Compare Crawlora's documented, platform-specific APIs that return normalized JSON with Diffbot's machine-learning extraction, web-scale Knowledge Graph, and Natural Language API.
Benchmark
Before comparing Crawlora to Diffbot on the table below, here’s how Crawlora performs on its own: we ran Crawlora’s /web/scrape endpoint once against a stratified sample of 30 public URLs (docs, e-commerce, and anti-bot-protected sites), with the cache bypassed. 21/30 requests returned usable content.
This is Crawlora's own measured reliability on a single disclosed run — not a head-to-head benchmark against Firecrawl, Scrapfly, or any other named competitor. We don't hold API keys for competitor products and won't publish a number for a tool we haven't actually run.
Internally conducted benchmark, run . Last verified . Full methodology and per-URL results.
Short verdict
Crawlora is stronger for predictable, documented data from known platforms with self-serve pricing. Diffbot is stronger for open-ended ML extraction across the web and entity/Knowledge-Graph use cases.
Quick comparison
Use this table as a starting point for evaluating Crawlora against Diffbot, then verify current details on both providers' official pages before making a production decision.
| Category | Crawlora | Diffbot |
|---|---|---|
| Primary product type | Structured public web data APIs | ML extraction APIs, Knowledge Graph, and Natural Language API |
| Extraction approach | Documented endpoints with fixed response shapes | Machine-learning auto-extraction and page classification |
| Best for | Structured data from known platforms | Open-ended extraction and entity graphs across the web |
| Output format | Normalized JSON by endpoint | Extracted entities/fields inferred by ML models |
| Knowledge Graph | Not offered | Web-scale entity graph of organizations, people, and products |
| Natural Language API | Not offered | Entity and relationship extraction from text |
| Output predictability | Defined schema per endpoint | Depends on model inference for the page type |
| Onboarding | Self-serve docs, Playground, and API keys | Self-serve from $299/month; Enterprise is sales-assisted |
| Entry price | $9/month Starter (20,000 credits) | $299/month Startup (250,000 credits), then $899 Plus (1,000,000 credits) |
| Free tier | 2,000 free credits every month, no card required | 10,000 credits per month on the free plan, all four APIs, no card required |
| Pricing model | Credit-based, one fixed published weight per endpoint (most cost 1-3 credits) | Credit-based at about $1.20 per 1,000 credits on Startup and $0.90 on Plus, with overage at $0.001 and $0.0009 per credit |
| Credits per call | Published per endpoint — for example google/search is 3 credits and amazon/product is 2 | 1 to extract a page (2 via datacenter proxy), 1 per NLP document or web search, 0 to crawl, but 25 per Knowledge Graph entity record and 100 per facet query |
| Cost of 1,000 page extractions | No generic page-extraction tier — pricing is per documented endpoint | About $1.20 on Startup and $0.90 on Plus (1 credit per page) |
| Cost of 1,000 entity records | Not offered — no entity graph product | About $29.90 on Startup and $22.48 on Plus, since a Knowledge Graph entity is 25 credits |
| Rate limit | 5 requests/minute on Free up to 1,000/minute on Enterprise | 5 requests/minute on Free, 5/second on Startup, 25/second on Plus |
| Seats and crawling | No seat limits; crawling is not a separate product | Crawl access starts on Plus (25 active crawls, 3 user seats); Enterprise adds 100+ crawls |
| Agent-native workflows | Structured data and hosted MCP tools for supported endpoints | Extract and Knowledge Graph APIs usable from agents |
Details
Choosing between Crawlora and Diffbot depends on output format, target coverage, developer workflow, and how much infrastructure your team wants to operate.
Crawlora gives you a documented endpoint per supported source and returns a fixed, normalized JSON shape. Diffbot uses machine learning to classify a page (article, product, discussion, and so on) and infer structured fields from arbitrary URLs, which is powerful for the open web but means the output depends on model inference.
If you need a known platform like Amazon, Google Search, TikTok, YouTube, or app stores, Crawlora's per-endpoint schemas are direct and predictable. Diffbot's differentiator is its web-scale Knowledge Graph and Natural Language API — useful when you need entities and relationships across the whole web rather than one platform.
Crawlora emphasizes self-serve: endpoint docs, Playground testing, API keys, and credit usage you can start without a sales call. Diffbot is frequently evaluated for larger or enterprise usage and entity-graph projects, which can involve more upfront scoping.
Use Crawlora when an agent needs clean, structured records from supported public platforms, optionally via hosted MCP tools. Use Diffbot when an agent needs ML extraction from arbitrary pages or to query a Knowledge Graph of entities.
Crawlora uses transparent, credit-based API pricing you can estimate per endpoint call. Diffbot's pricing follows plan and usage tiers and may be quoted for larger projects. Compare the cost per successful workflow for your specific data, not just headline plans.
Crawlora is designed for responsible public web data workflows. It should not be used for private or protected data, and no comparison page should be read as a guarantee that every target will succeed. Review provider terms, target-site rules, and your own compliance requirements before production use.
Evaluation checklist
Compare Crawlora and Diffbot against your real workflow and maintenance burden, not just top-line feature labels.
FAQ
These Diffbot comparison answers use conservative language and should be verified against both providers' official pages for current product and pricing details.
Yes, for buyers comparing web data APIs. Crawlora is platform-specific with documented JSON; Diffbot is ML extraction plus a Knowledge Graph for the open web.
Diffbot is an AI web-data company offering machine-learning extraction APIs, a web-scale Knowledge Graph of entities, and a Natural Language API.
No. Crawlora returns normalized JSON from documented platform endpoints; it does not build a cross-web entity graph the way Diffbot does.
Crawlora's per-endpoint schemas are fixed and documented, so the response shape is predictable. Diffbot's output depends on ML inference for the page type.
Diffbot. Its ML extraction is designed to auto-classify and parse pages across the open web, including sources Crawlora does not cover as endpoints.
Crawlora is a strong fit when those sources are in the supported catalog and you want normalized JSON without relying on inference.
Both bill credits, but the entry points are far apart: Crawlora starts at $9/month for 20,000 credits, Diffbot at $299/month for 250,000. Per credit they are closer than that suggests — roughly $1.20 per 1,000 credits on Diffbot's Startup plan against $0.45 on Crawlora's Starter — and what a credit buys differs completely, so compare cost per successful workflow rather than per credit.
Yes. A common pattern is Crawlora for supported structured platforms and Diffbot for open-web extraction or entity-graph enrichment.
Diffbot offers plans you can start online, but larger usage and Knowledge Graph projects are often sales-assisted. Crawlora is designed for self-serve onboarding.
The free plan gives 10,000 credits a month across all four APIs with no card. Paid plans are $299/month for 250,000 credits (Startup, overage $0.001 per credit, 5 requests/second) and $899/month for 1,000,000 credits (Plus, overage $0.0009, 25 requests/second, 25 active crawls and 3 seats), with Enterprise quoted. That works out at roughly $1.20 and $0.90 per 1,000 credits.
Per Diffbot's pricing page: extracting one page is 1 credit, or 2 through a datacenter proxy; one NLP document of up to 10,000 characters is 1; one web search is 1; and crawling to spider a site for links and pages is 0. The expensive calls are the Knowledge Graph ones — 25 credits per entity record exported or enhanced, 100 for a facet query record or an enhance with refresh. So 1,000 page extractions cost about $1.20 on Startup while 1,000 entity records cost about $29.90.
Last reviewed: . Competitor pricing and features can change. Check each official provider page for the latest details.
Browse endpoint docs, run a Playground request against a platform Diffbot doesn't cover, and compare credit-based pricing before deciding whether Crawlora fits your workflow.