DataBlue vs ScrapeGraphAI: Which is Better in 2026?
A comprehensive comparison of DataBlue and ScrapeGraphAI covering features, pricing, use cases, and which tool is the right choice for your needs.
⚡ Quick Verdict
Choose DataBlue if:
- →You need clean markdown, links and structured json instead of raw html or residential and datacenter proxy rotation included in the credit price
Choose ScrapeGraphAI if:
- →You want more affordable paid plans (from $20/mo)
- →You need a broader feature set (6 features vs 5)
- →You need describe the data in a prompt instead of writing selectors or structured json output resilient to markup changes
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DataBlue vs ScrapeGraphAI: At a Glance
Pricing Comparison: DataBlue vs ScrapeGraphAI
Understanding the pricing differences between DataBlue and ScrapeGraphAI is crucial for making the right choice. Here's how their plans compare side by side.
DataBlue Pricing
ScrapeGraphAI Pricing
💡 Pricing takeaway: Both DataBlue and ScrapeGraphAI offer free tiers, making it easy to try before you buy. Compare the specific plans to find the best value for your use case.
Feature-by-Feature Comparison
Here's how every feature from DataBlue and ScrapeGraphAI stacks up.
What Makes Each Tool Unique
🔵 Unique to DataBlue
Features available in DataBlue but not in ScrapeGraphAI:
- ✓Clean markdown, links and structured JSON instead of raw HTML
- ✓Residential and datacenter proxy rotation included in the credit price
- ✓Real headless browser rendering for SPAs and infinite scroll
- ✓One shared credit balance across scrape, crawl, search, SERP and Amazon APIs
- ✓Live sandbox running real requests with no signup, plus a cost calculator
🟣 Unique to ScrapeGraphAI
Features available in ScrapeGraphAI but not in DataBlue:
- ✓Describe the data in a prompt instead of writing selectors
- ✓Structured JSON output resilient to markup changes
- ✓Page and endpoint monitors that alert on change
- ✓Concurrent crawls and per-tier request-rate ceilings
- ✓Basic and advanced proxy rotation on higher tiers
- ✓Non-expiring credit packs that stack on any subscription
Use Case Recommendations
Best for: DataBlue
DataBlue is a scraping and search API that returns LLM-ready output rather than raw HTML. You POST a URL with a list of formats and get back clean markdown, extracted links and metadata as structured JSON, ready to drop into a RAG pipeline without writing a parser. The three parts of scraping that usually become their own infrastructure projects are handled inside the service: a rotating global pool of residential and datacenter proxies so there are no IP bans or CAPTCHAs to manage, a real headless browser that executes JavaScript and waits for content so single-page apps and infinite scroll are captured as a user would see them, and structured extraction so what comes back is usable instead of soup. Beyond /v1/scrape there are crawl, map, search and extract endpoints, and a wide set of data APIs — Google SERP in Lite and Advanced variants, Maps, Images, News, Finance, Jobs, Hotels, Flights, Keyword Suggestions, Trends interest and autocomplete, plus Amazon products, autocomplete, full scrape, store and A+ content. Everything draws on one shared credit balance rather than separate quotas per product, and a workload calculator shows what a run will cost before you execute it, which is a meaningful difference from providers where credit weights are discovered after the invoice. Jobs can run async with polling or webhooks, job history is retained, and the vendor publishes a live sandbox that runs real requests against sample queries with no signup so you can see the exact response shape first.
Ideal use cases:
- •Teams or individuals who need clean markdown, links and structured json instead of raw html
- •Teams or individuals who need residential and datacenter proxy rotation included in the credit price
- •Teams or individuals who need real headless browser rendering for spas and infinite scroll
- •Teams or individuals who need one shared credit balance across scrape, crawl, search, serp and amazon apis
- •Anyone focused on api workflows
- •Anyone focused on web-scraping workflows
Best for: ScrapeGraphAI
ScrapeGraphAI is an AI-native web-scraping API that replaces brittle CSS selectors with a prompt: you say what data you want from a page and it returns structured output, so a site redesign that would have broken a traditional scraper mostly does not break this. It grew out of a widely used open-source Python library into a hosted V2 API the company describes as better, faster and cheaper than the first generation, and the commercial product wraps the extraction core in the operational parts that matter at scale — concurrent crawls, request-rate ceilings, and monitors that watch a page or endpoint and alert on change rather than requiring you to poll it yourself. Proxy rotation appears as a tiered feature, basic on the mid plan and advanced above it, which is the practical difference between scraping a cooperative site and scraping one that does not want to be scraped. Everything is metered in API credits with published rate limits per tier, and one-time credit packs stack on top of a subscription and never expire, so a spiky backfill job does not force a permanent upgrade. The company is SOC 2 Type 2 compliant and states that all requests run under that compliance boundary. Documentation, an API status page, a changelog and a comparison page are public, and there is a dedicated startup programme.
Ideal use cases:
- •Teams or individuals who need describe the data in a prompt instead of writing selectors
- •Teams or individuals who need structured json output resilient to markup changes
- •Teams or individuals who need page and endpoint monitors that alert on change
- •Teams or individuals who need concurrent crawls and per-tier request-rate ceilings
- •Anyone focused on web-scraping workflows
- •Anyone focused on structured-data workflows
🗃️ Other Data Extraction Tools to Consider
DataBlue and ScrapeGraphAI aren't the only options. Here are other popular tools in the same space:
Browse AI
No-code web scraping and monitoring tool.
Maxun
Open-source no-code platform to crawl, scrape, search, and AI-extract web data, with MCP, SDKs, and a visual recorder
Smooth
Serverless browser agent API scoring 92% on WebVoyager — proxies, sessions, and CAPTCHA solving handled
Siftly
Drop invoices or receipts in, get clean CSV, Excel, or Google Sheets data out, from $3.99/month
SocialKit
One API for YouTube, TikTok, Instagram, Facebook, X, and LinkedIn data — transcripts, stats, and profiles
AnyAPI
One key, one wallet, pay-per-request access to 1,200+ web data sources
Is one of these your tool?
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Frequently Asked Questions
Is DataBlue better than ScrapeGraphAI?
It depends on your needs. DataBlue offers 5 key features including Clean markdown, links and structured JSON instead of raw HTML and Residential and datacenter proxy rotation included in the credit price, while ScrapeGraphAI provides 6 features including Describe the data in a prompt instead of writing selectors and Structured JSON output resilient to markup changes. DataBlue uses a freemium model with a free tier, while ScrapeGraphAI is freemium with free access available. Choose based on which features and pricing model align with your requirements.
Is DataBlue cheaper than ScrapeGraphAI?
ScrapeGraphAI is cheaper, starting at $20/month compared to DataBlue's $29/month. Both tools offer free tiers, so you can try each before committing. Always check the official websites for the most current pricing.
Can I use DataBlue and ScrapeGraphAI together?
Yes, many users combine DataBlue and ScrapeGraphAI in their workflow. DataBlue excels at clean markdown, links and structured json instead of raw html, while ScrapeGraphAI shines with describe the data in a prompt instead of writing selectors. Using both allows you to leverage the strengths of each tool, though this means managing two subscriptions — though free tiers can help manage costs.
What's the main difference between DataBlue and ScrapeGraphAI?
While both are data extraction tools, DataBlue emphasizes clean markdown, links and structured json instead of raw html, whereas ScrapeGraphAI is known for describe the data in a prompt instead of writing selectors. The best choice depends on your specific workflow and feature priorities.
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