--- title: "Scrapegraph-ai vs unstract" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/scrapegraphai-scrapegraph-ai-vs-zipstack-unstract" tools: ["scrapegraphai-scrapegraph-ai", "zipstack-unstract"] --- # Scrapegraph-ai vs unstract *GraphCanon updated Aug 16, 2026* ## Verdict Pick Scrapegraph-ai if scrapegraph-ai is a Python-based scraping tool leveraging AI for smarter data extraction and search tasks; pick unstract if unstract is a Python-driven tool for transforming unstructured data into structured formats using OCR, PDF extraction, and other techniques to integrate with APIs and ETL workflows under AGPL-3.0 license. [Scrapegraph-ai](https://scrapegraphai.com) reports 30k GitHub stars, 2.9k forks, and 12 open issues, last pushed Jul 20, 2026. [unstract](https://unstract.com) has 6.9k stars, 663 forks, and 88 open issues, last pushed Jul 27, 2026. Figures are from public GitHub metadata via [Scrapegraph-ai's repository](https://github.com/ScrapeGraphAI/Scrapegraph-ai) and [unstract's repository](https://github.com/Zipstack/unstract). | | [Scrapegraph-ai](/tools/scrapegraphai-scrapegraph-ai.md) | [unstract](/tools/zipstack-unstract.md) | | --- | --- | --- | | Tagline | Python scraper based on AI | LLM-Driven Extraction of Unstructured Data for API Deployments and ETL Pipeline Workflows | | Stars | 29,618 | 6,932 | | Forks | 2,925 | 663 | | Open issues | 12 | 88 | | Language | Python | Python | | Adopt for | Scrapegraph-ai is a Python-based scraping tool leveraging AI for smarter data extraction and search tasks. | Unstract is a Python-driven tool for transforming unstructured data into structured formats using OCR, PDF extraction, and other techniques to integrate with APIs and ETL workflows under AGPL-3.0 license. | | Persona | - | - | | Runtime | - | - | | License | Scrapegraph-ai operates under the MIT License, offering users flexible rights for modification and distribution of the code. | AGPL-3.0 | | Categories | Data & Retrieval, LLM Frameworks | Data & Retrieval, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Scrapegraph-ai](/tools/scrapegraphai-scrapegraph-ai.md) | [unstract](/tools/zipstack-unstract.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 27d | 0d | | Open issues (now) | 12 | 88 | | Stars delta | +1.2k (30d) | Unknown | | Open issues delta | +5 (30d) | Unknown | | Full report | [trust report](/tools/scrapegraphai-scrapegraph-ai/trust.md) | [trust report](/tools/zipstack-unstract/trust.md) | ## Decision facts: Scrapegraph-ai - **Pricing:** freemium - Free to use with potential charges for advanced features or premium services, as specified by its license. - **Requirements:** Developed in Python and can leverage existing libraries and frameworks related to AI and web scraping. - **Adopt for:** Scrapegraph-ai is a Python-based scraping tool leveraging AI for smarter data extraction and search tasks. - **License detail:** Scrapegraph-ai operates under the MIT License, offering users flexible rights for modification and distribution of the code. ## Decision facts: unstract - **Adopt for:** Unstract is a Python-driven tool for transforming unstructured data into structured formats using OCR, PDF extraction, and other techniques to integrate with APIs and ETL workflows under AGPL-3.0 license. ## Choose when ### Choose Scrapegraph-ai if… - License: Scrapegraph-ai is MIT, unstract is AGPL-3.0. - Pricing: Free to use with potential charges for advanced features or premium services, as specified by its license.. - Requirements: Developed in Python and can leverage existing libraries and frameworks related to AI and web scraping.. - Tags unique to Scrapegraph-ai: ai-crawler, crawler, data-extraction, large-language-model. - Scrapegraph-ai ships Docker support for self-hosted deployment. - When you need advanced AI capabilities to parse and understand the context of scraped web content. ### Choose unstract if… - License: unstract is AGPL-3.0, Scrapegraph-ai is MIT. - Tags unique to unstract: ai-agents, data-engineering, document-ai, generative-ai. - You prioritize open-source contributions and require the flexibility of the AGPL-3.0 license. ## When NOT to use Scrapegraph-ai - If you have simple and straightforward data extraction needs that do not require AI-powered intelligence. - When your project aims to scrape static or relatively unchanging datasets from websites with well-defined structures, as Scrapegraph-ai is more geared towards complex and dynamic scraping tasks where ## When NOT to use unstract - Your workflow strictly adheres to closed-source software management policies and requires proprietary control. - Projects needing direct integration with commercial data processing services incompatible with AGPL-3.0 licensing. - Cases where real-time performance is critical, as the LLM-driven extraction may introduce latency. ## Common questions ### What is the difference between Scrapegraph-ai and unstract? Scrapegraph-ai: Python scraper based on AI. unstract: LLM-Driven Extraction of Unstructured Data for API Deployments and ETL Pipeline Workflows. See the comparison table for live GitHub stats and shared categories. ### When should I choose Scrapegraph-ai over unstract? Choose Scrapegraph-ai over unstract when License: Scrapegraph-ai is MIT, unstract is AGPL-3.0; Pricing: Free to use with potential charges for advanced features or premium services, as specified by its license.; Requirements: Developed in Python and can leverage existing libraries and frameworks related to AI and web scraping.; Tags unique to Scrapegraph-ai: ai-crawler, crawler, data-extraction, large-language-model; Scrapegraph-ai ships Docker support for self-hosted deployment; When you need advanced AI capabilities to parse and understand the context of scraped web content. ### When should I choose unstract over Scrapegraph-ai? Choose unstract over Scrapegraph-ai when License: unstract is AGPL-3.0, Scrapegraph-ai is MIT; Tags unique to unstract: ai-agents, data-engineering, document-ai, generative-ai; You prioritize open-source contributions and require the flexibility of the AGPL-3.0 license. ### When should I avoid Scrapegraph-ai? If you have simple and straightforward data extraction needs that do not require AI-powered intelligence. When your project aims to scrape static or relatively unchanging datasets from websites with well-defined structures, as Scrapegraph-ai is more geared towards complex and dynamic scraping tasks where ### When should I avoid unstract? Your workflow strictly adheres to closed-source software management policies and requires proprietary control. Projects needing direct integration with commercial data processing services incompatible with AGPL-3.0 licensing. Cases where real-time performance is critical, as the LLM-driven extraction may introduce latency. ### Is Scrapegraph-ai or unstract more popular on GitHub? Scrapegraph-ai has more GitHub stars (29,618 vs 6,932). Stars measure visibility, not whether either tool fits your constraints. ### Are Scrapegraph-ai and unstract open source? Yes - both are open-source projects on GitHub (Scrapegraph-ai: MIT, unstract: AGPL-3.0). ### Where can I find alternatives to Scrapegraph-ai or unstract? GraphCanon lists graph-backed alternatives at [Scrapegraph-ai alternatives](/tools/scrapegraphai-scrapegraph-ai/alternatives) and [unstract alternatives](/tools/zipstack-unstract/alternatives) ([Scrapegraph-ai markdown twin](/tools/scrapegraphai-scrapegraph-ai/alternatives.md), [unstract markdown twin](/tools/zipstack-unstract/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/scrapegraphai-scrapegraph-ai-vs-zipstack-unstract.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Scrapegraph-ai or unstract? Scrapegraph-ai: Active. unstract: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for Scrapegraph-ai and unstract? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Scrapegraph-ai trust report](/tools/scrapegraphai-scrapegraph-ai/trust); [unstract trust report](/tools/zipstack-unstract/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=scrapegraphai-scrapegraph-ai`](/api/graphcanon/graph?tool=scrapegraphai-scrapegraph-ai) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_