--- title: "pandas-ai vs unstract" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/sinaptik-ai-pandas-ai-vs-zipstack-unstract" tools: ["sinaptik-ai-pandas-ai", "zipstack-unstract"] --- # pandas-ai vs unstract *GraphCanon updated Aug 17, 2026* ## Verdict Pick pandas-ai if pandasAI is a Python library that allows users to interact conversationally with databases (SQL) and data lakes (CSV, Parquet), leveraging large language models (LLMs) for improved accessibility and efficiency in data wr; 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. [pandas-ai](https://pandas-ai.com) reports 24k GitHub stars, 2.3k forks, and 22 open issues, last pushed Oct 28, 2025. [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 [pandas-ai's repository](https://github.com/sinaptik-ai/pandas-ai) and [unstract's repository](https://github.com/Zipstack/unstract). | | [pandas-ai](/tools/sinaptik-ai-pandas-ai.md) | [unstract](/tools/zipstack-unstract.md) | | --- | --- | --- | | Tagline | Chat with your database or your datalake using LLMs and RAG. | LLM-Driven Extraction of Unstructured Data for API Deployments and ETL Pipeline Workflows | | Stars | 23,746 | 6,932 | | Forks | 2,342 | 663 | | Open issues | 22 | 88 | | Language | Python | Python | | Adopt for | PandasAI is a Python library that allows users to interact conversationally with databases (SQL) and data lakes (CSV, Parquet), leveraging large language models (LLMs) for improved accessibility and efficiency in data wr | 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 | Other | AGPL-3.0 | | Categories | Data & Retrieval, LLM Frameworks | Data & Retrieval, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [pandas-ai](/tools/sinaptik-ai-pandas-ai.md) | [unstract](/tools/zipstack-unstract.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Very active (96%) | | Days since push | 292d | 0d | | Open issues (now) | 22 | 88 | | Stars delta | +90 (30d) | Unknown | | Open issues delta | +1 (30d) | Unknown | | Full report | [trust report](/tools/sinaptik-ai-pandas-ai/trust.md) | [trust report](/tools/zipstack-unstract/trust.md) | ## Decision facts: pandas-ai - **Pricing:** unknown - Pricing details for using pandas-ai, especially those related to the integration of external LLM services like GPT-4, are unclear based on available information. - **Adopt for:** PandasAI is a Python library that allows users to interact conversationally with databases (SQL) and data lakes (CSV, Parquet), leveraging large language models (LLMs) for improved accessibility and efficiency in data wr ## 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 pandas-ai if… - License: pandas-ai is Other, unstract is AGPL-3.0. - Pricing: Pricing details for using pandas-ai, especially those related to the integration of external LLM services like GPT-4, are unclear based on available information.. - Tags unique to pandas-ai: ai, csv, data-analysis, database. - pandas-ai ships Docker support for self-hosted deployment. - - When you need to perform complex data analysis tasks interactively through natural language commands. ### Choose unstract if… - License: unstract is AGPL-3.0, pandas-ai is Other. - 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 pandas-ai - - When you require advanced, custom SQL features that cannot be effectively translated from natural language commands. - - For applications where precise control over every aspect of query formulation is necessary due to performance or security concerns. - - In scenarios that demand real-time analytical capabilities beyond the conversational analysis offered by PandasAI. - - If your data operations are better managed through traditional programming techniques and you do not see significant value in conversational data querying. ## 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 pandas-ai and unstract? pandas-ai: Chat with your database or your datalake using LLMs and RAG.. 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 pandas-ai over unstract? Choose pandas-ai over unstract when License: pandas-ai is Other, unstract is AGPL-3.0; Pricing: Pricing details for using pandas-ai, especially those related to the integration of external LLM services like GPT-4, are unclear based on available information.; Tags unique to pandas-ai: ai, csv, data-analysis, database; pandas-ai ships Docker support for self-hosted deployment; - When you need to perform complex data analysis tasks interactively through natural language commands. ### When should I choose unstract over pandas-ai? Choose unstract over pandas-ai when License: unstract is AGPL-3.0, pandas-ai is Other; 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 pandas-ai? - When you require advanced, custom SQL features that cannot be effectively translated from natural language commands. - For applications where precise control over every aspect of query formulation is necessary due to performance or security concerns. - In scenarios that demand real-time analytical capabilities beyond the conversational analysis offered by PandasAI. - If your data operations are better managed through traditional programming techniques and you do not see significant value in conversational data querying. ### 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 pandas-ai or unstract more popular on GitHub? pandas-ai has more GitHub stars (23,746 vs 6,932). Stars measure visibility, not whether either tool fits your constraints. ### Are pandas-ai and unstract open source? Yes - both are open-source projects on GitHub (pandas-ai: Other, unstract: AGPL-3.0). ### Where can I find alternatives to pandas-ai or unstract? GraphCanon lists graph-backed alternatives at [pandas-ai alternatives](/tools/sinaptik-ai-pandas-ai/alternatives) and [unstract alternatives](/tools/zipstack-unstract/alternatives) ([pandas-ai markdown twin](/tools/sinaptik-ai-pandas-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/sinaptik-ai-pandas-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, pandas-ai or unstract? pandas-ai: Slowing. 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 pandas-ai and unstract? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [pandas-ai trust report](/tools/sinaptik-ai-pandas-ai/trust); [unstract trust report](/tools/zipstack-unstract/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=sinaptik-ai-pandas-ai`](/api/graphcanon/graph?tool=sinaptik-ai-pandas-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/_