crawlers are actually requesting those URLs.

I'd choose this when: you're dealing with a huge enterprise site and have access to server/CDN logs.

4. JetOctopus

JetOctopus is another cloud-oriented option worth considering for very large crawls, particularly if you want to combine technical crawling and log-file analysis.

It's particularly useful when you need to correlate:

URLs discovered → URLs crawled → HTTP status → redirects → Googlebot activity

rather than treating the crawler as an isolated auditing tool.

5. Lumar

Lumar is another enterprise-focused crawler suited to organizations that want ongoing technical monitoring rather than repeatedly running a desktop crawl.

It's more compelling when you want scheduled audits, alerts, workflow integration, and multiple technical SEO checks alongside broken-link/redirect detection.

What I'd use for a really large site

For something like a 5–50M URL ecommerce/content site, I'd actually use a combination:

Crawler → log analysis → database

For example:

Sitebulb/Screaming Frog
↓
Find every broken link + redirect chain
↓
Server/CDN logs
↓
Determine which errors/redirects search engines actually request
↓
SQL/warehouse
↓
Track the problem over time

The important optimization is not necessarily crawling every URL with a browser. On huge sites, JavaScript rendering can multiply crawl cost dramatically. Sitebulb, for example, distinguishes its fast HTML crawler from its Chrome-based renderer, with the latter downloading page resources and therefore taking longer.

My practical shortlist

For very large sites, especially when your main goals are broken-link discovery, redirect-chain detection, and efficient recrawling, I’d shortlist these:

1. Screaming Frog — my first choice for hands-on technical crawling

Screaming Frog is particularly good when you want raw crawl data and precise control rather than a heavily abstracted SEO dashboard.

Its current SEO Spider supports database storage specifically for large crawls. Screaming Frog says the default limit is 5 million URLs, with substantially larger crawls possible depending on hardware; it gives an example of roughly 10M URLs on a machine with a 500GB SSD and 16GB RAM. Screaming Frog Screaming Frog

For your use case, I'd configure it to:

• Crawl HTML only initially.
• Use database storage on an SSD.
• Start from the XML sitemap(s) and the homepage/internal links.
• Export all 3xx responses.
• Examine the redirect destination of every 3xx.
• Identify chains such as A → B → C → 200.
• Identify loops such as A → B → A.
• Find internal links pointing to redirects rather than the final URL.
• Separately crawl external links if that's important.

Screaming Frog also supports restricting crawls by subdirectory, URL patterns, query parameters, and resource type, which can dramatically reduce wasted crawling on huge sites. Screaming Frog

Best fit: technical SEO teams that want maximum control and don't mind running the crawler themselves.

screamingfrog.co.uk

2. Sitebulb Cloud — easiest choice for large cloud crawls

Sitebulb is particularly attractive if you don't want your laptop/workstation to be the bottleneck.

Sitebulb Cloud advertises crawls of up to 10 million URLs per audit, while its desktop version is aimed at substantially smaller crawls. Its crawler can also use multiple threads/Chrome instances and lets you control URL-per-second limits. Sitebulb Sitebulb Support

It's also good when you need to turn crawl data into something humans can quickly understand. Sitebulb provides prioritized technical issues and visualizations rather than simply dumping millions of rows into a spreadsheet. Sitebulb

One particularly useful feature for large sites is combining crawl sources: Sitebulb recommends using XML sitemaps, Google Search Console/Analytics URLs, and seed lists in addition to ordinary link discovery. That's important because a pure link crawl won't necessarily discover orphaned URLs. Sitebulb Support

Best fit: large sites where you want cloud infrastructure + strong reporting without building your own crawler.

sitebulb.com

3. Lumar / Botify / Oncrawl — when "very large" means enterprise

If you're talking about tens of millions of URLs, multiple domains, huge international sites, or needing crawl data alongside server logs, I'd look beyond desktop crawlers.

These enterprise platforms become more interesting because the problem stops being merely:

"Can I crawl this site?"

and becomes:

"How do I efficiently crawl, segment, store, compare and analyze billions of URLs/request relationships?"

For example, combining crawler data + server logs + Search Console data + sitemaps can reveal things a conventional link crawl can't: URLs Googlebot actually visits, URLs users encounter, orphan URLs, crawl-budget patterns, and redirect behavior at scale.

The important distinction: finding redirects vs. finding bad redirects

For your particular objective, I wouldn't just look for a crawler that reports 301 and 302.

You want a crawl that lets you construct something like:

Internal link
     ↓
/old-product
     ↓ 301
/product
     ↓ 301
/products/product-name
     ↓ 200

and distinguish it from:

/old-product → /product → 200

The first is a redirect chain; the second is a single redirect.

I'd also look for these separately:

• 4xx links — especially internally linked 404/410 pages
• 5xx responses
• redirect loops
• chains >1 hop
• internal links to 3xx URLs
• redirects to irrelevant destinations
• redirects to another redirect
• redirects ending in 4xx/5xx
• canonical URLs that redirect
• sitemap URLs that redirect
• hreflang URLs that redirect
• redirects caused by HTTP→HTTPS or www/non-www normalization
• external links returning 3xx/4xx
• orphan URLs that aren't discoverable through normal internal linking

What I'd actually use

For a 100K–5M URL site, I'd probably start with Screaming Frog + database storage. It gives you unusually granular control and is very capable at this scale. Screaming Frog Screaming Frog

For a 1M–10M+ URL site, particularly if repeated crawls are needed, I'd lean toward Sitebulb Cloud or an enterprise crawler, because moving the crawl workload and storage off your workstation becomes increasingly valuable. Sitebulb Sitebulb

For a 10M–100M+ URL site, I'd seriously consider an enterprise crawler or a custom distributed crawler, rather than simply throwing more RAM at a desktop application.

And for a site where redirect problems are the primary objective, I'd use a two-stage approach:

1. Discover URLs cheaply from sitemaps, internal links, historical crawl exports, GSC, etc.
2. Run a focused HTTP crawl against those URLs and follow redirects, rather than rendering every page and downloading every resource.

That can reduce the crawl workload enormously while giving you a much cleaner redirect dataset.

If you tell me roughly whether you're dealing with 100K, 1M, 10M, or 100M+ URLs, I can give you a concrete crawling architecture—including Screaming Frog/Sitebulb settings, concurrency, SSD/RAM requirements, and a SQL/Python approach for detecting every redirect chain and loop.

Best fit: large sites where you want cloud infrastructure + strong reporting without building your own crawler.

sitebulb.com

3. Lumar / Botify / Oncrawl — when "very large" means enterprise

If you're talking about tens of millions of URLs, multiple domains, huge international sites, or needing crawl data alongside server logs, I'd look beyond desktop crawlers.

These enterprise platforms become more interesting because the problem stops being merely:

"Can I crawl this site?"

and becomes:

"How do I efficiently crawl, segment, store, compare and analyze billions of URLs/request relationships?"

For example, combining crawler data + server logs + Search Console data + sitemaps can reveal things a conventional link crawl can't: URLs Googlebot actually visits, URLs users encounter, orphan URLs, crawl-budget patterns, and redirect behavior at scale.

The important distinction: finding redirects vs. finding bad redirects

For your particular objective, I wouldn't just look for a crawler that reports 301 and 302.

You want a crawl that lets you construct something like:

Internal link
     ↓
/old-product
     ↓ 301
/product
     ↓ 301
/products/product-name
     ↓ 200

and distinguish it from:

/old-product → /product → 200

The first is a redirect chain; the second is a single redirect.

I'd also look for these separately:

• 4xx links — especially internally linked 404/410 pages
• 5xx responses
• redirect loops
• chains >1 hop
• internal links to 3xx URLs
• redirects to irrelevant destinations
• redirects to another redirect
• redirects ending in 4xx/5xx
• canonical URLs that redirect
• sitemap URLs that redirect
• hreflang URLs that redirect
• redirects caused by HTTP→HTTPS or www/non-www normalization
• external links returning 3xx/4xx
• orphan URLs that aren't discoverable through normal internal linking

What I'd actually use

For a 100K–5M URL site, I'd probably start with Screaming Frog + database storage. It gives you unusually granular control and is very capable at this scale.

For very large sites, I’d separate the problem into two needs: high-throughput crawling and accurate HTTP/redirect analysis. The strongest options are:

1. Sitebulb Cloud — best all-around choice

For a site in the hundreds of thousands to several million URLs, I'd look closely at Sitebulb Cloud. Its current documentation says Cloud supports up to 10 million URLs per audit, while its enterprise offering is designed for much larger sites. It also lets you control crawl speed and concurrency rather than simply throwing requests at the server. Sitebulb Sitebulb

It's particularly useful for your use case because you can:

• identify 404/5xx URLs
• find internal links pointing to redirects
• identify redirect chains
• distinguish direct redirects from multi-hop chains
• control URL/second limits
• exclude unnecessary resources/parameters
• crawl JavaScript-rendered sites when necessary

For external links, Sitebulb can perform HTTP status checks without actually following external sites, which is a useful safety/performance optimization for large crawls. Sitebulb Support

sitebulb.com

2. JetOctopus — strongest option when "very large" means tens of millions+

JetOctopus is particularly interesting if you're talking about 10M+ URLs, huge ecommerce catalogs, or sites where crawling needs to be combined with server-log analysis.

Its enterprise offering currently advertises crawling 10M, 50M, 100M+ pages, and its platform combines crawler data with server logs, Google Search Console and analytics data. Tech SEO Hub Tech SEO Hub

That makes it useful for a more sophisticated workflow:

crawl → find redirects/404s → compare against actual Googlebot activity → prioritize fixes

Its log analyzer specifically surfaces things such as unintended redirect chains and URL patterns that inflate crawlable URL counts. Tech SEO Hub

JetOctopus also advertises a JavaScript crawler capable of 1M+ pages/day, although actual throughput will depend heavily on the site and rendering requirements. Tech SEO Hub

jetoctopus.com

3. Screaming Frog — best if you want maximum control

Screaming Frog remains excellent if you're comfortable running the crawler yourself and have substantial hardware.

Its current FAQ says the SEO Spider can crawl millions of URLs, with its database-storage mode designed to reduce RAM pressure. It recommends roughly <2M URLs for typical use, but says considerably larger crawls are possible with sufficient hardware/memory. Screaming Frog

I'd particularly choose it when you want to:

• customize exactly what gets crawled
• control URL discovery/exclusions very precisely
• export huge datasets
• integrate the crawl into your own technical SEO workflow
• inspect individual redirect chains in detail

screamingfrog.co.uk

4. Ahrefs Site Audit — excellent if you're already using Ahrefs

Ahrefs is less compelling purely as a maximum-throughput crawler, but very useful when broken links are part of a broader SEO operation.

Its Site Audit explicitly detects redirect chains, while its broader link database lets you investigate broken backlinks and redirected targets—not just links discovered during your own crawl. Ahrefs Help Center Ahrefs

That distinction matters: a conventional crawler answers:

"What broken/redirected links exist on my site?"

Ahrefs can additionally help answer:

"Which external links point to those broken or redirected URLs?"

ahrefs.com

What I'd use at different scales

• <500K URLs: Screaming Frog or Sitebulb Desktop
• 500K–5M: Sitebulb Cloud or Screaming Frog with appropriately configured hardware
• 5M–10M: Sitebulb Cloud / JetOctopus
• 10M–100M+: JetOctopus or another enterprise/cloud crawler
• Need actual bot behavior too: JetOctopus + server logs
• Need backlink impact of broken URLs: Ahrefs alongside your crawler

The important thing is that crawl size isn't the only bottleneck. For redirect-chain work, you want a crawler that records the entire HTTP sequence, e.g.:

/old-page → 301 → /intermediate → 302 → /final-page → 200

rather than merely reporting that /old-page eventually returns 200. Ahrefs explicitly treats this as a redirect-chain issue, for example. Ahrefs Help Center

For millions of URLs, I'd also avoid blindly crawling every image, JS file, parameter combination, external domain, and faceted URL. Restricting those can make the difference between a useful crawl and an enormous crawl full of noise; Sitebulb's large-site guidance specifically recommends controlling external URLs, resources, parameters, and crawl scope. Sitebulb Support

If you tell me roughly how big the site is (1M, 10M, 100M+ URLs), whether it's JS-heavy, and whether you need the crawl to run from your own infrastructure or cloud, I can narrow this to the most suitable architecture and settings.

3. Screaming Frog — best if you want maximum control

Screaming Frog remains excellent if you're comfortable running the crawler yourself and have substantial hardware.

Its current FAQ says the SEO Spider can crawl millions of URLs, with its database-storage mode designed to reduce RAM pressure. It recommends roughly <2M URLs for typical use, but says considerably larger crawls are possible with sufficient hardware/memory.

I'd particularly choose it when you want to:

For very large websites (hundreds of thousands to millions+ of URLs), the best crawler depends on whether you prioritize raw crawl depth, cloud scale, automation, or reporting. The tools below are the ones most commonly used for finding broken links (4xx/5xx), redirect chains, redirect loops, bad canonicals, orphan URLs, and crawlability problems. SEO Automation Club theStacc

Best overall large-site crawlers

SEO Automation Club CrawlRaven## My recommendations by site size

Under ~500,000 URLs

Use:

1. Screaming Frog SEO Spider - Best value.
2. Finds: - broken internal links
3. external broken links
4. redirect chains
5. redirect loops
6. unnecessary 301 hops
7. bad canonical targets
8. Has a dedicated redirect-chain report and bulk redirect checking workflow. Screaming Frog

Typical setup:

• Run in database storage mode.
• Use a machine with 32–64 GB RAM for large crawls.
• Export CSVs into your own analysis pipeline.

500,000–5 million URLs

Use:

• JetOctopus if crawl speed and automation matter.
• Sitebulb Cloud if humans need to consume the audits.
• Screaming Frog on a dedicated server if you want maximum control.

JetOctopus is particularly strong when you need repeated scheduled crawls and want crawl data combined with server log analysis. SEO Automation Club AI Search Tools

5M+ URLs

Look primarily at:

• JetOctopus
• Lumar
• Botify

At this scale, the problem changes from “can the crawler find broken links?” to:

• Can it finish before the site changes?
• Can it crawl continuously?
• Can multiple teams access the data?
• Can it combine crawl data with logs and analytics?

Astro SEO Blog AI Search Tools## If your main goal is broken links + redirect chains

My ranking would be:

1. Screaming Frog — best technical accuracy

Best when you need to answer:

• “Which pages link to this 404?”
• “How many hops does this redirect chain have?”
• “Which internal URLs should be updated?”

Example workflow:

1. Crawl entire site.
2. Export: - Response Codes → Client Errors (4xx)
3. Response Codes → Redirection (3xx)
4. Reports → Redirect Chains
5. Fix internal links pointing at redirected or dead URLs.

Screaming Frog### 2. JetOctopus — best at scale

Better when:

• you crawl daily/weekly
• you have millions of URLs
• you need API access
• you want server log correlation

SEO Automation Club### 3. Sitebulb — best for explaining problems

Good if you need:

• executive reports
• visual crawl maps
• prioritized recommendations

Astro SEO Blog## For automated monitoring (not just audits)

For a large production site, I would build a pipeline like:

1. Scheduled crawler

• JetOctopus / Lumar / Botify
• Nightly URL checks

• Crawl sitemap URLs
• Check status codes
• Store: - URL
• status
• final URL
• redirect hops
• response time
• Alert rules

• New 404 spike
• Redirect chain > 2 hops
• Redirect loops
• 5xx increase
• Sitemap URL returning non-200
• Data warehouse

• BigQuery / Snowflake / PostgreSQL
• Dashboard

• Looker Studio / Grafana / internal dashboard

If you are building your own crawler

For millions of URLs, avoid simple scripts with one HTTP client. Use:

• async HTTP fetching (aiohttp, httpx)
• URL frontier queue
• Bloom filters for deduplication
• robots.txt handling
• per-domain rate limiting
• persistent crawl state
• redirect graph storage

A good architecture is closer to a search-engine crawler than a link checker.

Short answer

• Best overall for enterprise: JetOctopus
• Best technical SEO crawler: Screaming Frog
• Best enterprise platform: Lumar/Botify
• Best reporting: Sitebulb
• Best DIY stack: custom crawler + database + scheduled checks

For a site with millions of pages and a primary goal of finding broken links and redirect chains, I would usually choose JetOctopus for continuous monitoring and keep Screaming Frog for deep investigations. SEO Automation Club Screaming Frog

If the goal is very large sites (100k → millions of URLs) and specifically finding broken links, redirects, redirect chains, and loops, I’d shortlist these:

My picks

1. Best overall for serious technical crawling: Screaming Frog

It gives you exceptionally granular control over crawling, filtering and exporting. It detects 404/server errors and can follow redirects through multiple hops, identifying chains and loops. Screaming Frog Screaming Frog

For genuinely huge crawls, use database storage rather than RAM storage; Screaming Frog specifically recommends this for particularly large sites. Screaming Frog

screamingfrog.co.uk

2. Best cloud alternative: Sitebulb

Sitebulb is particularly attractive if you don't want your workstation's RAM/disk to become the bottleneck. Its current Cloud offering supports up to 10 million URLs per audit. Sitebulb

It has dedicated reporting for broken internal links, links pointing to redirects, and redirect chains, with redirect-chain data exportable for further processing. Sitebulb Support

It also gives you unusually good control over crawl scope—parameters, directories, external URLs, subdomains, resources, etc.—which is critical when you're dealing with millions of URLs. Sitebulb Support Sitebulb Support

sitebulb.com

3. Best for enterprise-scale crawling + server logs: JetOctopus

If you're dealing with a genuinely enormous site and want to combine crawler data + server log data + Google Search Console/GA data, JetOctopus is particularly compelling. It positions itself specifically around enterprise sites and combines crawling, logs, GSC and GA4. TechSEO AI Search

jetoctopus.com

One important distinction

For a million-page site, don't just launch a crawler at the homepage and let it rip.

A much more efficient approach is:

1. Crawl internal HTML links to discover broken/redirected links.
2. Upload XML sitemap URLs as an additional source.
3. Import known URLs from GSC/analytics where possible.
4. Exclude tracking parameters, faceted-navigation explosions, search URLs, calendars, etc.
5. Disable unnecessary JavaScript/resource crawling if your objective is strictly links/redirects.
6. Run a targeted redirect-chain crawl against the URLs returning 3xx.
7. Export the results as something like:

source URL → hop 1 → hop 2 → final URL → status code.

Sitebulb explicitly recommends combining crawl sources such as XML sitemaps and Search Console/Analytics when you need to ensure you're discovering URLs that aren't internally linked. Sitebulb Support

If your primary objective is only broken links + redirect chains

I'd rank them:

Screaming Frog → Sitebulb Cloud → JetOctopus → Lumar

For 100k–500k URLs, I'd probably choose Screaming Frog or Sitebulb.

For 500k–10M+ URLs, I'd lean toward Sitebulb Cloud or JetOctopus, unless you specifically need Screaming Frog's extremely granular desktop workflow.

And if you're building an automated pipeline rather than doing SEO audits manually, there's another interesting option: a custom high-concurrency HTTP crawler (Go/Rust/Python) that reads sitemap/URL inventories and records every redirect hop. For pure broken-link/redirect detection, that can be dramatically faster and cheaper than a full SEO crawler because you don't need to parse/render every page.

It also gives you unusually good control over crawl scope—parameters, directories, external URLs, subdomains, resources, etc.—which is critical when you're dealing with millions of URLs. Sitebulb Support Sitebulb Support

sitebulb.com

3. Best for enterprise-scale crawling + server logs: JetOctopus

If you're dealing with a genuinely enormous site and want to combine crawler data + server log data + Google Search Console/GA data, JetOctopus is particularly compelling. It positions itself specifically around enterprise sites and combines crawling, logs, GSC and GA4.

For very large sites, I’d shortlist these:

1. jetoctopus.com — best for massive sites

If you're talking tens or hundreds of millions of URLs, this would be my first choice. JetOctopus currently advertises crawling 10M, 50M, 100M+ pages without a crawl cap, and its crawler can run at roughly 1M pages/day. TechSEO AI Search TechSEO AI Search

Its redirect-chain analysis is particularly relevant: it follows redirect hops and stores the complete chain, including a redirect-chain length field. TechSEO AI Search

Choose it if: you're dealing with ecommerce/marketplaces, international sites, millions of URLs, or want recurring crawls rather than occasional audits.

2. sitebulb.com — best overall

Sitebulb is probably my recommendation for the sweet spot between enormous crawling capability and actually pleasant analysis.

Its Cloud product supports up to 10M URLs per audit, while its enterprise offering emphasizes crawling at hundreds of URLs/second and exporting millions of rows directly to S3. Sitebulb Sitebulb

For your particular use case, it explicitly reports:

• Broken internal links
• Internal links pointing to redirects
• Broken/redirected external links
• Full redirect chains, exportable for analysis Sitebulb Sitebulb Support

It also has useful controls for large crawls—excluding external URLs, subdomains, resources, parameters, etc.—which can dramatically reduce unnecessary crawl volume. Sitebulb Support

Choose it if: you want excellent diagnostics and reporting without building your own analysis pipeline.

3. screamingfrog.co.uk — best for technical control

Still one of the best choices if you want to control exactly how the crawl works.

For large crawls, its database storage mode is specifically designed for scale. The default limit is 5M URLs, but Screaming Frog says it can go substantially higher; it gives approximately 10M URLs on a machine with 16 GB RAM and a 500 GB SSD as an example. Screaming Frog

The big advantage is flexibility: custom extraction, URL rewriting, JavaScript rendering, custom search, API integrations, crawl configuration, etc.

Choose it if: you're an SEO engineer/technical SEO and want granular control over the crawl rather than a SaaS crawler doing most of the work for you.

What I'd actually use

For a 10M+ URL site, I'd probably use:

JetOctopus → primary crawler
Screaming Frog → targeted technical investigations
Sitebulb → reporting/diagnosis and stakeholder-friendly analysis

For a 500K–5M URL site, I'd lean toward Sitebulb Cloud unless you specifically prefer Screaming Frog's workflow.

One important optimization: don't just crawl the site's discovered HTML links. For serious broken-link detection, combine crawl discovery + XML sitemaps + historical URLs/GSC data + server logs. Otherwise you can miss URLs that aren't currently internally linked. Sitebulb, for example, explicitly recommends adding XML sitemaps and other URL sources when the site's architecture doesn't expose every URL. Sitebulb Support

If your goal is specifically "crawl 50M+ URLs as fast as possible and produce a machine-readable list of every 404 and redirect chain", I can also give you a JetOctopus vs Screaming Frog vs custom crawler architecture comparison, including throughput, storage, concurrency, HTTP handling, and what I'd use in a CI/CD pipeline.

For very large websites (hundreds of thousands to millions of URLs), the “best” crawler depends on whether you need a one-time technical audit, continuous monitoring, JavaScript rendering, API access, or engineering integration. For broken links and redirect chains specifically, these are the strongest options: theStacc RankYak

Best overall tools

Crawlmouse Lorenzo Solís## My recommendations by scenario

1. Millions of URLs, continuous monitoring

Pick:

• Lumar
• Botify

Why:

• Run scheduled crawls without tying up a workstation
• Detect new 404s and redirect regressions automatically
• Share findings across SEO, engineering, and content teams
• Better for sites where changes ship constantly

These are the tools I would consider for:

• ecommerce catalogs
• marketplaces
• news publishers
• documentation sites
• multinational sites

Lorenzo Solís

2. Best value + maximum control

Pick:

• Screaming Frog SEO Spider

Strengths:

• Finds: - 404/410 errors
• 5xx server errors
• redirect chains
• redirect loops
• orphan URLs
• broken external links
• Can crawl with JavaScript rendering
• Supports custom extraction using XPath, CSS selectors, and regex
• Excellent exports for developers/data analysis

It is often the first tool technical SEO teams reach for because it gives raw crawl data without hiding details behind dashboards. Screaming Frog

For very large crawls, run it with:

• lots of RAM (32–64GB+)
• SSD storage
• crawl limits tuned carefully
• database storage mode enabled

3. Best for handing reports to non-SEO teams

Pick:

• Sitebulb

Advantages:

• Better visualizations
• Easier prioritization
• Good explanations of why an issue matters
• Useful when developers or executives need actionable reports

It is less about raw crawling power and more about turning crawl data into decisions. Teksyte

4. If you want to build your own crawler

For engineering teams, consider:

• Apache Nutch — distributed crawling framework
• Scrapy — flexible custom crawler
• Apache Solr or Elasticsearch — indexing crawl results
• Playwright — JavaScript rendering

A custom stack makes sense when you need:

• billions of URLs
• custom business rules
• integration into CI pipelines
• proprietary dashboards

For finding redirect chains efficiently, prioritize these features

Look for:

• HEAD request support

Reduces bandwidth versus full GET requests.

• Parallel crawling controls

Ability to tune concurrency without overwhelming servers.

• Redirect hop reporting

Example:

/old-page
 → 301
 → /intermediate-page
 → 302
 → /final-page

• Canonical + redirect conflict detection

• redirecting pages with canonical tags pointing elsewhere
• chains caused by migrations
• Sitemap crawling

Compare:

• URLs discovered internally
• URLs in XML sitemaps
• URLs returning errors
• API/export access

Critical for large sites.

A practical enterprise workflow

For a large production website, I would usually combine:

1. Lumar or Botify

• scheduled enterprise crawl
• monitoring
• Screaming Frog

• deep investigations
• custom extraction
• migration testing
• Server logs

• confirm what Googlebot actually hits
• CI/CD checks

• block releases that introduce: - new 404s
• redirect chains
• accidental noindex
• broken canonicals

Short version

• Best enterprise: Lumar / Botify
• Best technical crawler: Screaming Frog
• Best reporting: Sitebulb
• Best custom solution: Scrapy + Playwright + your own data pipeline

For a site with 1M+ URLs, I would generally avoid relying only on desktop crawlers and use a cloud crawler or a distributed crawler architecture. Lorenzo Solís

For very large sites, the best choice depends mainly on whether you mean 100k URLs, 1M+, or 10M+, and whether you need a one-off audit or continuous monitoring.

1. Lumar — best when "very large" really means millions

lumar.io is particularly attractive for huge sites. Lumar reports crawl speeds of up to 450 URLs/sec non-rendered and 350 URLs/sec rendered, and supports analysis of redirect chains, HTTP status codes, link structure, and broken resources. Lumar Lumar

For a 5–20M URL site, I'd put Lumar near the top of the list because you're less constrained by the hardware running the crawler.

2. Sitebulb — probably the best choice for link-specific auditing

Sitebulb is unusually good if your actual objective is:

"Show me every broken internal link, every redirected internal link, and every redirect chain, then tell me exactly which pages contain those links."

It explicitly reports broken links, internal links to redirects, and redirect chains, with redirect-chain data exportable for further analysis. Sitebulb Sitebulb Support

Its Cloud version supports up to 10 million URLs per audit, while Desktop supports up to 500,000 URLs. Sitebulb

One particularly useful detail: Sitebulb distinguishes a broken link from merely having a 404 page—the broken link is the link pointing to that 404/410 URL. Sitebulb Support

3. Screaming Frog — best if you want maximum control

screamingfrog.co.uk remains my choice for technically sophisticated one-off crawls.

It can:

• crawl sites and identify 404/broken links;
• inspect 301/302/other 3xx responses;
• follow multiple redirects to the final destination;
• identify redirect loops;
• bulk-check a supplied URL list rather than crawling the entire site. Screaming Frog Screaming Frog

The downside for truly enormous sites is that you're more dependent on the machine and crawl configuration than with cloud-native enterprise crawlers.

What I'd choose by size

• <100k URLs: Screaming Frog or Sitebulb Desktop
• 100k–500k: Screaming Frog or Sitebulb
• 500k–5M: Sitebulb Cloud or Lumar
• 5M–10M: Sitebulb Cloud or Lumar
• 10M+ / huge enterprise: Lumar, Botify, or another enterprise crawler
• Need server-log analysis too: Botify / JetOctopus become much more interesting

One important optimization

For this particular job, don't automatically render JavaScript.

If you're primarily looking for HTTP errors and redirects, an HTML/HTTP crawl is dramatically cheaper and faster than browser rendering. For example, Sitebulb describes its HTML crawler as its fastest crawler, while Chrome crawling requires downloading page resources and therefore takes longer. Sitebulb Support

I'd run the workflow roughly like this:

1. Crawl HTML/HTTP first.
2. Extract every internal URL and HTTP status.
3. Identify 4xx/5xx destinations and their source pages.
4. Identify every internal link whose target is 3xx.
5. Follow each redirect until the final destination.
6. Flag: - redirect chains;
7. redirect loops;
8. redirects ending in 4xx/5xx;
9. internal links pointing to redirects;
10. multiple redirects before reaching 200;
11. links to HTTP when HTTPS is canonical.
12. Only then run a JS-rendered crawl against sections where discovery depends on JavaScript.

If you tell me roughly how big the site is (e.g. 500k, 5M, 50M URLs) and whether you're looking for a one-time crawl or continuous monitoring, I can narrow this down to the best 2–3 options and compare their architecture, speed, cost, and API/export capabilities.

It explicitly reports broken links, internal links to redirects, and redirect chains, with redirect-chain data exportable for further analysis. sitebulb.com support.sitebulb.com

Its Cloud version supports up to 10 million URLs per audit, while Desktop supports up to 500,000 URLs. sitebulb.com

One particularly useful detail: Sitebulb distinguishes a broken link from merely having a 404 page—the broken link is the link pointing to that 404/410 URL.

3. Screaming Frog — best if you want maximum control

For very large websites (millions+ URLs), I’d shortlist these:

• Screaming Frog SEO Spider — excellent all-around crawler; strong broken-link, redirect-chain, canonical, and JavaScript auditing. Best for deep technical SEO work, though very large crawls may require careful memory/configuration.
• Sitebulb — excellent visualization and diagnostics; easier to interpret than many enterprise crawlers, but less ideal when sheer crawl scale is the priority.
• jetoctopus.com — particularly strong for huge sites. Cloud crawling, large URL volumes, log-file analysis, and useful redirect/broken-link reporting make it one of my top choices at enterprise scale.
• botify.com — enterprise-grade crawling and log analysis. Very good when you need to combine crawl data with Googlebot behavior and prioritize issues across millions of pages.
• lumar.io — strong enterprise technical-SEO platform with large-scale crawling, monitoring, and integrations.
• semrush.com — convenient if you're already using Semrush, but I wouldn't make it my first choice for extremely large, highly technical crawl workloads.
• ahrefs.com — useful for ongoing site health monitoring, but again, less specialized for massive crawl engineering than JetOctopus/Botify/Lumar.

For your specific use case

If the main goal is finding broken links + redirect chains efficiently at very large scale, I'd rank them:

One important distinction

For millions or tens of millions of URLs, don't just look for a crawler that reports "redirect chain." You want one that can efficiently capture something like:

URL A → 301 → URL B → 302 → URL C → 200

and ideally tell you:

• which internal links initiate the chain
• chain length
• redirect status codes
• final destination
• redirect loops
• links pointing directly to redirected URLs
• broken URLs returning 4xx/5xx
• redirect behavior by bot/user-agent
• whether the destination is canonical/indexable
• crawl depth and affected pages

For really large sites, crawl data + server/CDN logs is considerably more powerful than crawling alone. A crawler tells you what it can discover; log analysis tells you what Googlebot and real users actually request.

My practical recommendation: start with JetOctopus if scale and efficiency are the priority; choose Botify or Lumar if you're operating an enterprise SEO program and want sophisticated log/crawl analysis; choose Screaming Frog if you want the strongest hands-on technical crawler and your site is within its practical scale limits.

URL A → 301 → URL B → 302 → URL C → 200

and ideally tell you:

• which internal links initiate the chain
• chain length
• redirect status codes
• final destination
• redirect loops
• links pointing directly to redirected URLs
• broken URLs returning 4xx/5xx
• redirect behavior by bot/user-agent
• whether the destination is canonical/indexable
• crawl depth and affected pages

For really large sites, crawl data + server/CDN logs is considerably more powerful than crawling alone. A crawler tells you what it can discover; log analysis tells you what Googlebot and real users actually request.

If you're talking about hundreds of thousands to millions of URLs, I'd narrow the field considerably. The best choice depends on whether you prioritize raw crawl speed, diagnostics, or ease of use.

1. Lumar — my pick for truly enormous sites

If you're dealing with 1M–100M+ URLs, Lumar is probably where I'd start. Its current crawler claims speeds up to 450 URLs/sec for non-rendered pages and 350 URLs/sec rendered, and it supports segmentation and detailed technical metrics including HTTP status, redirects, link structure and broken resources. Lumar Lumar

The big advantage is architecture: you're not waiting for your laptop's RAM/CPU to chew through a giant crawl.

Best when: you need repeated enterprise crawls, very large sites, custom extraction, or automated technical monitoring.

2. Screaming Frog — best diagnostic tool

For actually investigating why links are broken, I'd still put Screaming Frog near the top.

Its redirect reporting is particularly good: it can map redirect chains, show the number of hops, identify loops, and distinguish different chain types. It can also follow redirects in List mode, which is extremely useful when you already have a large URL dataset. Screaming Frog

Its broken-link workflow can also trace a 404 back through redirects to the original source page, rather than merely telling you "this URL is 404." Screaming Frog

Best when: you're an SEO/engineer who wants to inspect and export the underlying crawl data rather than just receive a health score.

3. Sitebulb Cloud — excellent middle ground

Sitebulb has become particularly interesting for large sites. Its Cloud product supports up to 10 million URLs per audit, runs crawls on its infrastructure, and supports JavaScript crawling at scale. Sitebulb Sitebulb

Its reporting around redirects is excellent: it explicitly identifies broken redirects, redirect loops and chained redirects, and can export redirect-chain data. Sitebulb Support Sitebulb

I especially like it when the people consuming the results aren't necessarily crawling experts.

Best when: you want enterprise-scale crawling but also want very approachable visualization and prioritization.

4. Oncrawl — best if crawl data feeds a larger SEO analytics operation

Oncrawl is worth considering when crawling isn't the end goal. Its redirect analysis identifies chains and loops and can follow substantially long chains during analysis. Oncrawl Help

I'd favor it when you're combining crawl data with things like Google Search Console, analytics, log files, rankings, and large-scale SEO analysis, rather than simply looking for 404s.

What I'd use in practice

For a very large website, I'd actually use a two-stage approach:

Stage 1 — discover efficiently

Use Lumar, Sitebulb Cloud, or Screaming Frog to crawl the site and identify:

• 404/410 links
• 5xx links
• links pointing to 3xx URLs
• redirect chains
• redirect loops
• redirects ending in 4xx/5xx
• canonical chains
• orphan URLs
• URL-parameter explosions

Stage 2 — aggressively validate the problem URLs

Take the resulting URL/source pairs and run a targeted HTTP crawl rather than repeatedly crawling the entire site.

This is particularly useful for enormous sites because you don't necessarily need to render 10 million pages just to establish that A → B → C → 404.

One important distinction

Don't confuse "URLs returning 404" with "broken links."

A 404 page isn't necessarily a broken link. The broken link is the link on another page that points to that 404. Sitebulb explicitly makes this distinction, which is important when generating remediation lists. Sitebulb Support

For redirect chains, I'd similarly want the output to look roughly like:

/source-page
    ↓
/old-url        301
    ↓
/older-url      301
    ↓
/current-url    301
    ↓
/final-page     200

rather than simply reporting "/old-url = 301."

If you tell me roughly how large the site is (e.g. 500K, 5M, 50M+ URLs) and whether you need JavaScript rendering, I can recommend the fastest/most cost-effective setup and crawl configuration.

Its reporting around redirects is excellent: it explicitly identifies broken redirects, redirect loops and chained redirects, and can export redirect-chain data. support.sitebulb.com Sitebulb

I especially like it when the people consuming the results aren't necessarily crawling experts.

Best when: you want enterprise-scale crawling but also want very approachable visualization and prioritization.

4. Oncrawl — best if crawl data feeds a larger SEO analytics operation

Oncrawl is worth considering when crawling isn't the end goal. Its redirect analysis identifies chains and loops and can follow substantially long chains during analysis.

I'd favor it when you're combining crawl data with things like Google Search Console, analytics, log files, rankings, and large-scale SEO analysis, rather than simply looking for 404s.

What I'd use in practice

For a very large website, I'd actually use a two-stage approach:

Stage 1 — discover efficiently

For crawling very large websites (hundreds of thousands to millions of URLs) to find broken links, redirect chains, redirect loops, and crawl issues, the best tools depend on whether you need a desktop crawler, cloud-scale crawler, API integration, or custom pipeline.

Best large-scale website crawlers

Best open-source / engineering-focused options

nutch.apache.org

Best when you need a crawler you can customize.

Pros

• Designed for very large-scale crawling
• Distributed crawling architecture
• Integrates with Hadoop/Solr ecosystems

Cons

• Requires engineering effort
• Not an out-of-box SEO audit tool

github.com

Used for web-scale archival crawling.

Pros

• Handles enormous crawl workloads
• Mature crawler architecture

Cons

• Not optimized for SEO diagnostics
• You need to build reporting logic

Custom crawler stacks

For very large sites (10M+ URLs), many teams build pipelines using:

• scrapy.org — Python crawling framework
• kafka.apache.org — URL queue/event streaming
• redis.io — fast URL deduplication queues
• postgresql.org or clickhouse.com — storing crawl results
• playwright.dev — JavaScript rendering when needed

A custom crawler lets you detect things most SEO crawlers struggle with:

• redirect chains across millions of URLs
• redirect changes over time
• regional redirects
• broken assets
• API endpoint failures
• JS-generated links
• authentication-gated areas

Best tools specifically for redirect chains

1. Screaming Frog

Probably the easiest choice.

It can identify:

• 301 → 301 → 200 chains
• 302 chains
• redirect loops
• redirect hops
• unnecessary redirects

Useful settings:

• Enable "Always Follow Redirects"
• Increase crawl memory
• Use database storage mode for very large sites

2. Command-line tools for targeted checking

For URL lists rather than full crawling:

github.com

Example:

cat urls.txt | httpx -status-code -follow-redirects

Good for:

• millions of URLs
• CI/CD checks
• monitoring migrations

3. Bulk HTTP testing

curl.se or custom async scripts can be extremely fast.

A typical high-volume architecture:

URL list
   |
   v
Async workers (10k concurrent requests)
   |
   +--> status code
   +--> redirect hops
   +--> final URL
   +--> response time
   +--> errors
   |
   v
Database + dashboard

Python example stack:

• aiohttp
• asyncio
• tldextract
• PostgreSQL/ClickHouse

My recommendations by site size

Under 500k URLs

Use:

1. Screaming Frog
2. Sitebulb
3. Ahrefs Site Audit

500k–10M URLs

Use:

1. Screaming Frog (with database storage)
2. Oncrawl
3. Lumar
4. Botify

10M+ URLs

Use:

1. Botify / Lumar / Oncrawl
2. Custom Scrapy-based crawler
3. Apache Nutch / Heritrix for specialized needs

For the fastest broken-link detection pipeline

A strong setup is:

1. Discover URLs

• XML sitemaps
• internal crawl
• server logs
• Google Search Console exports
• Run async HTTP crawler

• follow redirects
• record every hop
• Store

• URL
• status code
• redirect path
• canonical target
• timestamp
• Report

• 404/410 pages
• 5xx errors
• redirect chains >1 hop
• redirect loops
• orphan URLs

For a very large site migration or SEO cleanup project, I would generally choose Screaming Frog for up to a few million URLs, and Botify/Lumar/Oncrawl or a custom crawler for tens of millions of URLs.

Use:

1. Botify / Lumar / Oncrawl
2. Custom Scrapy-based crawler
3. Apache Nutch / Heritrix for specialized needs

For the fastest broken-link detection pipeline

A strong setup is:

For very large websites, the best choice depends on whether you prioritize raw crawl scale, SEO diagnostics, API automation, or distributed crawling.

Best options

• Screaming Frog SEO Spider — Best overall for technical SEO. Excellent at finding broken links, redirect chains/loops, orphaned URLs, canonicals, and internal-link issues. Its database storage mode makes it much more practical for very large crawls.
• Sitebulb — Best for visualization and diagnosing why a site has redirect chains or broken-link problems. Particularly good for turning crawl data into actionable reports.
• Oncrawl — Best for enterprise-scale crawling + log-file analysis. Useful when you want to correlate crawler discoveries with what Googlebot actually crawls.
• Botify — Best for extremely large enterprise sites where crawl-budget optimization and Googlebot behavior matter. Designed around very large datasets and enterprise SEO workflows.
• JetOctopus — Strong choice for large-scale, fast crawling, particularly when you need to crawl millions of URLs and analyze technical SEO issues.
• Ahrefs Site Audit — Convenient cloud crawler with good broken-link and redirect reporting, especially if you're already using Ahrefs for SEO.
• Semrush Site Audit — Similar advantage: easy cloud-based crawling and reporting, though I'd generally favor a specialized crawler for extremely large/custom sites.
• Custom crawler (Scrapy/Go/Node) — Best if you need tens or hundreds of millions of URLs, custom URL-discovery rules, distributed workers, or integration with your own data pipeline.

My picks by scale

For broken links + redirect chains specifically

The important thing is that the crawler shouldn't merely report 301 or 404. For each discovered URL, you ideally want a record like:

source_url
→ requested_url
→ status_code
→ Location
→ status_code
→ Location
→ final_url
→ final_status

That lets you distinguish:

/page-a
  → 301 /page-b
  → 301 /page-c
  → 200 /page-final

from a problematic loop:

/page-a
  → 301 /page-b
  → 302 /page-a
  → 301 /page-b
  → ...

For very large sites, I'd also look for these capabilities:

1. Concurrent/asynchronous crawling with configurable request rates.
2. Persistent crawl state, so a crawl can resume without starting over.
3. Disk/database-backed storage rather than holding the URL graph in RAM.
4. Redirect-chain tracking, including loops and mixed 301/302/307/308 chains.
5. Canonical and hreflang validation alongside link checking.
6. JavaScript rendering only when necessary—rendering every page can make a huge crawl dramatically slower.
7. URL deduplication and normalization before fetching.
8. Custom extraction for links inside JSON, JavaScript, XML, APIs, etc.
9. Distributed workers if you're getting into tens of millions of URLs.
10. Rate limiting per hostname/path to avoid overwhelming the site.

If you're dealing with something like 10M+ URLs, I would not simply throw the entire site at a desktop SEO crawler. A distributed crawler or enterprise platform becomes much more attractive.

If you tell me roughly how many URLs (100K / 1M / 10M / 100M+), whether the site is JavaScript-heavy, and whether you need to crawl from the public internet or from a sitemap/list of URLs, I can narrow this down to the best 2–3 options and explain the architecture I'd use.

If the goal is very large sites + broken links + redirect chains, I’d shortlist these:

1. Lumar — best when raw crawling speed matters

Lumar is particularly compelling for huge sites. Its crawler reports speeds of up to 450 URLs/sec without rendering and 350 URLs/sec rendered, and it specifically supports redirect chains, HTTP status codes, broken resources, and link structure. Lumar Lumar

For a 5–20M URL site where crawl duration itself is a major constraint, I'd put Lumar near the top.

2. Sitebulb Cloud — my choice for most teams

Sitebulb has a particularly nice combination of scale + analysis. Its Cloud product supports up to 10 million URLs per audit, while its documentation explicitly covers identifying broken links and exporting redirect chains. Sitebulb Sitebulb Support

The useful distinction is that it doesn't just tell you "there are 37,000 redirects." You can investigate the URLs and links responsible and export the redirect-chain data for further processing.

It also lets you exclude things such as external URLs, parameters, resources, or entire site sections—important because controlling crawl scope is often more valuable than simply throwing more hardware at the crawler. Sitebulb Support

3. Screaming Frog — best if you want maximum control

Screaming Frog remains one of my favorites for technical investigations. It directly supports:

• 404/5xx discovery
• source URLs for broken links
• 301/302/307/308 analysis
• redirect chains and loops
• bulk redirect auditing from URL lists
• JavaScript rendering
• custom extraction with XPath/CSS/regex Screaming Frog

Its major disadvantage for very large sites is that you're generally more constrained by your own machine/resources than with a cloud-native enterprise crawler.

4. Oncrawl — particularly interesting if you have server logs

Oncrawl becomes more attractive if the question isn't merely "what can my crawler discover?", but "what is Google actually crawling?"

Combining crawl data with server-log data can expose an important class of problems: URLs that aren't necessarily prominent in your crawl but are consuming significant crawler activity because of redirects, obsolete URLs, parameters, etc.

For your specific use case

If I were building a workflow for a multi-million-URL website, I'd use:

Lumar or Sitebulb Cloud → crawl → export URL/link data → programmatically analyze redirect graphs.

The last part is important. Don't rely solely on the crawler's "redirect chain" report.

Represent redirects as a directed graph:

/page-a
   ↓ 301
/page-b
   ↓ 302
/page-c
   ↓ 301
/page-d 200

Then calculate:

• chain length
• final destination
• number of hops
• redirect loops
• redirect-to-redirect links
• redirects ending in 4xx/5xx
• internal links pointing to redirects
• percentage of links requiring ≥2 hops
• orphaned/obsolete redirect destinations
• chains that cross domains/protocols
• repeated destinations receiving thousands of redirected links

That approach scales much better for serious remediation than manually inspecting crawler reports.

One important optimization

For broken-link hunting, you don't necessarily need to crawl/render every page in full.

A fast first pass can collect:

source URL
→ outgoing URL
→ HTTP status
→ Location header
→ final status
→ chain length

Then run expensive rendering/HTML analysis only on the URLs that need it. This can make an enormous difference on sites with millions of URLs.

My ranking:
Lumar if speed/scale is #1 → Sitebulb Cloud if analysis and usability matter most → Screaming Frog if you want maximum technical control → Oncrawl if log analysis is part of the problem.

If you're dealing with hundreds of thousands to millions of URLs, I’d narrow the field to these:

My picks

1. Lumar — best if the site is truly enormous

Lumar is particularly compelling when speed is the priority. It advertises crawling millions of URLs at speeds up to 450 pages/sec, with crawl segmentation and reporting for redirect chains, HTTP status, broken resources, and link structure. Lumar

I'd choose it for a multi-million-URL enterprise site where you need repeated crawls rather than occasional audits.

2. Screaming Frog — best redirect-chain investigator

For actually understanding why a redirect is problematic, Screaming Frog remains one of my favorites. Its redirect reports map the complete chain, number of hops, source and final destination, and identify loops. Screaming Frog Screaming Frog

It can also follow redirects until the final non-3XX destination in List Mode, which is extremely useful for auditing migration URL lists. Screaming Frog Screaming Frog

For broken links, it gives you the source page → broken URL relationship and bulk exports of those relationships. Screaming Frog

3. Sitebulb — best overall workflow

I'd pick Sitebulb if you want something easier to operate than an enterprise platform while still handling very large sites. Its Cloud product supports audits up to 10 million URLs, and it specifically reports broken internal links, links to redirects, and redirect chains. Sitebulb Sitebulb

It also has a nice optimization: after fixing problems, you can re-audit only failed URLs rather than recrawling the entire site. Sitebulb Support

4. Botify — best enterprise SEO platform

Botify is more than a crawler. Its cloud SiteCrawler is designed around very large sites and can render JavaScript, identify broken links, and analyze thousands of technical data points. Botify Knowledge Base

Its HTTP Codes reporting specifically surfaces redirect chains and loops, while its Outlinks report lets you analyze broken links by HTTP status. Botify Knowledge Base Botify Knowledge Base

5. JetOctopus — worth considering for raw crawl performance

I'd put JetOctopus on the shortlist if your priority is fast cloud crawling and handling large URL datasets, particularly if you're less interested in the broader enterprise SEO platform that comes with Botify/Lumar.

What I'd actually use

For a 500K–5M URL site, my preference would be:

Sitebulb Cloud + Screaming Frog

Use Sitebulb Cloud for the regular, large-scale crawl and monitoring, then Screaming Frog for particularly nasty migration/redirect investigations.

For 5M+ URLs or very frequent crawls, I'd move toward Lumar or Botify.

For a site migration, however, I'd lean heavily toward Screaming Frog because its redirect-chain tooling is exceptionally well suited to taking a giant old-URL list and determining:

old URL → 301 → 301 → 302 → 404

rather than merely telling you that the original URL returned a redirect. Screaming Frog Screaming Frog

One important distinction: don't just look for 404 pages. For fixing the actual site, you want the relationship:

source page → linked URL → HTTP status → redirect hops → final URL/status

That lets you prioritize things like internal link → 301 → 301 → 200 and internal link → 301 → 404, which are much more actionable than a simple list of 404s. Sitebulb and Screaming Frog both expose this relationship particularly well. Sitebulb Support Screaming Frog

If you tell me roughly how many URLs you're crawling (100K / 1M / 10M / 100M+) and whether it's a JS-heavy site, I can give you a more specific recommendation—including the fastest/cheapest architecture for doing it.

If the goal is very large sites + broken links + redirect chains, I’d narrow the field to these:

1. Screaming Frog — best if you want control

Screaming Frog is probably my first choice if you're comfortable working with exports and crawl configuration.

It explicitly supports millions of URLs, has database storage for large crawls, and provides dedicated reports for redirect chains, redirect loops, redirects-to-errors, and their individual hops. Screaming Frog Screaming Frog

The particularly useful workflow is:

• Crawl the site.
• Filter 4XX responses.
• Export the source pages linking to those URLs.
• Examine Redirect Chains and Redirects to Errors.
• Use Always Follow Redirects when auditing a known URL list/migration so every hop through to the final destination is captured. Screaming Frog Screaming Frog

For really big crawls, Screaming Frog recommends database storage + SSD. Their current guidance says roughly 4 GB allocated RAM can handle ~2M URLs, 8 GB ~5M, and 16 GB ~10M, depending on the site. Screaming Frog

Best choice if: you want granular control over what gets crawled and don't mind managing the infrastructure yourself.

2. Sitebulb — probably the easiest large-scale option

Sitebulb is particularly attractive if you want the crawler to do more of the analysis for you.

Its Cloud product currently supports up to 10 million URLs per audit, while the desktop version supports up to 500,000. Sitebulb

For your specific use case, Sitebulb has dedicated reporting for:

• Broken internal links
• Links to redirected URLs
• Redirects that terminate in 4XX/5XX errors
• Redirect chains
• Redirect loops

It can also export redirect-chain data for further analysis. Sitebulb Support Sitebulb

Best choice if: you're auditing millions of URLs and want good visualization, prioritization, and reporting without spending as much time configuring the crawler.

3. Botify — for genuinely massive enterprise sites

Botify is where I'd look once you're dealing with tens of millions of URLs, multiple properties, or enterprise SEO teams.

Botify's SiteCrawler analyzes broken links and HTTP status codes and specifically surfaces multiple redirects, redirect chains, and redirect loops, with drill-down into the URLs involved. Botify Botify Knowledge Base

The advantage isn't just raw crawling—it is the surrounding enterprise analytics and segmentation. You can, for example, identify whether redirect/broken-link problems are concentrated in a particular product category, country, template, or site section.

Best choice if: crawling is part of a broader enterprise SEO/data platform rather than a one-off technical audit.

4. JetOctopus — strong cloud alternative

I'd consider JetOctopus when you want cloud-based crawling and large datasets without running something like Screaming Frog locally.

It's particularly worth comparing against Sitebulb/Botify if crawl speed and handling of large ecommerce sites are important.

What I'd choose

For your specific requirement, I'd rank them:

1. Screaming Frog → best technical crawler and maximum control
2. Sitebulb Cloud → best combination of scale + usability
3. Botify → best for enterprise/tens-of-millions scale
4. JetOctopus → strong cloud alternative

One important distinction: don't just look for "404 detection." For a large site, you want the crawler to preserve the relationship:

source page → linked URL → redirect 1 → redirect 2 → final URL → final HTTP status

That lets you distinguish:

Page A → 404 ❌

from

Page A → 301 → 404 ❌

from

Page A → 301 → 301 → 200 ⚠️

from

Page A → 301 → 302 → 301 → 200 ⚠️

Screaming Frog and Sitebulb are particularly good at this level of analysis. Screaming Frog Sitebulb Support

If you're talking about a site with 10M+ URLs, I'd strongly favor a cloud crawler over simply throwing more RAM at a desktop crawler. For a 1–5M URL site, however, Screaming Frog with database storage is extremely compelling.

For crawling very large websites (hundreds of thousands to millions of URLs) to find broken links, redirect chains, redirect loops, orphaned pages, and crawl issues, the best tools depend on whether you prioritize speed, SEO auditing, custom pipelines, or enterprise-scale crawling.

Best large-scale website crawling tools

Best choices by use case

1. Huge production website (1M+ URLs)

Use:

• Lumar
• Botify
• JetOctopus

Why:

• Distributed cloud crawling
• Scheduled recurring crawls
• Crawl budget controls
• Historical comparisons
• API access

These are better than running a desktop crawler when the site is very large.

2. Maximum control / building your own crawler

Use:

• Scrapy
• Apache Nutch
• Heritrix

A custom crawler pipeline can:

• Stream URLs into a queue
• Crawl asynchronously
• Store results in Elasticsearch/ClickHouse/PostgreSQL
• Detect: - 404/410 errors
• 301→301→200 chains
• redirect loops
• canonical problems
• mixed content
• slow responses

Typical architecture:

URL Frontier
      |
      v
Distributed Crawlers
      |
      +---- HTTP Status Collector
      |
      +---- Redirect Analyzer
      |
      +---- Link Graph Database
      |
      v
Reporting Dashboard

For very large sites, this often beats traditional SEO crawlers.

3. Best desktop tool for one-off audits

Use:

• Screaming Frog SEO Spider

It is probably the most popular technical SEO crawler because it handles:

• Broken internal links
• External broken links
• Redirect chains
• Redirect loops
• Canonical issues
• Hreflang issues
• XML sitemap validation
• JavaScript rendering

For millions of URLs, configure:

• Database storage mode instead of RAM mode
• Lower crawl speed to avoid server overload
• Custom user agent
• Crawl limits
• URL exclusions

For detecting redirect chains specifically

A good crawler should record the full redirect path:

Example:

/old-page
  ↓ 301
/moved-page
  ↓ 302
/new-page
  ↓ 200

Flag:

• More than 1 redirect hop
• Redirect chains across domains
• Temporary redirects left in production
• Loops:

A → B → C → A

Tools particularly good at this:

• Screaming Frog
• Lumar
• Botify
• JetOctopus
• Custom Scrapy crawler

For millions of URLs, avoid these mistakes

• Do not crawl everything from a single machine

Use distributed workers or cloud crawlers.

• Do not store only final status codes

Keep:

• original URL
• every redirect hop
• final URL
• response time
• crawl timestamp
• Do not ignore JavaScript-heavy sites

If pages generate links client-side, use browser rendering (Playwright/Puppeteer) selectively.

• Do not crawl without rate limits

Large crawls can accidentally overload production servers.

My shortlist

• Best overall SEO crawler: Screaming Frog SEO Spider
• Best enterprise crawler: Lumar or Botify
• Best for millions of URLs on a budget: JetOctopus
• Best developer solution: Scrapy + your own storage/analysis stack
• Best open-source distributed crawler: Apache Nutch

If the goal is specifically finding broken links and redirect chains on a very large site (10M+ URLs), I would lean toward a distributed Scrapy/Nutch pipeline or an enterprise cloud crawler, rather than a single-machine SEO crawler.

My shortlist

If the site is very large—hundreds of thousands to millions of URLs—I’d prioritize crawlers that can run distributed/cloud crawls rather than relying solely on a desktop machine.

My picks

1. Sitebulb — my default recommendation

For your specific use case, Sitebulb Cloud is probably the sweet spot. It supports crawls of up to 10 million URLs per audit, runs on Sitebulb's infrastructure rather than your workstation, and supports multiple large crawls simultaneously. Sitebulb Sitebulb

It explicitly reports:

• 4xx/5xx broken URLs
• the pages linking to those broken URLs
• redirected internal links
• redirect chains and chain length
• redirect loops
• redirect destinations

Its redirect-chain data can also be exported for bulk analysis. Sitebulb Support Sitebulb Support Sitebulb Support

Why I like it for huge sites: you can aggressively control what gets crawled. Excluding parameters, external links, unnecessary resources, search pages, faceted navigation, etc. can make an enormous difference to crawl efficiency. Sitebulb Support Sitebulb Support

2. Screaming Frog — best for hands-on technical work

screamingfrog.co.uk is still my choice when an SEO engineer wants maximum control over exactly what is being crawled.

It directly supports finding 404/server errors and auditing redirects, including redirect chains and loops. It can also bulk-export the errors and their source URLs. Screaming Frog

It's particularly good for:

• migration audits
• debugging complicated redirect rules
• crawling specific URL lists
• custom extraction
• inspecting individual URLs
• testing unusual server behavior
• integrating crawl data into your own scripts/pipelines

The limitation is scale: you're ultimately constrained by the machine running it. For a 5M–20M URL site, I'd generally move the primary crawl to a cloud/enterprise crawler.

3. Botify — best when "very large" means millions+

For a genuinely massive enterprise site, I'd look seriously at botify.com.

Its SiteCrawler is cloud-based and designed for large-scale crawling/rendering, including JavaScript rendering. It reports broken links and other technical problems, and its data model includes redirect chains, inlinks/outlinks, and crawl-related metrics. Botify Knowledge Base Botify Botify Knowledge Base

The big advantage isn't simply "it can crawl a lot." It's the ability to combine crawl data with enterprise-scale SEO analysis and monitoring.

I'd choose Botify over Sitebulb when you're dealing with something like:

• 10M+ URLs
• huge ecommerce catalogs
• international sites with many domains/subdomains
• frequent automated crawls
• large SEO teams
• API/data-warehouse workflows
• serious crawl-budget analysis

One important distinction

For finding broken links, don't just crawl URLs and look for 404s.

You ideally want a dataset like:

source_url
    ↓
linked_url
    ↓
HTTP status
    ↓
redirect target 1
    ↓
redirect target 2
    ↓
final URL
    ↓
final status

That lets you distinguish:

/page-a → /page-b → 200

from:

/page-a → /old → /older → /current → 200

and:

/page-a → /old → /missing → 404

The latter two are much more actionable than simply reporting "/page-a contains a redirect."

For maximum efficiency

For a huge site, I'd configure the crawl roughly like this:

1. Crawl internal HTML links first.
2. Add XML sitemaps as an additional URL source so orphaned URLs aren't missed. Sitebulb specifically recommends combining crawl sources when internal architecture doesn't expose every URL. Sitebulb Support
3. Exclude or separately analyze: - URL parameters
4. faceted navigation
5. internal search
6. tracking URLs
7. unnecessary external links
8. static resources unless you need them
9. Don't render JavaScript unless necessary. Sitebulb's HTML crawler is substantially quicker; Chrome rendering downloads page resources and takes longer. Sitebulb Support
10. Export source → broken URL and source → redirect chain relationships rather than just URL-level errors.
11. Prioritize internal links pointing to redirects and especially chains ending in 4xx/5xx.
12. Run the crawl repeatedly and compare against the previous crawl rather than processing millions of unchanged URLs from scratch where your platform supports it.

My short recommendation

• 100K–500K URLs: Screaming Frog or Sitebulb Desktop
• 500K–10M: Sitebulb Cloud
• 10M+ / enterprise: Botify
• Migration with lots of weird redirect rules: Screaming Frog
• Automated recurring monitoring: Sitebulb Cloud or Botify

If your goal is specifically "crawl 10–100M URLs as cheaply/quickly as possible and output a clean CSV of every broken link + complete redirect chain," that's a slightly different problem—I can also compare the tools specifically on crawl speed, concurrency, memory usage, API/export capabilities, and cost per million URLs.

from:

/page-a → /old → /older → /current → 200

and:

/page-a → /old → /missing → 404

The latter two are much more actionable than simply reporting "/page-a contains a redirect."

For maximum efficiency

For a huge site, I'd configure the crawl roughly like this:

If your priority is very large sites + efficient detection of 404s, redirect chains, loops, and bad internal links, I’d narrow the field to these:

1. Screaming Frog — best technical crawler

screamingfrog.co.uk

For finding exactly where broken links and redirect chains occur, this is probably my first choice.

It can:

• Find 404/410 and 5xx errors and show the pages linking to them.
• Follow redirects through multiple hops.
• Identify redirect chains and redirect loops.
• Export the complete chain, including source, intermediate URLs, and final destination.
• Crawl from the site or process a supplied URL list in bulk. Screaming Frog Screaming Frog

A particularly useful feature is its "Redirects to Errors" and "Redirect Chains" reports, which let you trace something like:

Page A → 301 → Page B → 302 → Page C → 404

back to the original source. Screaming Frog Screaming Frog

Best when: you have a technical SEO team that wants raw crawl data and maximum control.

2. Sitebulb Cloud — best for truly massive sites

sitebulb.com

If "very large" means hundreds of thousands to millions of URLs, I'd seriously consider Sitebulb Cloud.

Sitebulb specifically positions its cloud crawler for sites ranging from 500,000 to 5+ million URLs, with crawling performed on its servers rather than consuming your workstation's resources. Sitebulb Sitebulb

It has dedicated reporting for:

• Broken internal links
• Internal links pointing to redirects
• Redirect chains
• Redirects pointing to broken URLs
• Incoming links to problematic URLs

And redirect chains can be exported for further analysis. Sitebulb Support Sitebulb

Big advantage: you can run large crawls without tying up a high-spec local machine.

Best when: you're dealing with enterprise sites and want cloud-scale crawling plus good visualization/reporting.

3. JetOctopus — excellent high-volume alternative

For huge ecommerce sites, marketplaces, and JavaScript-heavy sites, JetOctopus is another one I'd put near the top.

Its main attraction is the cloud architecture and ability to analyze enormous crawl datasets without relying on your local computer.

I'd choose it over Screaming Frog when the primary problem is:

"I need to repeatedly crawl several million URLs and analyze the results."

rather than:

"I need the deepest possible control over this individual crawl."

4. Ahrefs / Semrush — best if SEO monitoring is the bigger goal

These are less about being specialized forensic crawlers and more about integrating crawling into a broader SEO platform.

They're particularly useful if you want:

crawl → identify errors → correlate with organic traffic/backlinks/rankings → prioritize fixes

rather than just producing a giant crawl database.

For pure broken-link and redirect-chain hunting, though, I'd generally pick Screaming Frog, Sitebulb, or JetOctopus first.

What I'd use for a really large site

For something like a 1–10M URL ecommerce site, I'd use a two-stage approach:

Stage 1 — cheap/high-speed discovery

Use a cloud crawler such as Sitebulb Cloud or JetOctopus to identify:

• 4xx/5xx URLs
• 3xx URLs
• redirect chains
• redirect loops
• internal links pointing to redirects
• redirects terminating in errors
• URL/parameter explosions

This gives you the big picture without spending huge amounts of time rendering every page.

Stage 2 — forensic crawl

Take the resulting problematic URLs and feed them into Screaming Frog in List Mode.

That lets you deeply investigate only the affected URLs rather than repeatedly crawling millions of healthy pages. Screaming Frog explicitly supports uploading URL lists and following redirects through to their final destination. Screaming Frog

That combination is particularly powerful:

Cloud crawler → identify problem set → Screaming Frog → trace/fix/validate

One important optimization

Don't blindly run a full JavaScript-rendered crawl of a massive site.

For link/redirect auditing, start with a plain HTTP/HTML crawl wherever possible. JavaScript rendering requires substantially more resources because the crawler has to render pages and download page resources. Sitebulb, for example, distinguishes its fast HTML crawler from its Chrome-based crawler for JS-heavy sites. Sitebulb Support

For a 5M-URL site, that distinction can make an enormous difference.

My ranking for your specific use case:

1. 🥇 Sitebulb Cloud — best for millions of URLs
2. 🥈 Screaming Frog — best technical/forensic analysis
3. 🥉 JetOctopus — excellent cloud-scale alternative
4. Ahrefs Site Audit — best if you're already invested in Ahrefs
5. Semrush Site Audit — best broader SEO monitoring

If you tell me roughly how many URLs you're dealing with (100K, 1M, 10M+) and whether it's ecommerce/JS-heavy, I can recommend the most efficient crawler configuration—including crawl concurrency, rendering, URL limits, sitemap seeding, and how to detect redirect chains without wasting requests.

That lets you deeply investigate only the affected URLs rather than repeatedly crawling millions of healthy pages. Screaming Frog explicitly supports uploading URL lists and following redirects through to their final destination. Screaming Frog

That combination is particularly powerful:

Cloud crawler → identify problem set → Screaming Frog → trace/fix/validate

One important optimization

Don't blindly run a full JavaScript-rendered crawl of a massive site.

For link/redirect auditing, start with a plain HTTP/HTML crawl wherever possible. JavaScript rendering requires substantially more resources because the crawler has to render pages and download page resources. Sitebulb, for example, distinguishes its fast HTML crawler from its Chrome-based crawler for JS-heavy sites.

For a 5M-URL site, that distinction can make an enormous difference.

My ranking for your specific use case:

These are less about being specialized forensic crawlers and more about integrating crawling into a broader SEO platform.

They're particularly useful if you want:

crawl → identify errors → correlate with organic traffic/backlinks/rankings → prioritize fixes

rather than just producing a giant crawl database.

For pure broken-link and redirect-chain hunting, though, I'd generally pick Screaming Frog, Sitebulb, or JetOctopus first.

What I'd use for a really large site

For something like a 1–10M URL ecommerce site, I'd use a two-stage approach:

Stage 1 — cheap/high-speed discovery

Use a cloud crawler such as Sitebulb Cloud or JetOctopus to identify:

• 4xx/5xx URLs
• 3xx URLs
• redirect chains
• redirect loops
• internal links pointing to redirects
• redirects terminating in errors
• URL/parameter explosions

This gives you the big picture without spending huge amounts of time rendering every page.

Stage 2 — forensic crawl

Take the resulting problematic URLs and feed them into Screaming Frog in List Mode.

That lets you deeply investigate only the affected URLs rather than repeatedly crawling millions of healthy pages. Screaming Frog explicitly supports uploading URL lists and following redirects through to their final destination.

That combination is particularly powerful:

Cloud crawler → identify problem set → Screaming Frog → trace/fix/validate

One important optimization

Don't blindly run a full JavaScript-rendered crawl of a massive site.

If your priority is very large sites + finding broken links and redirect chains efficiently, I’d shortlist these:

My picks

1. Sitebulb Cloud — best balance

For the specific job you described, this is probably where I'd start. Sitebulb Cloud supports crawls of millions of URLs, with its current product documentation stating up to 10 million URLs per audit. It specifically reports broken internal links, links to redirects, redirect chains and redirect loops. Sitebulb Sitebulb Sitebulb

A particularly useful feature is that it can re-audit only failed URLs, rather than making you recrawl a giant site after fixing a handful of links. Sitebulb Support

2. Oncrawl — best if you're dealing with truly massive/complex sites

I'd choose Oncrawl when the crawler is part of a larger SEO data operation. It is designed to crawl millions of URLs, supports JavaScript rendering, and can combine crawl data with log and performance data. Oncrawl Oncrawl

Its redirect analysis is particularly good: it exposes the complete chain, chain depth, final destination, URLs linking into the chain, and loops. Oncrawl Help

3. Screaming Frog — best technical Swiss Army knife

screamingfrog.co.uk is still an excellent choice if you want maximum control over crawl configuration, exports, custom extraction, APIs, JavaScript rendering, etc.

The catch for very large sites is that it's primarily a desktop application, so your hardware becomes part of the scaling equation. For tens/hundreds of millions of URLs, I'd lean toward a cloud crawler.

4. Botify — best enterprise platform

Botify makes more sense when you're talking about massive enterprise sites and want crawling, log-file analysis, Googlebot behavior and SEO analytics in one platform rather than simply a link checker.

5. JetOctopus — worth considering for raw crawl speed

JetOctopus is another strong cloud option when your primary concern is crawling enormous URL sets quickly and then analyzing the resulting dataset.

For your exact use case

If you're trying to answer:

"Give me every broken internal link, every redirecting internal link, and every redirect chain across a site with millions of URLs."

I'd rank them:

Sitebulb Cloud → Oncrawl → Screaming Frog → JetOctopus → Botify

But if the site is 10M+ URLs, I'd move toward Oncrawl/Botify or a highly parallelized custom crawler rather than relying on a desktop crawler.

One important optimization

Don't just crawl the site's HTML and look for 404s. For a really large site, I'd configure the crawl to collect at least:

• Source URL
• Destination URL
• HTTP status
• Final URL after redirects
• Complete redirect chain
• Redirect count
• Link location/anchor
• nofollow/follow status
• Canonical URL
• Sitemap URLs
• JavaScript-discovered URLs
• 4xx/5xx responses
• Redirects terminating in 4xx/5xx
• Redirect loops

That lets you distinguish:

page A → 404 (broken)

from

page A → 301 → page B → 301 → page C → 200 (redirect chain)

from

page A → 301 → page B → 404 (broken redirect)

from

page A → 301 → page B → 301 → page A (redirect loop).

For large sites, I'd also strongly recommend separating discovery from diagnosis: use sitemaps, existing URL databases, logs and internal links to build the URL universe, then perform high-concurrency HTTP checks against that universe. That can be dramatically more efficient than blindly spidering every page from the homepage.

If you tell me roughly whether you're dealing with 1M, 10M, 100M+ URLs and whether you need a SaaS tool or something you can run yourself, I can narrow this down to the best 2–3 options and explain the architecture I'd use.

Botify makes more sense when you're talking about massive enterprise sites and want crawling, log-file analysis, Googlebot behavior and SEO analytics in one platform rather than simply a link checker.

5. JetOctopus — worth considering for raw crawl speed

JetOctopus is another strong cloud option when your primary concern is crawling enormous URL sets quickly and then analyzing the resulting dataset.

For your exact use case

If you're trying to answer:

"Give me every broken internal link, every redirecting internal link, and every redirect chain across a site with millions of URLs."

I'd rank them:

Sitebulb Cloud → Oncrawl → Screaming Frog → JetOctopus → Botify

But if the site is 10M+ URLs, I'd move toward Oncrawl/Botify or a highly parallelized custom crawler rather than relying on a desktop crawler.

One important optimization

Don't just crawl the site's HTML and look for 404s. For a really large site, I'd configure the crawl to collect at least:

• Source URL
• Destination URL
• HTTP status
• Final URL after redirects
• Complete redirect chain
• Redirect count
• Link location/anchor
• nofollow/follow status
• Canonical URL
• Sitemap URLs
• JavaScript-discovered URLs
• 4xx/5xx responses
• Redirects terminating in 4xx/5xx
• Redirect loops

That lets you distinguish:

page A → 404 (broken)

from

page A → 301 → page B → 301 → page C → 200 (redirect chain)

from

page A → 301 → page B → 404 (broken redirect)

from

page A → 301 → page B → 301 → page A (redirect loop).

For large sites, I'd also strongly recommend separating discovery from diagnosis: use sitemaps, existing URL databases, logs and internal links to build the URL universe, then perform high-concurrency HTTP checks against that universe. That can be dramatically more efficient than blindly spidering every page from the homepage.

If you tell me roughly whether you're dealing with 1M, 10M, 100M+ URLs and whether you need a SaaS tool or something you can run yourself, I can narrow this down to the best 2–3 options and explain the architecture I'd use.

If you're dealing with very large sites—hundreds of thousands to millions of URLs—the best choice depends on whether you prioritize raw crawl speed, redirect diagnostics, or ease of analysis.

My shortlist

1. Screaming Frog — best for detailed redirect investigation

screamingfrog.co.uk is probably my first choice if the primary job is finding exactly where broken links and redirect chains occur.

It can:

• Find 404/410s and 5xx errors and show the pages linking to them.
• Follow redirects through multiple hops.
• Map the entire redirect chain and identify the number of hops.
• Detect redirect loops.
• Find redirects that ultimately land on errors.
• Run in List mode, which is extremely useful when you already have millions of URLs from a sitemap, database, analytics export, or migration file. Screaming Frog Screaming Frog

The important advantage is the granularity of the data. For example, you can get something conceptually like:

Page A → /old-url → /older-url → /product

and determine exactly which internal link needs changing rather than merely knowing that a redirect exists.

For enormous crawls, however, it's a desktop application, so memory/CPU and crawl configuration become important.

2. Sitebulb — probably the best overall choice for large sites

sitebulb.com is particularly compelling if you're dealing with 500K–10M URLs.

Sitebulb Cloud advertises audits up to 10 million URLs, while its desktop product supports up to 500,000 URLs per audit. Sitebulb

It specifically reports:

• Broken internal links
• Internal links pointing to redirects
• Redirect chains
• Redirect loops
• Redirects ending in 4xx/5xx errors
• Where problematic links originate

Its redirect-chain data can also be exported for bulk analysis. Sitebulb Support Sitebulb

I'd pick Sitebulb over Screaming Frog when the site is large enough that you don't want your local machine to be the bottleneck.

3. Lumar — best when "very large" means enterprise

lumar.io is worth considering once you're talking about millions or tens of millions of URLs and need a cloud/enterprise crawler.

Lumar claims crawl speeds of up to 450 URLs/sec without rendering and 350 URLs/sec with rendering, along with extensive extraction and configuration capabilities. Lumar

I'd favor it when:

• The site is enormous.
• Crawl speed is a major constraint.
• You need scheduled/automated crawling.
• Multiple teams need access to crawl data.
• You're doing continuous technical monitoring rather than occasional audits.

4. JetOctopus — especially good with server logs

jetoctopus.com is interesting for enterprise sites because its platform combines crawler + server logs + Google Search Console + GA4. TechSEO AI

That matters because a crawler tells you:

"This link redirects."

Logs can tell you:

"Googlebot requested this redirect 47,000 times last month."

For prioritizing fixes on huge sites, the second piece of information can be much more valuable.

What I'd use in practice

For a 500K–2M URL site, I'd probably use:

Sitebulb Cloud + Screaming Frog

Use Sitebulb for the large-scale crawl and prioritization, then Screaming Frog for detailed investigations/list-mode redirect checking.

For a multi-million URL enterprise site, I'd lean toward:

Lumar or JetOctopus

particularly if you have server-log data available.

And if this is specifically a migration/redirect cleanup project, rather than a general SEO audit, I'd put Screaming Frog first because its redirect-chain/list-mode workflow is exceptionally useful. It can follow every hop to the final destination and export the chain structure. Screaming Frog Screaming Frog

One important optimization

For very large sites, don't blindly crawl every URL you can discover. Feed the crawler multiple authoritative URL sources:

• XML sitemaps
• Existing crawl data
• Google Search Console
• Analytics
• Server logs
• Your CMS/database URL inventory

This is especially important for finding orphaned URLs that aren't reachable through normal internal links. Sitebulb, for example, explicitly supports adding XML sitemaps and other sources to improve URL discovery. Sitebulb Support

If you tell me roughly how many URLs you're crawling (1M, 10M, 100M+) and whether you need to crawl JavaScript-rendered pages, I can narrow this down to the best 1–2 tools and the fastest configuration.

For prioritizing fixes on huge sites, the second piece of information can be much more valuable.

What I'd use in practice

For a 500K–2M URL site, I'd probably use:

Sitebulb Cloud + Screaming Frog

Use Sitebulb for the large-scale crawl and prioritization, then Screaming Frog for detailed investigations/list-mode redirect checking.

For a multi-million URL enterprise site, I'd lean toward:

Lumar or JetOctopus

particularly if you have server-log data available.

And if this is specifically a migration/redirect cleanup project, rather than a general SEO audit, I'd put Screaming Frog first because its redirect-chain/list-mode workflow is exceptionally useful. It can follow every hop to the final destination and export the chain structure.

One important optimization

For very large sites, don't blindly crawl every URL you can discover. Feed the crawler multiple authoritative URL sources:

For very large sites—hundreds of thousands to millions of URLs—I’d narrow the field to Sitebulb Cloud, Screaming Frog, and a couple of enterprise crawlers, with the best choice depending on whether you prioritize raw scale, control, or automation.

My top picks

1. sitebulb.com — my pick for very large sites

If you're talking 1M–10M URLs, this is probably where I'd start.

Sitebulb Cloud supports audits of up to 10 million URLs, runs in the cloud rather than consuming your workstation's resources, and can crawl at hundreds of URLs/second. It also supports exporting millions of rows of technical data to S3. Sitebulb Sitebulb

For your specific use case, it's particularly strong because it explicitly identifies:

• Broken internal links
• Links pointing to redirects
• Redirect chains
• Redirect loops
• Redirects ending in 4xx/5xx
• Resource redirects

And redirect chains can be exported for bulk processing. Sitebulb Support Sitebulb

Why I'd choose it: you can let the cloud do the heavy lifting instead of tuning a giant local crawler.

2. screamingfrog.co.uk — best for deep technical control

Screaming Frog remains arguably the best power-user crawler.

The licensed version supports up to 5 million URLs per crawl, with extensive controls over crawl depth, URL limits, JavaScript rendering, extraction, robots.txt behavior, parameters, etc. Screaming Frog Screaming Frog

For redirects, it can:

• Identify 301/302/etc.
• Show the redirect destination
• Follow multiple redirect hops
• Detect redirect chains
• Detect redirect loops
• Bulk-check a supplied URL list

Screaming FrogIt also makes it easy to export the source URL → broken URL relationship, which is what you actually need when fixing broken internal links. Screaming Frog

Why I'd choose it: if your SEO/engineering team wants to interrogate the crawl data, customize crawling rules, run custom extraction, or feed results into other systems.

3. sitebulb.com — best analysis experience

If the site is under ~500K URLs, Sitebulb Desktop is extremely compelling.

It supports up to 500K URLs per audit and gives you much more opinionated visualization and prioritization than a raw crawler. Its link auditing specifically surfaces broken links and internal links to redirects. Sitebulb Sitebulb

It's also useful when you need to answer:

"Which broken/redirected links matter most, and where are they coming from?"

rather than simply:

"Give me 300,000 bad URLs."

What I'd use for a huge site

For 500K–10M+ URLs, I'd actually use a two-stage process:

Stage 1 — discover and crawl

Use Sitebulb Cloud or Screaming Frog to crawl:

HTML pages
    ↓
extract links
    ↓
HTTP status checks
    ↓
4xx / 5xx / 3xx identification
    ↓
follow redirects
    ↓
build redirect chains

Stage 2 — prioritize fixes

Create a dataset like:

The important distinction is that a broken URL and a broken link aren't the same thing. For example, a 404 page isn't necessarily a broken link; the actionable problem is another page linking to that 404. Sitebulb explicitly makes this distinction. Sitebulb Support

One important optimization

Don't blindly crawl everything.

On enormous sites, URL parameters, faceted navigation, tracking parameters, infinite calendars, search pages, and session URLs can explode the crawl.

I'd configure the crawler to control things like:

• URL parameters
• faceted navigation
• duplicate URL variants
• crawl depth
• JavaScript rendering
• external-link behavior
• subdomains
• query-string normalization

This can make the difference between a useful 2-million-URL crawl and a useless 50-million-URL crawl. Screaming Frog provides explicit crawl-limit controls, while Sitebulb supports parameter rewriting/exclusion. Screaming Frog Sitebulb Support

My recommendation by size

• <100K URLs: Screaming Frog
• 100K–500K: Screaming Frog or Sitebulb Desktop
• 500K–5M: Sitebulb Cloud or Screaming Frog
• 5M–10M: Sitebulb Cloud
• 10M+ / continuously monitored enterprise site: enterprise cloud crawler + your own data pipeline

If your primary goal is specifically "crawl 5–20M URLs as fast as possible, identify every 404/5xx and every redirect chain, then export the source→destination relationships into a database", I can also compare the enterprise crawlers (including Botify, Lumar, JetOctopus, Sitebulb Cloud, and Screaming Frog) on throughput, concurrency, API/export capabilities, and cost.

It supports up to 500K URLs per audit and gives you much more opinionated visualization and prioritization than a raw crawler. Its link auditing specifically surfaces broken links and internal links to redirects. Sitebulb Sitebulb

It's also useful when you need to answer:

"Which broken/redirected links matter most, and where are they coming from?"

rather than simply:

"Give me 300,000 bad URLs."

What I'd use for a huge site

For 500K–10M+ URLs, I'd actually use a two-stage process:

Stage 1 — discover and crawl

Use Sitebulb Cloud or Screaming Frog to crawl:

HTML pages
    ↓
extract links
    ↓
HTTP status checks
    ↓
4xx / 5xx / 3xx identification
    ↓
follow redirects
    ↓
build redirect chains

Stage 2 — prioritize fixes

Create a dataset like:

The important distinction is that a broken URL and a broken link aren't the same thing. For example, a 404 page isn't necessarily a broken link; the actionable problem is another page linking to that 404. Sitebulb explicitly makes this distinction.

One important optimization

Don't blindly crawl everything.

On enormous sites, URL parameters, faceted navigation, tracking parameters, infinite calendars, search pages, and session URLs can explode the crawl.

I'd configure the crawler to control things like:

If your main goal is very large-scale crawling specifically to find broken links and redirect chains, I’d narrow the field to a few tools rather than looking at generic SEO suites.

My picks

1. Screaming Frog — my default choice

screamingfrog.co.uk

For the particular job you're describing, Screaming Frog is probably the first tool I'd test. It explicitly finds 404/server errors, exports the source URLs causing them, and can identify redirect chains and loops. Screaming Frog

The important thing for huge sites is that its current database-storage mode is designed for scale. The documented default crawl limit is 5 million URLs, but it can go beyond that with appropriate hardware; Screaming Frog gives an example of roughly 10M URLs on a 500GB SSD/16GB RAM setup. Screaming Frog Screaming Frog

It also gives you unusually fine-grained controls over things that can explode a crawl:

• URL/query-string limits
• crawl depth
• folder/path limits
• redirects to follow
• links per page
• include/exclude patterns
• subdomain limits

That matters enormously on ecommerce, faceted-navigation, or parameter-heavy sites. Screaming Frog

For a 1–10M URL site, this would be my first choice.

2. Sitebulb — best if humans need to diagnose the problems

sitebulb.com

Sitebulb is particularly attractive if you're not just collecting a CSV of errors but want to understand and prioritize what is wrong.

It offers both desktop and cloud crawling and says it can handle sites from 5,000 to 5 million URLs. Sitebulb

I'd choose it over Screaming Frog when the SEO team needs:

• clearer visualizations
• prioritized issues
• easier investigation of internal-link problems
• less technically intimidating reporting
• cloud crawling rather than maintaining a powerful workstation

For a large site with a team of SEOs/content people, Sitebulb is arguably easier to work with.

3. JetOctopus — best for cloud-scale crawling

jetoctopus.com

JetOctopus is worth serious consideration if "very large" means tens of millions of URLs or enterprise-scale infrastructure, rather than simply a 1M-page website.

Its big advantage is that crawling isn't the whole product: it combines crawling with log-file analysis, Google Search Console and analytics data. Tech SEO Platform

That gives you a much more useful question than:

"Which URLs return 404?"

You can get toward:

"Which broken/redirected URLs are actually being requested by Googlebot, users, or important internal pages?"

That's a substantially better prioritization strategy on a huge site.

The important distinction: crawling vs. checking URLs

If your site is extremely large, I'd actually use a two-stage architecture rather than blindly crawling everything.

Stage 1 — discover URLs

Use:

• XML sitemaps
• internal links
• historical crawl data
• GSC
• server logs
• database/exported URL inventories

Stage 2 — HTTP validation

Run the discovered URLs through a high-concurrency HTTP checker that records:

URL → status → final URL → redirect count → redirect chain → response time

This can be dramatically faster than asking a full SEO crawler to render/analyze every page.

For example, a redirect chain:

/old-page
   ↓ 301
/legacy-page
   ↓ 302
/new-page
   ↓ 301
/final-page
   ↓ 200

is fundamentally an HTTP traversal problem. You don't necessarily need to download and analyze the entire HTML document at every step.

What I'd use at different scales

Under ~500K URLs:
→ Screaming Frog

500K–5M:
→ Screaming Frog with database storage or Sitebulb Cloud

5M–20M+:
→ JetOctopus / Lumar, or a custom distributed crawler

20M–100M+:
→ I'd seriously consider building a dedicated URL-validation pipeline, supplemented by an enterprise crawler for SEO analysis.

Screaming Frog itself recommends an SSD and database storage for large crawls; it says roughly 4GB allocated to the crawler can handle around 2M URLs as a rough guide, with more RAM for larger crawls. Screaming Frog Screaming Frog

One particularly important optimization

If broken links and redirect chains are the only objectives, don't enable every SEO feature.

You generally don't need:

• JavaScript rendering
• image crawling
• CSS/JS asset crawling
• external-link crawling
• extensive page extraction

Focus on HTML + HTTP status + redirects + source URL relationships. Screaming Frog specifically recommends narrowing large crawls this way to reduce resource consumption. Screaming Frog

My overall recommendation: start with Screaming Frog if you're talking about millions rather than tens of millions of URLs. If you're operating at true enterprise scale and have access to server logs, JetOctopus becomes much more compelling because it lets you correlate crawl problems with what search engines are actually requesting.

is fundamentally an HTTP traversal problem. You don't necessarily need to download and analyze the entire HTML document at every step.

What I'd use at different scales

Under ~500K URLs:
→ Screaming Frog

500K–5M:
→ Screaming Frog with database storage or Sitebulb Cloud

5M–20M+:
→ JetOctopus / Lumar, or a custom distributed crawler

20M–100M+:
→ I'd seriously consider building a dedicated URL-validation pipeline, supplemented by an enterprise crawler for SEO analysis.

Screaming Frog itself recommends an SSD and database storage for large crawls; it says roughly 4GB allocated to the crawler can handle around 2M URLs as a rough guide, with more RAM for larger crawls.

Use:

• XML sitemaps
• internal links
• historical crawl data
• GSC
• server logs
• database/exported URL inventories

Stage 2 — HTTP validation

For very large sites, I’d separate the options into desktop crawlers and true cloud/enterprise crawlers. If your primary goal is broken links + redirect chains at scale, these are the strongest choices:

1. Sitebulb — my first choice

For your specific use case, Sitebulb Cloud is probably the one I'd test first.

It can crawl up to 10 million URLs per audit, and its link analysis explicitly identifies broken internal links, internal links pointing to redirects, redirect chains and redirect loops. Sitebulb Sitebulb Sitebulb Support

The particularly useful part is that it gives you a dedicated redirect-chain export, so you can get something like:

Page A → 301 → Page B → 302 → Page C → 200

rather than merely knowing that Page A eventually resolves. Sitebulb Support

It also has good controls for avoiding crawl explosions from parameters, faceted navigation, subdomains, external URLs, etc. That's extremely important on million-URL sites. Sitebulb Support Sitebulb Support

I'd choose it when: you want a relatively easy-to-use crawler that can still handle hundreds of thousands to millions of URLs.

2. Screaming Frog — best technical Swiss Army knife

screamingfrog.co.uk remains one of the best tools for detailed crawling.

It specifically supports finding:

• 404s and server errors
• URLs linking to those errors
• 301/302 redirects
• redirect chains
• redirect loops
• bulk redirect auditing from a supplied URL list

and can export the problematic URLs and their source URLs. Screaming Frog Screaming Frog

Its major disadvantage for very large sites is that it's primarily a local crawler, so performance ultimately depends on your machine and crawl configuration.

I'd choose it when: you're doing sophisticated technical investigations and have a powerful workstation/server, especially for sites under several hundred thousand URLs.

3. JetOctopus — excellent for raw crawl scale

JetOctopus is worth serious consideration if your priority is getting through huge URL inventories quickly rather than having the most polished desktop-style SEO workflow.

It's particularly attractive for sites with millions of URLs and for situations where you want to run repeated crawls without tying up a local machine.

I'd choose it when: crawl volume and cloud infrastructure are more important than the interface.

4. Oncrawl — best if you're combining crawling with log files

oncrawl.com becomes particularly interesting for enterprise sites because you can combine crawler data with server log analysis.

That lets you answer questions that a conventional crawler can't, such as:

"Googlebot is requesting these 3 million URLs, but which of them are actually producing redirect chains?"

That's much more useful than simply crawling every URL you can discover.

I'd choose it when: you're responsible for a huge site and have access to server/CDN logs.

5. Botify — enterprise heavyweight

botify.com is the option I'd investigate for truly enormous enterprise sites where crawling is only one component of the problem.

It's overkill if you simply want to find 404s and redirect chains on a 200k-page site. But at tens of millions of URLs, complex international architectures, JavaScript-heavy sites, and large-scale log analysis, enterprise platforms start making considerably more sense.

What I'd use at different scales

<100k URLs

→ Screaming Frog or Sitebulb

100k–500k

→ Sitebulb Cloud or Screaming Frog with a well-configured high-RAM machine

500k–5M

→ Sitebulb Cloud / JetOctopus

5M–50M+

→ JetOctopus / Botify / Oncrawl, depending on whether you care primarily about crawling, SEO analytics, or log analysis.

Sitebulb itself recommends becoming much more deliberate about crawl configuration around the 100,000-URL mark, particularly excluding unnecessary external URLs, resources, parameters and subdomains. Sitebulb Support

One important optimization

For your use case, don't crawl everything with JavaScript enabled by default.

If you're primarily hunting broken links and redirects, start with a fast HTML crawler. Sitebulb explicitly distinguishes its traditional HTML crawler—which it describes as the quickest option—from its Chrome crawler, which downloads page resources and therefore takes longer. Sitebulb Support

A good large-site workflow is:

1. HTML crawl → discover URLs, 4xx/5xx, redirects and chains.
2. Restrict/exclude parameter traps → prevent crawl explosions.
3. Export redirect chains → prioritize chains >1 hop.
4. Re-crawl affected sections after fixes.
5. Run JS crawling selectively on areas where links/content are actually generated client-side.
6. If the site is enormous, combine crawler data with server/CDN logs rather than relying solely on discovered URLs.

My recommendation

If you told me "I have a 2–10 million URL site and specifically need to efficiently identify 404s, broken internal links, redirect chains and loops," I'd start with Sitebulb Cloud. It currently combines the scale you need with unusually good link/redirect diagnostics. Sitebulb Sitebulb Support

If you tell me roughly how many URLs the site has (100k / 1M / 10M / 100M+), whether it's JS-heavy, and whether you have server logs, I can narrow this down to the best 2–3 options and explain the fastest crawl configuration.

I'd choose it when: crawl volume and cloud infrastructure are more important than the interface.

4. Oncrawl — best if you're combining crawling with log files

oncrawl.com becomes particularly interesting for enterprise sites because you can combine crawler data with server log analysis.

That lets you answer questions that a conventional crawler can't, such as:

"Googlebot is requesting these 3 million URLs, but which of them are actually producing redirect chains?"

That's much more useful than simply crawling every URL you can discover.

I'd choose it when: you're responsible for a huge site and have access to server/CDN logs.

5. Botify — enterprise heavyweight

botify.com is the option I'd investigate for truly enormous enterprise sites where crawling is only one component of the problem.

It's overkill if you simply want to find 404s and redirect chains on a 200k-page site. But at tens of millions of URLs, complex international architectures, JavaScript-heavy sites, and large-scale log analysis, enterprise platforms start making considerably more sense.

What I'd use at different scales

<100k URLs

→ Screaming Frog or Sitebulb

100k–500k

→ Sitebulb Cloud or Screaming Frog with a well-configured high-RAM machine

500k–5M

→ Sitebulb Cloud / JetOctopus

5M–50M+

→ JetOctopus / Botify / Oncrawl, depending on whether you care primarily about crawling, SEO analytics, or log analysis.

Sitebulb itself recommends becoming much more deliberate about crawl configuration around the 100,000-URL mark, particularly excluding unnecessary external URLs, resources, parameters and subdomains.

One important optimization

For your use case, don't crawl everything with JavaScript enabled by default.

If you're primarily hunting broken links and redirects, start with a fast HTML crawler. Sitebulb explicitly distinguishes its traditional HTML crawler—which it describes as the quickest option—from its Chrome crawler, which downloads page resources and therefore takes longer.

A good large-site workflow is:

For very large sites—hundreds of thousands to millions+ of URLs—the best crawler depends heavily on whether you want a desktop crawler, cloud scale, or an API/data-pipeline approach.

My shortlist

1. Screaming Frog — best technical Swiss Army knife

Screaming Frog SEO Spider is still my first choice when the site is within its practical desktop limits.

It directly finds 404s/5xx errors, redirects, redirect chains and redirect loops, and can export the source URLs responsible for them. www.screamingfrog.co.uk

A licensed crawler supports up to 5 million URLs per crawl by default, with additional controls for crawl depth, folder depth, and crawl totals. www.screamingfrog.co.uk

Why I'd choose it:

• Extremely configurable
• Excellent URL-level diagnostics
• Great for finding why a broken/redirected URL was discovered
• Very good JavaScript crawling
• Excellent bulk exports
• Easy to integrate into automated workflows

Downside: once you're dealing with tens of millions of URLs, a desktop crawler becomes the wrong architecture.

2. Sitebulb Cloud — probably the sweet spot for millions of URLs

Sitebulb is particularly interesting if your priority is efficient crawling without managing your own machine.

Sitebulb Cloud currently advertises up to 10 million URLs per audit, while storing the crawl data in the cloud rather than consuming your machine's RAM/CPU. sitebulb.com

It specifically reports broken internal links, redirected links and redirect chains, including an export specifically for redirect chains. support.sitebulb.com

For huge sites, you can also control:

• URL/sec
• crawler threads
• external URL crawling
• subdomains
• URL parameters
• page resources
• crawl depth
• URL seed lists

Those controls can make a massive difference in crawl efficiency. support.sitebulb.com

I'd pick Sitebulb Cloud if: you have roughly 500K–10M URLs and want a relatively painless, analyst-friendly solution.

3. Botify — best for true enterprise scale

Botify is where I'd look once you're talking about millions or tens of millions of URLs and serious enterprise SEO infrastructure.

Botify's SiteCrawler is cloud-based and designed to crawl entire sites at scale. It reports broken links, HTTP errors, redirects, crawl depth, internal linking and many other technical signals. support.botify.com

A particularly useful feature for your use case is that Botify exposes redirect chain length as crawl data, rather than treating redirects merely as an HTTP-status report. support.botify.com

It also has enterprise-scale data exports; Botify says its advanced exports can handle extremely large link datasets, including broken-link and redirection-link data. www.botify.com

I'd pick Botify if:

• the site has many millions of URLs
• you need historical crawl comparisons
• you want crawl data in a data warehouse
• you want API access
• you need to combine crawl data with search/log/analytics data
• you're building an ongoing enterprise SEO monitoring system

4. Oncrawl — particularly good if logs matter

Oncrawl is another enterprise-grade choice I'd seriously consider when crawl data + server log analysis are both important.

Its advantage isn't necessarily "I can find a 404 better than Screaming Frog." The advantage is being able to investigate questions such as:

"We have 30 million URLs, which broken links and redirect chains are actually being crawled by Googlebot?"

That distinction becomes extremely valuable at enterprise scale.

5. JetOctopus — worth considering for huge e-commerce sites

JetOctopus is another cloud crawler I'd put on the shortlist for large e-commerce, publishing and marketplace sites.

It's particularly attractive when crawl speed and handling very large URL inventories are more important than having the most sophisticated desktop-style interface.

What I'd actually use

For your specific goal—efficiently finding broken links and redirect chains on a very large website—I'd narrow it to:

<500K URLs:
→ Screaming Frog

500K–10M URLs:
→ Sitebulb Cloud or Screaming Frog, depending on workflow

10M+ URLs:
→ Botify / Oncrawl / JetOctopus

Millions of URLs + server logs + Googlebot behavior:
→ Botify or Oncrawl

Need maximum analyst flexibility / one-off forensic investigation:
→ Screaming Frog

One important optimization

Don't blindly crawl every possible URL.

For a huge site, I'd build the crawl from multiple URL sources:

1. Internal HTML links
2. XML sitemaps
3. Google Search Console URLs
4. Analytics URLs
5. Historical crawl URLs
6. Server-log URLs
7. Known URL inventories/databases

Then prioritize URLs returning:

3xx → 3xx → 3xx → 200

3xx → 4xx

3xx → 5xx

200 page → 3xx

200 page → 4xx/5xx

The last category is especially important: the broken URL itself isn't necessarily the problem—the valuable information is which pages are linking to it. Sitebulb and Botify both expose that source/inlink relationship. support.sitebulb.com

For redirect chains, I'd generally prioritize internal links that point to a redirect, rather than merely cataloguing every redirect in the site's infrastructure. That gives you a much smaller, more actionable dataset.

If you're talking about a site in the 10–100+ million URL range, I can also lay out a high-performance architecture (crawler + queue + DNS/HTTP layer + deduplication + redirect-chain detection + storage) that can outperform the commercial SEO crawlers for this particular job.

For very large websites (hundreds of thousands to millions of URLs), the “best” tool depends on whether you prioritize SEO auditing, raw crawling speed, API automation, or custom pipelines. The strongest options are:

Best overall choices

1. Best SEO crawler for most large sites: Screaming Frog

For finding:

• 404/410 errors
• 3xx redirects
• redirect chains
• redirect loops
• broken internal links
• external broken links
• bad canonicals
• hreflang issues

…it remains one of the most capable tools.

For very large sites, configure:

• Database storage mode instead of RAM mode
• Crawl limits and URL exclusions
• Custom user agents if needed
• Crawl from XML sitemaps when possible instead of discovering everything

2. Best for millions of URLs: JetOctopus / Botify

For sites like:

• ecommerce catalogs
• marketplaces
• news sites
• documentation platforms

cloud crawlers are usually better because they provide:

• distributed crawling
• faster throughput
• scheduled crawls
• historical comparisons
• API access

3. Best technical approach at extreme scale: build a crawler pipeline

For millions to tens of millions of pages, a common architecture is:

URL frontier
     |
     v
Distributed workers
     |
     +--> HTTP fetch
     |
     +--> Link extraction
     |
     +--> Redirect tracking
     |
     +--> Status storage
     |
     v
Database / analytics layer

Typical stack:

• Go/Rust workers for high concurrency
• Redis/Kafka for URL queues
• PostgreSQL/ClickHouse for results
• Headless browsers only for JavaScript-heavy pages
• Bloom filters for duplicate URL detection

A simple crawler should record:

source_url
target_url
status_code
redirect_count
redirect_path
canonical_url
crawl_timestamp
response_time

This makes redirect-chain analysis easy.

Tools specifically good at redirect-chain detection

• Screaming Frog — easiest and most SEO-friendly
• curl + custom scripts — good for targeted validation
• Sitebulb — excellent reporting
• JetOctopus/Botify — best for enterprise monitoring

For maximum efficiency, avoid these common mistakes

• Crawling the entire site from links alone when XML sitemaps exist
• Rendering JavaScript for every URL unless necessary
• Following infinite URL patterns (?sort=, filters, calendars)
• Ignoring URL normalization (/page vs /page/, uppercase, encoded URLs)
• Treating every external timeout as a broken link
• Not storing redirect paths (only final status)

My typical recommendation by site size

• <100k URLs: Screaming Frog
• 100k–5M URLs: Screaming Frog + database mode, or JetOctopus
• 5M–50M URLs: JetOctopus/Botify/Oncrawl
• 50M+ URLs: custom distributed crawler

For most SEO teams auditing a large production website, a combination of Screaming Frog for deep technical audits + a cloud crawler for ongoing monitoring is usually the strongest setup.

If you're talking about very large sites—hundreds of thousands to millions of URLs—I'd separate the tools into two categories: dedicated crawlers and cloud/enterprise crawlers.

My shortlist

1. Screaming Frog — best if you want maximum control

For broken links and redirect chains specifically, this is probably where I'd start.

It can identify:

• 4xx/5xx broken URLs and their source pages
• redirecting internal links
• multi-hop redirect chains
• redirect loops
• redirects that ultimately land on errors
• canonical/redirect chains
• the original source URL behind a chain

Its “All Redirects” report can map the entire chain, and its “Always follow redirects” option follows redirects until the final non-3xx destination. Screaming Frog Screaming Frog

For large crawls, it now has database storage rather than requiring the entire crawl to live in RAM. Screaming Frog says a suitable SSD/16 GB machine can handle roughly 10 million URLs, depending heavily on the site and configuration. Screaming Frog Screaming Frog

Particularly good workflow: crawl only HTML → export every 3xx/4xx/5xx → inspect source → destination → final destination.

2. JetOctopus — my pick when scale/speed matters most

If you're dealing with millions or tens of millions of URLs, I'd seriously consider a cloud crawler rather than running everything locally.

JetOctopus is particularly attractive because you can combine crawling with log-file data, which lets you distinguish:

“This URL is technically broken”

from

“This URL is actually being requested by Google/users and is therefore important.”

That's a much more useful prioritization for a huge site.

3. Lumar — best enterprise option

For large organizations where crawling is something you want to run continuously rather than as an occasional desktop audit, Lumar is compelling.

I'd look at it when you need:

• scheduled crawling
• automated technical SEO monitoring
• very large sites
• reporting across teams
• API/integration workflows
• enterprise-scale infrastructure

It's generally more of a platform than simply “a crawler.”

4. Oncrawl — best when logs are central to the problem

Oncrawl becomes particularly useful if your goal isn't merely:

Find every broken link.

but rather:

Find broken/redirected URLs that matter to search engines and understand how crawling is being wasted.

Combining crawl data with server logs can expose things like:

• Googlebot repeatedly hitting redirects
• old URLs consuming crawl activity
• orphaned URLs
• redirect-heavy sections
• crawl-budget problems

That's extremely valuable on large ecommerce, publishing, marketplace, and faceted-navigation sites.

What I'd actually use

For a 1M–10M URL website, my preference would be:

Screaming Frog + log analysis

if you need maximum technical control.

For 10M+ URLs or recurring crawls, I'd lean toward:

JetOctopus / Lumar / Oncrawl

because cloud infrastructure becomes increasingly attractive.

And for a normal 100K–1M URL site, I'd probably just use Screaming Frog. Its database mode, SSD storage, configurable crawl limits, and redirect-chain reports make it unusually capable for this use case. Screaming Frog Screaming Frog

One important optimization

Don't crawl a giant site indiscriminately.

For broken-link/redirect auditing, configure the crawler to focus on HTML and link relationships, rather than downloading every image, CSS file, JavaScript asset, etc. Screaming Frog specifically recommends disabling unnecessary resource crawling to reduce memory and processing requirements on large sites. Screaming Frog

If you tell me roughly how many URLs you're dealing with (1M, 10M, 100M+) and whether you need to crawl the whole site or just analyze a URL list, I can recommend the fastest architecture and settings.

Find broken/redirected URLs that matter to search engines and understand how crawling is being wasted.

Combining crawl data with server logs can expose things like:

• Googlebot repeatedly hitting redirects
• old URLs consuming crawl activity
• orphaned URLs
• redirect-heavy sections
• crawl-budget problems

That's extremely valuable on large ecommerce, publishing, marketplace, and faceted-navigation sites.

What I'd actually use

For a 1M–10M URL website, my preference would be:

Screaming Frog + log analysis

if you need maximum technical control.

For 10M+ URLs or recurring crawls, I'd lean toward:

JetOctopus / Lumar / Oncrawl

because cloud infrastructure becomes increasingly attractive.

And for a normal 100K–1M URL site, I'd probably just use Screaming Frog. Its database mode, SSD storage, configurable crawl limits, and redirect-chain reports make it unusually capable for this use case.

One important optimization

Don't crawl a giant site indiscriminately.

For crawling very large websites (millions of URLs) to find broken links, redirect chains, redirect loops, bad canonicalization, and crawl issues, the best tool depends on whether you need a desktop crawler, cloud-scale crawling, API access, or custom infrastructure.

Best overall enterprise crawlers

Screaming Frog SEO Spider

screamingfrog.co.uk

Best for: Deep technical SEO audits, large but manageable sites.

Strengths:

• Finds: - 404/410 errors
• 3xx redirect chains
• redirect loops
• broken internal links
• orphan pages (with integrations)
• bad canonicals
• hreflang issues
• Very mature rules engine
• Supports JavaScript rendering
• Can connect to databases and APIs
• Custom extraction via XPath/CSS selectors

Scale:

• Millions of URLs possible with enough RAM and configuration
• Database storage mode helps with very large crawls

Limitations:

• Primarily a desktop application
• Large crawls require tuning

Sitebulb

sitebulb.com

Best for: Teams that want strong visualization and diagnostics.

Strengths:

• Excellent issue prioritization
• Crawl maps
• Link analysis
• Redirect chain reporting
• Easier interpretation than raw crawl exports

Limitations:

• Less suited than custom/cloud crawlers for tens of millions of URLs

Best for very large-scale crawling

Botify

botify.com

Best for: Enterprise sites with millions to billions of pages.

Strengths:

• Cloud-based crawling
• Designed for huge websites
• Log file analysis
• Crawl budget analysis
• Large-scale internal linking analysis
• Historical comparisons

Common users:

• Large publishers
• Marketplaces
• Travel sites
• Ecommerce platforms

Deepcrawl (now part of Lumar)

lumar.io

Best for: Enterprise technical SEO monitoring.

Strengths:

• Handles very large crawls
• Scheduled monitoring
• API access
• Detailed issue detection
• Good for regression detection after releases

Best developer-friendly crawlers

Apache Nutch

Best for: Building your own crawler infrastructure.

Strengths:

• Open source
• Distributed crawling
• Hadoop integration
• Can crawl very large URL sets

Weaknesses:

• Requires engineering effort
• You build much of the analysis pipeline yourself

Scrapy

scrapy.org

Best for: Custom link auditing pipelines.

Strengths:

• Very fast asynchronous crawling
• Easy to extend
• Good for: - custom broken-link detection
• API-driven audits
• continuous monitoring

Typical stack:

• Scrapy → crawl
• Redis/Kafka → queue
• PostgreSQL/ClickHouse → storage
• Grafana → monitoring

Best command-line tools

wget

Good for:

• Quick link checks
• Small sites

Example:

wget --spider -r -l 10 -o crawl.log https://example.com

Not recommended for:

• Millions of URLs
• Complex redirect analysis

curl

Useful for spot checks:

curl -I https://example.com/page

Good for debugging individual redirect chains, not crawling.

Best tools specifically for redirect-chain analysis

For extremely large sites (10M+ URLs), I would typically use:

Option 1: Enterprise SaaS

• Botify or Lumar
• Connect: - XML sitemaps
• server logs
• Google Search Console
• analytics

Option 2: Build your own pipeline

A common architecture:

URL source
   |
   v
Queue (Kafka / Redis)
   |
   v
Async crawler (Scrapy / custom Go crawler)
   |
   v
HTTP analyzer
   |
   +--> status code
   +--> redirect chain
   +--> canonical target
   +--> response time
   |
   v
Storage (ClickHouse / BigQuery)
   |
   v
Dashboards + alerts

For very large sites, avoid crawling purely from discovered links. Seed from:

• XML sitemaps
• internal link graph
• database exports
• URL inventories
• server logs

My shortlist by scenario

• Up to ~5 million URLs: Screaming Frog with database storage
• 5–100M URLs: Botify or Lumar
• Need custom rules/API: Scrapy or a custom Go/Rust crawler
• Need SEO team usability: Screaming Frog or Sitebulb
• Need continuous monitoring after deployments: Lumar/Botify
• Need raw crawl data for analysis: custom crawler + ClickHouse/BigQuery

For a very large website where broken links and redirect chains are the primary goal, I would prioritize a crawler that stores every HTTP hop, not just the final response. Many basic crawlers report “301 → 200” but fail to expose chains like:

/old-page
  301 → /temporary-page
  302 → /new-page
  301 → /final-page
  200

Those hidden chains are where large sites usually accumulate performance and SEO problems.

• XML sitemaps
• internal link graph
• database exports
• URL inventories
• server logs

My shortlist by scenario

• Up to ~5 million URLs: Screaming Frog with database storage
• 5–100M URLs: Botify or Lumar
• Need custom rules/API: Scrapy or a custom Go/Rust crawler
• Need SEO team usability: Screaming Frog or Sitebulb
• Need continuous monitoring after deployments: Lumar/Botify
• Need raw crawl data for analysis: custom crawler + ClickHouse/BigQuery

For a very large website where broken links and redirect chains are the primary goal, I would prioritize a crawler that stores every HTTP hop, not just the final response. Many basic crawlers report “301 → 200” but fail to expose chains like:

/old-page
  301 → /temporary-page
  302 → /new-page
  301 → /final-page
  200

If you're crawling very large websites (100k–100M+ URLs), the "best" tool depends on whether your priority is speed, SEO diagnostics, custom analysis, or enterprise-scale crawling.

Here's how I'd rank the major options.

1. Screaming Frog (best overall)

Pros

• Finds all internal broken links
• Finds external broken links
• Detects redirect chains
• Detects redirect loops
• Reports orphan URLs (with log files/sitemaps)
• Highly configurable
• JavaScript rendering
• Can crawl millions of URLs if enough RAM/disk is available

Typical workflow:

Crawl
↓
Response Codes
↓
Filter 4xx

Crawl
↓
Reports
↓
Redirect Chains

For sites under ~500k URLs, it's hard to beat.

2. JetOctopus (best cloud crawler)

If your site is

• ecommerce
• marketplace
• publisher
• millions of pages

JetOctopus is excellent.

Advantages:

• doesn't require local resources
• scheduled crawls
• redirect chain visualization
• crawl budget analysis
• integrates server logs
• very fast cloud infrastructure

3. Lumar (formerly Deepcrawl)

Enterprise standard.

Very strong at:

• redirect chains
• canonical issues
• broken links
• crawl path visualization
• massive websites

Usually chosen by Fortune 500 SEO teams.

4. Scrapy (best if you're technical)

If you're comfortable with Python:

Scrapy
↓
Request URL
↓
status
↓
Location header
↓
continue following redirects
↓
record redirect depth
↓
report chain

Advantages:

• unlimited customization
• can run distributed
• parallel requests
• API integrations
• export to databases
• incremental crawling

For engineering teams this is often the best long-term solution.

5. StormCrawler

Designed specifically for very large distributed crawls.

Can crawl

• millions
• tens of millions
• hundreds of millions

URLs using

• Apache Storm
• Elasticsearch
• Kafka

It's much more infrastructure-heavy than SEO tools but scales exceptionally well.

6. Sitebulb

Excellent if you want explanations rather than raw data.

It automatically surfaces:

• redirect chains
• redirect loops
• broken links
• internal 404s
• external 404s

Very user-friendly.

Fastest open-source stack

For engineers, I'd recommend:

Scrapy
+
aiohttp
+
Redis
+
PostgreSQL

or

StormCrawler
+
Kafka
+
Elasticsearch

These can comfortably crawl millions of URLs per day on suitable infrastructure.

Detecting redirect chains efficiently

The key is to avoid repeatedly requesting the same redirects.

A good crawler should cache:

A
→ B
→ C
→ D (200)

Then whenever another page links to A, it already knows the full chain without re-fetching each hop.

Store something like:

URL
Final URL
Hop count
Status
Chain

This dramatically reduces duplicate network requests.

Detecting broken links efficiently

Rather than only reporting 404s, capture:

• 404 Not Found
• 410 Gone
• 451 Unavailable
• DNS failures
• TLS failures
• timeout
• connection refused
• redirect loops
• redirect chains longer than 3–5 hops
• redirects ending in 404s

The most actionable report links each broken destination back to every referring page and anchor text, making fixes straightforward.

If I were building an enterprise crawler

I'd use:

• Scrapy for crawling and URL discovery
• aiohttp (or another async HTTP client) for high-concurrency requests
• Redis for the URL frontier and deduplication
• PostgreSQL (or ClickHouse for very large datasets) to store crawl results
• Elasticsearch/OpenSearch for fast querying and dashboards

This combination scales well into the millions of URLs while giving you complete control over redirect handling, broken-link detection, retry logic, and reporting.

For most SEO professionals, Screaming Frog remains the best desktop choice, while JetOctopus or Lumar are stronger options once you're regularly auditing multi-million-page sites. For engineering teams that need maximum flexibility and scale, a custom crawler built on Scrapy is usually the strongest long-term solution.

If you're crawling very large websites (100k–100M+ URLs), the "best" tool depends on whether your priority is speed, SEO diagnostics, custom analysis, or enterprise-scale crawling.

Here's how I'd rank the major options.

1. Screaming Frog (best overall)

Pros

• Finds all internal broken links
• Finds external broken links
• Detects redirect chains
• Detects redirect loops
• Reports orphan URLs (with log files/sitemaps)
• Highly configurable
• JavaScript rendering
• Can crawl millions of URLs if enough RAM/disk is available

Typical workflow:

Crawl
↓
Response Codes
↓
Filter 4xx

Crawl
↓
Reports
↓
Redirect Chains

For sites under ~500k URLs, it's hard to beat.

2. JetOctopus (best cloud crawler)

If your site is

• ecommerce
• marketplace
• publisher
• millions of pages

JetOctopus is excellent.

Advantages:

• doesn't require local resources
• scheduled crawls
• redirect chain visualization
• crawl budget analysis
• integrates server logs
• very fast cloud infrastructure

3. Lumar (formerly Deepcrawl)

Enterprise standard.

Very strong at:

• redirect chains
• canonical issues
• broken links
• crawl path visualization
• massive websites

Usually chosen by Fortune 500 SEO teams.

4. Scrapy (best if you're technical)

If you're comfortable with Python:

Scrapy
↓
Request URL
↓
status
↓
Location header
↓
continue following redirects
↓
record redirect depth
↓
report chain

Advantages:

• unlimited customization
• can run distributed
• parallel requests
• API integrations
• export to databases
• incremental crawling

For engineering teams this is often the best long-term solution.

5. StormCrawler

Designed specifically for very large distributed crawls.

Can crawl

• millions
• tens of millions
• hundreds of millions

URLs using

• Apache Storm
• Elasticsearch
• Kafka

It's much more infrastructure-heavy than SEO tools but scales exceptionally well.

6. Sitebulb

Excellent if you want explanations rather than raw data.

It automatically surfaces:

• redirect chains
• redirect loops
• broken links
• internal 404s
• external 404s

Very user-friendly.

Fastest open-source stack

For engineers, I'd recommend:

Scrapy
+
aiohttp
+
Redis
+
PostgreSQL

or

StormCrawler
+
Kafka
+
Elasticsearch

These can comfortably crawl millions of URLs per day on suitable infrastructure.

Detecting redirect chains efficiently

The key is to avoid repeatedly requesting the same redirects.

A good crawler should cache:

A
→ B
→ C
→ D (200)

Then whenever another page links to A, it already knows the full chain without re-fetching each hop.

Store something like:

URL
Final URL
Hop count
Status
Chain

This dramatically reduces duplicate network requests.

Detecting broken links efficiently

Rather than only reporting 404s, capture:

• 404 Not Found
• 410 Gone
• 451 Unavailable
• DNS failures
• TLS failures
• timeout
• connection refused
• redirect loops
• redirect chains longer than 3–5 hops
• redirects ending in 404s

The most actionable report links each broken destination back to every referring page and anchor text, making fixes straightforward.

If I were building an enterprise crawler

I'd use:

• Scrapy for crawling and URL discovery
• aiohttp (or another async HTTP client) for high-concurrency requests
• Redis for the URL frontier and deduplication
• PostgreSQL (or ClickHouse for very large datasets) to store crawl results
• Elasticsearch/OpenSearch for fast querying and dashboards

This combination scales well into the millions of URLs while giving you complete control over redirect handling, broken-link detection, retry logic, and reporting.

For most SEO professionals, Screaming Frog remains the best desktop choice, while JetOctopus or Lumar are stronger options once you're regularly auditing multi-million-page sites. For engineering teams that need maximum flexibility and scale, a custom crawler built on Scrapy is usually the strongest long-term solution.

If you're crawling very large websites (100k–100M+ URLs), the "best" tool depends on whether your priority is speed, SEO diagnostics, custom analysis, or enterprise-scale crawling.

Here's how I'd rank the major options.

1. Screaming Frog (best overall)

Pros

• Finds all internal broken links
• Finds external broken links
• Detects redirect chains
• Detects redirect loops
• Reports orphan URLs (with log files/sitemaps)
• Highly configurable
• JavaScript rendering
• Can crawl millions of URLs if enough RAM/disk is available

Typical workflow:

Crawl
↓
Response Codes
↓
Filter 4xx

Crawl
↓
Reports
↓
Redirect Chains

For sites under ~500k URLs, it's hard to beat.

2. JetOctopus (best cloud crawler)

If your site is

• ecommerce
• marketplace
• publisher
• millions of pages

JetOctopus is excellent.

Advantages:

• doesn't require local resources
• scheduled crawls
• redirect chain visualization
• crawl budget analysis
• integrates server logs
• very fast cloud infrastructure

3. Lumar (formerly Deepcrawl)

Enterprise standard.

Very strong at:

• redirect chains
• canonical issues
• broken links
• crawl path visualization
• massive websites

Usually chosen by Fortune 500 SEO teams.

4. Scrapy (best if you're technical)

If you're comfortable with Python:

Scrapy
↓
Request URL
↓
status
↓
Location header
↓
continue following redirects
↓
record redirect depth
↓
report chain

Advantages:

• unlimited customization
• can run distributed
• parallel requests
• API integrations
• export to databases
• incremental crawling

For engineering teams this is often the best long-term solution.

5. StormCrawler

Designed specifically for very large distributed crawls.

Can crawl

• millions
• tens of millions
• hundreds of millions

URLs using

• Apache Storm
• Elasticsearch
• Kafka

It's much more infrastructure-heavy than SEO tools but scales exceptionally well.

6. Sitebulb

Excellent if you want explanations rather than raw data.

It automatically surfaces:

• redirect chains
• redirect loops
• broken links
• internal 404s
• external 404s

Very user-friendly.

Fastest open-source stack

For engineers, I'd recommend:

Scrapy
+
aiohttp
+
Redis
+
PostgreSQL

or

StormCrawler
+
Kafka
+
Elasticsearch

These can comfortably crawl millions of URLs per day on suitable infrastructure.

Detecting redirect chains efficiently

The key is to avoid repeatedly requesting the same redirects.

A good crawler should cache:

A
→ B
→ C
→ D (200)

Then whenever another page links to A, it already knows the full chain without re-fetching each hop.

Store something like:

URL
Final URL
Hop count
Status
Chain

This dramatically reduces duplicate network requests.

Detecting broken links efficiently

Rather than only reporting 404s, capture:

• 404 Not Found
• 410 Gone
• 451 Unavailable
• DNS failures
• TLS failures
• timeout
• connection refused
• redirect loops
• redirect chains longer than 3–5 hops
• redirects ending in 404s

The most actionable report links each broken destination back to every referring page and anchor text, making fixes straightforward.

If I were building an enterprise crawler

I'd use:

• Scrapy for crawling and URL discovery
• aiohttp (or another async HTTP client) for high-concurrency requests
• Redis for the URL frontier and deduplication
• PostgreSQL (or ClickHouse for very large datasets) to store crawl results
• Elasticsearch/OpenSearch for fast querying and dashboards

This combination scales well into the millions of URLs while giving you complete control over redirect handling, broken-link detection, retry logic, and reporting.

For most SEO professionals, Screaming Frog remains the best desktop choice, while JetOctopus or Lumar are stronger options once you're regularly auditing multi-million-page sites. For engineering teams that need maximum flexibility and scale, a custom crawler built on Scrapy is usually the strongest long-term solution.

If you're crawling very large websites (100k–100M+ URLs), the "best" tool depends on whether your priority is speed, SEO diagnostics, custom analysis, or enterprise-scale crawling.

Here's how I'd rank the major options.

1. Screaming Frog (best overall)

Pros

• Finds all internal broken links
• Finds external broken links
• Detects redirect chains
• Detects redirect loops
• Reports orphan URLs (with log files/sitemaps)
• Highly configurable
• JavaScript rendering
• Can crawl millions of URLs if enough RAM/disk is available

Typical workflow:

Crawl
↓
Response Codes
↓
Filter 4xx

Crawl
↓
Reports
↓
Redirect Chains

For sites under ~500k URLs, it's hard to beat.

2. JetOctopus (best cloud crawler)

If your site is

• ecommerce
• marketplace
• publisher
• millions of pages

JetOctopus is excellent.

Advantages:

• doesn't require local resources
• scheduled crawls
• redirect chain visualization
• crawl budget analysis
• integrates server logs
• very fast cloud infrastructure

3. Lumar (formerly Deepcrawl)

Enterprise standard.

Very strong at:

• redirect chains
• canonical issues
• broken links
• crawl path visualization
• massive websites

Usually chosen by Fortune 500 SEO teams.

4. Scrapy (best if you're technical)

If you're comfortable with Python:

Scrapy
↓
Request URL
↓
status
↓
Location header
↓
continue following redirects
↓
record redirect depth
↓
report chain

Advantages:

• unlimited customization
• can run distributed
• parallel requests
• API integrations
• export to databases
• incremental crawling

For engineering teams this is often the best long-term solution.

5. StormCrawler

Designed specifically for very large distributed crawls.

Can crawl

• millions
• tens of millions
• hundreds of millions

URLs using

• Apache Storm
• Elasticsearch
• Kafka

It's much more infrastructure-heavy than SEO tools but scales exceptionally well.

6. Sitebulb

Excellent if you want explanations rather than raw data.

It automatically surfaces:

• redirect chains
• redirect loops
• broken links
• internal 404s
• external 404s

Very user-friendly.

Fastest open-source stack

For engineers, I'd recommend:

Scrapy
+
aiohttp
+
Redis
+
PostgreSQL

or

StormCrawler
+
Kafka
+
Elasticsearch

These can comfortably crawl millions of URLs per day on suitable infrastructure.

Detecting redirect chains efficiently

The key is to avoid repeatedly requesting the same redirects.

A good crawler should cache:

A
→ B
→ C
→ D (200)

Then whenever another page links to A, it already knows the full chain without re-fetching each hop.

Store something like:

URL
Final URL
Hop count
Status
Chain

This dramatically reduces duplicate network requests.

Detecting broken links efficiently

Rather than only reporting 404s, capture:

• 404 Not Found
• 410 Gone
• 451 Unavailable
• DNS failures
• TLS failures
• timeout
• connection refused
• redirect loops
• redirect chains longer than 3–5 hops
• redirects ending in 404s

The most actionable report links each broken destination back to every referring page and anchor text, making fixes straightforward.

If I were building an enterprise crawler

I'd use:

• Scrapy for crawling and URL discovery
• aiohttp (or another async HTTP client) for high-concurrency requests
• Redis for the URL frontier and deduplication
• PostgreSQL (or ClickHouse for very large datasets) to store crawl results
• Elasticsearch/OpenSearch for fast querying and dashboards

This combination scales well into the millions of URLs while giving you complete control over redirect handling, broken-link detection, retry logic, and reporting.

For most SEO professionals, Screaming Frog remains the best desktop choice, while JetOctopus or Lumar are stronger options once you're regularly auditing multi-million-page sites. For engineering teams that need maximum flexibility and scale, a custom crawler built on Scrapy is usually the strongest long-term solution.

If you're crawling very large websites (100k–100M+ URLs), the "best" tool depends on whether your priority is speed, SEO diagnostics, custom analysis, or enterprise-scale crawling.

Here's how I'd rank the major options.

1. Screaming Frog (best overall)

Pros

• Finds all internal broken links
• Finds external broken links
• Detects redirect chains
• Detects redirect loops
• Reports orphan URLs (with log files/sitemaps)
• Highly configurable
• JavaScript rendering
• Can crawl millions of URLs if enough RAM/disk is available

Typical workflow:

Crawl
↓
Response Codes
↓
Filter 4xx

Crawl
↓
Reports
↓
Redirect Chains

For sites under ~500k URLs, it's hard to beat.

2. JetOctopus (best cloud crawler)

If your site is

• ecommerce
• marketplace
• publisher
• millions of pages

JetOctopus is excellent.

Advantages:

• doesn't require local resources
• scheduled crawls
• redirect chain visualization
• crawl budget analysis
• integrates server logs
• very fast cloud infrastructure

3. Lumar (formerly Deepcrawl)

Enterprise standard.

Very strong at:

• redirect chains
• canonical issues
• broken links
• crawl path visualization
• massive websites

Usually chosen by Fortune 500 SEO teams.

4. Scrapy (best if you're technical)

If you're comfortable with Python:

Scrapy
↓
Request URL
↓
status
↓
Location header
↓
continue following redirects
↓
record redirect depth
↓
report chain

Advantages:

• unlimited customization
• can run distributed
• parallel requests
• API integrations
• export to databases
• incremental crawling

For engineering teams this is often the best long-term solution.

5. StormCrawler

Designed specifically for very large distributed crawls.

Can crawl

• millions
• tens of millions
• hundreds of millions

URLs using

• Apache Storm
• Elasticsearch
• Kafka

It's much more infrastructure-heavy than SEO tools but scales exceptionally well.

6. Sitebulb

Excellent if you want explanations rather than raw data.

It automatically surfaces:

• redirect chains
• redirect loops
• broken links
• internal 404s
• external 404s

Very user-friendly.

Fastest open-source stack

For engineers, I'd recommend:

Scrapy
+
aiohttp
+
Redis
+
PostgreSQL

or

StormCrawler
+
Kafka
+
Elasticsearch

These can comfortably crawl millions of URLs per day on suitable infrastructure.

Detecting redirect chains efficiently

The key is to avoid repeatedly requesting the same redirects.

A good crawler should cache:

A
→ B
→ C
→ D (200)

Then whenever another page links to A, it already knows the full chain without re-fetching each hop.

Store something like:

URL
Final URL
Hop count
Status
Chain

This dramatically reduces duplicate network requests.

Detecting broken links efficiently

Rather than only reporting 404s, capture:

• 404 Not Found
• 410 Gone
• 451 Unavailable
• DNS failures
• TLS failures
• timeout
• connection refused
• redirect loops
• redirect chains longer than 3–5 hops
• redirects ending in 404s

The most actionable report links each broken destination back to every referring page and anchor text, making fixes straightforward.

If I were building an enterprise crawler

I'd use:

• Scrapy for crawling and URL discovery
• aiohttp (or another async HTTP client) for high-concurrency requests
• Redis for the URL frontier and deduplication
• PostgreSQL (or ClickHouse for very large datasets) to store crawl results
• Elasticsearch/OpenSearch for fast querying and dashboards

This combination scales well into the millions of URLs while giving you complete control over redirect handling, broken-link detection, retry logic, and reporting.

For most SEO professionals, Screaming Frog remains the best desktop choice, while JetOctopus or Lumar are stronger options once you're regularly auditing multi-million-page sites. For engineering teams that need maximum flexibility and scale, a custom crawler built on Scrapy is usually the strongest long-term solution.

If the goal is very large sites—hundreds of thousands to millions of URLs—and specifically finding 404s, broken links, redirect chains/loops, and links pointing to redirects, I’d shortlist these:

1. Lumar — my pick for enormous sites

Lumar is particularly compelling when crawl speed itself is the bottleneck. Its current crawler advertises up to 450 URLs/sec non-rendered and 350 URLs/sec rendered, and is explicitly designed for sites with millions of URLs. It also reports HTTP status codes, redirect chains, broken resources, link structure, etc. www.lumar.iosupport.sitebulb.com

For a 5–20M URL site, this is the kind of architecture I'd look at first.

Best when: crawl completion time and enterprise-scale infrastructure matter more than having a desktop application.

2. Oncrawl — best for crawl + logs

Oncrawl is particularly strong if you don't just want to find broken URLs but want to answer "which broken/redirected URLs actually matter?"

It can crawl millions of URLs, render JavaScript, and combine crawl data with log-file and SEO data. Its crawler specifically handles redirect loops/chains and can follow up to 30 redirects for analysis. www.oncrawl.com

That's valuable on huge sites because you can prioritize things like:

• redirect chains receiving lots of Googlebot hits
• 404s receiving significant traffic
• sections generating excessive crawl waste
• redirects that are disproportionately expensive to crawl

Best when: you're doing serious enterprise technical SEO rather than simply running a broken-link report.

3. Sitebulb Cloud — best combination of usability and scale

Sitebulb has become a strong option for large sites. Its Cloud crawler is designed for millions of URLs, including JavaScript rendering at scale. sitebulb.com

For your specific problem, it has particularly nice reporting: it identifies broken internal links, internal links to redirects, and redirect chains, and you can export redirect-chain data for further analysis. support.sitebulb.com

I'd choose it over a more enterprise-oriented platform if the people actually operating the crawler need to explore and understand the results easily.

4. Screaming Frog SEO Spider — best power-user option

Don't underestimate Screaming Frog for large sites.

Its database storage mode is designed specifically for large crawls. The documented default is 5M URLs, but it can go beyond that with appropriate hardware/configuration; Screaming Frog gives an example of ~10M URLs with a 500GB SSD and 16GB RAM. www.screamingfrog.co.uk

For serious crawling I'd use:

• database storage
• SSD/NVMe
• plenty of RAM
• carefully configured URL/parameter exclusions
• crawl only the resource types you actually need
• separate crawls for different subdomains/sections where appropriate

Screaming Frog is particularly good when you want precise control over exactly what gets crawled rather than handing everything to a cloud crawler.

Best when: you have an SEO engineer/technical person who wants maximum control.

5. JetOctopus — very good for massive sites

JetOctopus is worth serious consideration for database-driven sites with enormous URL counts. Its positioning is specifically around very large crawling, with no simultaneous-crawl or project limits advertised, and it combines crawling with log analysis. jetoctopus.com

I'd put it particularly high on the list for large ecommerce/faceted sites, where URL explosions and crawl-budget issues are common.

6. Ahrefs Site Audit — excellent if you already use Ahrefs

Ahrefs catches both broken pages and redirect chains, and its Site Audit can check external links as well. help.ahrefs.com

Its verified-site crawler can be configured up to 30,000 URLs/minute, although actual speed should be constrained by what your server can handle. help.ahrefs.com

The catch for truly gigantic sites is the crawl-credit model: depending on the subscription, Site Audit analyzes 100K–5M pages/month. help.ahrefs.com

So I wouldn't make Ahrefs my primary crawler for a 20M+ URL site, but it's excellent as a complementary SEO data source.

What I'd actually use

For a 1M+ URL website, my choices would be:

If you want one tool:
→ Lumar or Sitebulb Cloud

If you're an enterprise SEO team:
→ Oncrawl + Lumar

If you're technical and want maximum control:
→ Screaming Frog

If it's a gigantic ecommerce/database site:
→ JetOctopus or Lumar

If you're already paying for Ahrefs:
→ Use Ahrefs Site Audit alongside your primary crawler rather than necessarily replacing it.

One important distinction

For broken-link/redirect work, don't just look for URLs returning 404. The most useful dataset is really:

source URL → linked URL → HTTP status → redirect hop 1 → hop 2 → ... → final URL/status

That lets you distinguish:

• direct 404 — A → 404
• link to redirect — A → B (301) → C (200)
• redirect chain — A → B (301) → C (301) → D (200)
• broken redirect — A → B (301) → C (404)
• redirect loop — A → B → A
• redirect to another domain
• internal links that should be updated to the final destination

For your particular use case, Sitebulb and Lumar are especially attractive because they expose this link/redirect relationship rather than merely giving you a list of bad destination URLs. www.lumar.iosupport.sitebulb.com

If you're talking about something truly huge (10M–100M+ URLs), I'd narrow the field considerably and look at Lumar vs. Oncrawl vs. a custom crawler architecture, because at that scale crawl scheduling, deduplication, URL-parameter control, concurrency, storage, and incremental crawling become more important than the UI.

For very large sites, I’d narrow the field to a few serious crawlers. The best choice depends on whether you want a powerful desktop crawler, cloud-scale crawling, or an API/automation-heavy setup.

My shortlist

1. Screaming Frog — my default recommendation

Screaming Frog is particularly strong if your primary task is:

crawl everything → identify 4xx/5xx → trace redirects → find pages linking to the bad/redirected URLs → export the remediation list.

Its Redirect Chains report maps the entire chain, counts hops, identifies the source, and flags redirect loops. It also has a Redirects to Errors report, which is particularly useful for finding cases where a URL redirects to a 404/5xx. www.screamingfrog.co.uk

For very large crawls, its database storage mode is important. Screaming Frog says its default limit is 5 million URLs, but it can go beyond that with appropriate hardware; its documentation gives roughly 2 million URLs with 4 GB allocated RAM, 5 million with ~10 GB, and 10 million with ~16 GB as rough examples. www.screamingfrog.co.uk

For your use case, I'd choose this if you have the infrastructure to run it.

2. Lumar — if "very large" means genuinely enormous

Lumar is more compelling once you're talking about enterprise sites with millions of URLs, especially if you don't want to manage a powerful crawling workstation/VM yourself.

Lumar claims crawling speeds up to 450 pages/sec and specifically supports millions of URLs, with redirect chains, HTTP status codes, broken resources and link structure among its technical SEO checks. www.lumar.io

The big advantage is that the crawling infrastructure is cloud-based, so you can throw substantial workloads at it without turning your local machine into a database server.

I'd pick Lumar over Screaming Frog for a 10M–100M+ enterprise property where crawl throughput and centralized workflows matter more than having the most granular desktop controls.

3. Sitebulb — excellent alternative

Sitebulb has both desktop and cloud versions and explicitly supports sites ranging from thousands to 5 million URLs. sitebulb.com

Its biggest strength is arguably analysis and presentation rather than raw crawling. If you're auditing a giant site and need to quickly understand why thousands of broken links or redirects exist, its visualization and issue prioritization are excellent.

I'd put it behind Screaming Frog for a pure "find every bad URL as efficiently as possible" workflow, but ahead of it if communicating findings to stakeholders is important.

4. Oncrawl — best for crawl-data analysis

Oncrawl is worth considering when crawling isn't an isolated task but part of a broader enterprise SEO data pipeline.

Its redirect tooling identifies chains and loops and can follow chains to a substantial depth; it also supports using crawl data to analyze migrations and structural problems. help.oncrawl.com

I'd favor it when you're combining crawl data with things like log files, organic traffic, indexation and site architecture rather than simply wanting a list of broken links.

The important part: crawl architecture

For a really large website, the crawler itself isn't the whole solution. I'd structure the process roughly like this:

1. Discover URLs from multiple sources

• XML sitemaps
• Internal links
• Canonicals
• hreflang
• structured data
• redirects
• server logs
• existing URL inventories

2. Do a lightweight HTTP crawl first

Check:

URL → status → Location → final status

This lets you identify enormous numbers of redirect/broken URL problems without rendering pages unnecessarily.

3. Separately crawl HTML for link relationships

You want to know not merely:

/old-page = 301

but:

/article-123 → /old-page → /new-page

That makes the remediation actionable.

4. Classify redirect problems

I'd distinguish:

• 301 → 200 — generally okay, but potentially unnecessary
• 302 → 200 — investigate
• 301 → 301 → 200 — redirect chain
• 301 → 301 → 301 → 200 — high-priority chain
• 301 → 404 — broken redirect
• 301 → 5xx — server failure
• URL → itself — redirect loop
• URL → A → B → A — loop
• internal link → redirect — update the source link

The last category is particularly valuable: don't just report redirects; identify the internal links causing them.

What I'd use

If you told me the site was:

• <1M URLs: Screaming Frog
• 1–5M: Screaming Frog in database mode, or Sitebulb Cloud
• 5–20M: Lumar or a carefully configured Screaming Frog deployment
• 20M+ / enterprise: Lumar/Oncrawl, potentially supplemented by a custom HTTP crawler
• Continuous monitoring: Lumar/Oncrawl rather than repeatedly running a desktop crawl

For Screaming Frog specifically, its database storage mode is designed for this kind of workload, and the vendor recommends an SSD; its stated recommended hardware for million-URL crawling is a 64-bit machine with an SSD and around 16 GB RAM. www.screamingfrog.co.uk

If your main objective is specifically "find broken links and redirect chains on a 10M+ URL site as fast as possible," I'd start with Lumar for cloud crawling and Screaming Frog as the technical-audit benchmark.

If the site is very large—hundreds of thousands to millions of URLs—the best choice depends on whether you prioritize raw crawl power, cloud scalability, or analysis.

1. Screaming Frog — best all-around

Screaming Frog SEO Spider

For most technical SEO teams, this would be my first choice. It has extremely granular crawl data, flexible filtering/export, custom extraction, JavaScript rendering, and excellent handling of redirects and broken URLs.

For large crawls, Screaming Frog recommends database storage on an SSD. Their documentation says roughly 4 GB allocated RAM can handle up to ~2M URLs, 8 GB around ~5M, and 16 GB around ~10M depending on the site and configuration. www.screamingfrog.co.uk

Particularly good for:

• 404/410 discovery
• Finding every internal link pointing to a broken URL
• 301/302 chains
• Redirect loops
• Redirect → 404 situations
• Canonical/redirect inconsistencies
• Exporting raw crawl data for your own analysis

If you have a 1–10M URL site and can run a well-configured machine/VM, I'd seriously consider this before moving to a cloud platform.

2. JetOctopus — best for truly enormous sites

JetOctopus

This is the one I'd investigate first if "very large" means 10M, 50M, or 100M+ URLs.

JetOctopus says it is designed for large websites and supports 100M+ URLs, with crawler speeds advertised up to 250 pages/sec. It is cloud-based, so you don't have to dedicate a monster workstation to the crawl. jetoctopus.com

It's especially interesting if you want to combine:

crawl data + Google Search Console + server logs

rather than just asking "what links are broken?"

For example, you can distinguish:

50,000 broken URLs

from:

50,000 broken URLs, of which 3,200 are still being requested by Googlebot and 740 receive significant organic traffic.

That's a much more useful prioritization.

3. Sitebulb — best analysis experience

Sitebulb

Sitebulb is particularly good when you don't just want a giant CSV of problems—you want the crawler to help you understand and prioritize them.

Its link auditing specifically identifies broken internal links and internal links to redirects. Its redirect checks also cover redirect chains, loops, redirect-to-error situations, and related problems. sitebulb.com

Sitebulb has both desktop and cloud versions and explicitly supports sites ranging from thousands to millions of URLs. sitebulb.com

One important consideration: on extremely large sites, link-analysis data can become enormous. Sitebulb gives an example of a 1.6M-URL crawl producing 142.6M links and taking 36 GB with link analysis enabled. support.sitebulb.com

So I'd use its configuration controls aggressively on giant sites.

4. Oncrawl — best for crawl + server-log analysis

Oncrawl

Oncrawl is particularly compelling for enterprise sites where you're trying to understand how search engines actually crawl the site, rather than just discovering links.

It supports millions of URLs, JavaScript rendering, technical auditing, and combining crawl data with log data. www.oncrawl.com

It also explicitly analyzes redirect chains and loops and can export the affected URLs. help.oncrawl.com

I'd choose it when the question is something like:

"Which redirects are wasting Googlebot crawl activity?"

rather than simply:

"Which URLs redirect?"

What I'd use for your specific problem

If your primary objective is finding broken links + redirect chains efficiently, I'd narrow it down to:

Up to ~2M URLs:
→ Screaming Frog

2–10M URLs:
→ Screaming Frog with database storage, or Sitebulb Cloud

10M–100M+ URLs:
→ JetOctopus

Huge enterprise site + server logs:
→ JetOctopus or Oncrawl

You want the easiest interface for diagnosing problems:
→ Sitebulb

There's also a useful distinction between finding a redirect and finding the links that cause it. For example:

/old-page → 301 → /old-page-2 → 301 → /new-page

A good crawler should let you identify both the chain and the pages internally linking to /old-page, so you can change those internal links directly to /new-page.

That's why I'd favor a real crawler over simple HTTP-status checkers for this job. Sitebulb, for example, explicitly exposes the referring URL → target URL relationship for broken links. support.sitebulb.com

My overall ranking for this particular use case:
Screaming Frog → JetOctopus → Sitebulb → Oncrawl, with JetOctopus moving to #1 if you're talking about tens of millions of URLs.

If the goal is very large sites—hundreds of thousands to millions+ of URLs—and specifically broken links, redirect chains, loops, and redirected internal links, I’d shortlist these:

1. Screaming Frog — my default recommendation

Screaming Frog SEO Spider

For actually diagnosing why links are broken, I'd start here. It gives you granular URL-to-URL data, inlinks/outlinks, status codes, redirect paths, and extensive filtering/export capabilities.

The important thing for huge sites is Database Storage mode. Screaming Frog says its default 5-million-URL limit isn't a hard limit; with appropriate hardware, it gives an example of roughly 10 million URLs on a 500 GB SSD + 16 GB RAM. www.screamingfrog.co.uk

It's particularly good if you need reports like:

/old-page → 301 → /new-page → 301 → /final-page → 200

and then want to know every page internally linking to /old-page.

I'd choose it when: you have an SEO/engineering person who wants raw crawl data and maximum control.

2. Botify — best for true enterprise scale

Botify

Botify's SiteCrawler is designed as a cloud crawler for large sites and can crawl/render JavaScript while collecting a very large technical dataset. It explicitly reports broken links and other crawlability problems and supports ongoing monitoring/prioritization. support.botify.com

I'd choose it when: you're dealing with millions/tens of millions of URLs, multiple properties, complicated JS sites, or need a shared enterprise platform rather than a desktop crawler.

3. Ahrefs Site Audit — easiest cloud solution

Ahrefs Site Audit

Ahrefs is surprisingly good for this particular job. Its current Site Audit can crawl up to 170,000 URLs/minute under the appropriate conditions and explicitly detects redirect chains, redirect loops, broken redirects, 4xx/5xx pages, and pages linking to broken URLs. ahrefs.com

Its current plans can analyze 100K–5M pages/month, so it's worth checking the crawl-credit model against your site's size. help.ahrefs.com

I'd choose it when: you want cloud infrastructure and don't want to maintain a crawler workstation/VM.

4. Sitebulb — excellent for diagnosing the results

Sitebulb

Sitebulb is especially nice when the problem isn't merely "which URLs are broken?" but:

"Show me the structure of the problem and help me decide what to fix first."

It explicitly supports broken internal links, internal links to redirects, and dedicated redirect-chain exports. sitebulb.comhelp.ahrefs.com

It can also work at surprisingly large scale: Sitebulb documents a crawl of 1.6 million internal URLs, noting that link-analysis data can become enormous. support.sitebulb.com

I'd choose it when: humans need to analyze and communicate the crawl findings, rather than just dump millions of rows into a database.

5. Oncrawl — particularly interesting if you have server logs

Oncrawl

This becomes more interesting for a giant site because you can combine crawler data + server-log data. That's useful for answering questions such as:

• Which broken URLs are actually being requested?
• Which redirect chains are Googlebot encountering?
• Which 404s have significant crawl activity?
• Which pages are linking to redirects?
• Are there URLs being crawled that aren't discoverable through internal links?

For a huge ecommerce/content site, that distinction is valuable: a crawler tells you what exists in the site's link graph; logs tell you what real crawlers/users are actually requesting.

What I'd actually use

For a 500K–5M URL site, my preference would be:

Screaming Frog + server logs

Screaming Frog gives you the detailed URL/link graph, while logs give you the real-world crawl/request picture.

For 5M+ URLs, I'd lean toward:

Botify / Oncrawl / JetOctopus

because cloud/distributed crawling becomes much more attractive than trying to push everything through one machine.

For a smaller team that wants minimal infrastructure:

Ahrefs Site Audit

is probably the easiest answer.

For SEO consultants who need to investigate and present the problems:

Sitebulb is exceptionally pleasant.

One important optimization

Don't simply crawl every URL and then look for 404s. For a massive site, configure the crawler to prioritize:

1. Internal HTML
2. Sitemap URLs
3. URLs discovered from internal links
4. Redirect destinations
5. 4xx/5xx URLs
6. Redirect chains/loops
7. External links only if they're part of your objective

Screaming Frog specifically recommends narrowing large crawls by subfolder/subdomain, URL parameters, depth, and resource types rather than blindly crawling everything. www.screamingfrog.co.uk

And for redirect chains, the most actionable output isn't just:

A → 301 → B → 301 → C → 200

It's:

A → B → C, plus every internal page linking to A.

That lets engineering replace the internal link with C and eliminate the chain at the source. Ahrefs and Sitebulb both support this kind of inlink analysis. sitebulb.comhelp.ahrefs.com

If you tell me roughly whether the site is 100K, 1M, 10M, or 50M+ URLs, I can narrow this down to the best 2–3 tools and the most efficient crawl architecture.

If your priority is very large sites + finding broken links + fully resolving redirect chains efficiently, I’d shortlist these:

1. Screaming Frog — best if you want control

For pure technical link crawling, Screaming Frog SEO Spider is probably my first choice.

It can crawl up to 5 million URLs per crawl on a licensed installation, with controls for crawl limits, URL parameters, subdomains, redirects, response retries, etc. It also has a dedicated Redirect Chains report and can follow redirects to the final destination. www.screamingfrog.co.uk

That makes it particularly good for something like:

/page-a
   ↓ 301
/page-b
   ↓ 302
/page-c
   ↓ 301
/page-d
   ↓ 200

You can identify the complete chain rather than merely knowing /page-a is a redirect.

Best when: you have an SEO/engineering person who wants granular crawl configuration and exports.

2. Sitebulb — best overall for huge-site diagnostics

I'd pick Sitebulb if you care not just about finding the bad URLs, but understanding where they're linked from and how serious they are.

Its link analysis distinguishes the referring URL from the target URL, so you can get something like:

500 pages → /old-product
/old-product → 301 → /new-product

rather than simply seeing that /old-product is a redirect. It also has dedicated reporting for redirect chains and can export the chains for further analysis. support.sitebulb.com

For genuinely enormous sites, Sitebulb Cloud is particularly interesting: it advertises crawling millions of URLs, including JavaScript rendering at scale, without using your local machine's resources. sitebulb.com

One important consideration: Sitebulb itself notes that large crawls can explode in size because link-analysis data grows much faster than URL counts. It gives an example of a 1.6-million-URL crawl generating 142.6 million links and consuming substantially more disk space when link analysis was enabled. support.sitebulb.com

Best when: you're dealing with hundreds of thousands to millions of URLs and need useful analysis rather than just raw crawl output.

3. JetOctopus — particularly attractive for multi-million-URL sites

For cloud-first crawling at very large scale, I'd investigate JetOctopus.

It's a better fit than a desktop crawler when you don't want your laptop/workstation tied up for hours or days. It's particularly useful for sites where you want to repeatedly crawl large URL inventories and compare results.

Best when: your site is millions of URLs and cloud crawling speed/scale is more important than having every possible desktop configuration option.

4. Oncrawl — best if this becomes an enterprise data problem

Oncrawl is worth considering if the crawler is going to feed a larger SEO/data-analysis operation.

For example, you might want to combine:

• crawl data
• internal links
• log files
• Google Search Console data
• analytics
• indexation information

That's more powerful than simply asking "which URLs return 404?"

Best when: you're an enterprise SEO team and want to correlate crawl problems with search-engine behavior and traffic.

5. Ahrefs — excellent if you already have it

Ahrefs Site Audit specifically detects:

• 404 pages
• broken redirects
• redirect chains
• redirect loops
• pages linking to redirecting URLs

It can also identify the pages containing links to the problematic URLs, which is important because the real fix is often changing the source link, not adding yet another redirect. help.ahrefs.com

So if you already pay for Ahrefs, I wouldn't necessarily buy another crawler just for this.

What I'd actually use

For a very large website, I'd use a two-stage approach:

Stage 1 — exhaustive crawl

Use Screaming Frog, Sitebulb Cloud, or JetOctopus to crawl the entire URL universe.

Prioritize:

HTML pages
internal links
redirects
4xx/5xx responses
canonical URLs
XML sitemaps

Don't blindly crawl every external resource, image, JS file, query parameter, etc. On huge sites those can multiply the crawl enormously. Sitebulb explicitly recommends restricting unnecessary external URLs, resources, subdomains and parameters on large crawls. support.sitebulb.com

Stage 2 — targeted HTTP verification

For every URL that is:

3xx
4xx
5xx

run a lightweight HTTP checker that records the entire redirect path, e.g.:

requested URL
→ status
→ Location
→ status
→ Location
→ final status

That gives you a clean dataset like: