--- title: "DB-GPT vs pandas-ai" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/eosphoros-ai-db-gpt-vs-sinaptik-ai-pandas-ai" tools: ["eosphoros-ai-db-gpt", "sinaptik-ai-pandas-ai"] --- # DB-GPT vs pandas-ai *GraphCanon updated Aug 18, 2026* ## Verdict Pick DB-GPT if dB-GPT is an open-source framework that integrates with various LLM services, streamlining tasks from reasoning to SQL execution and planning; 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. [DB-GPT](http://docs.dbgpt.cn) reports 20k GitHub stars, 2.9k forks, and 428 open issues, last pushed Aug 17, 2026. [pandas-ai](https://pandas-ai.com) has 24k stars, 2.3k forks, and 22 open issues, last pushed Oct 28, 2025. Figures are from public GitHub metadata via [DB-GPT's repository](https://github.com/eosphoros-ai/DB-GPT) and [pandas-ai's repository](https://github.com/sinaptik-ai/pandas-ai). | | [DB-GPT](/tools/eosphoros-ai-db-gpt.md) | [pandas-ai](/tools/sinaptik-ai-pandas-ai.md) | | --- | --- | --- | | Tagline | open-source agentic AI data assistant for the next generation of AI + Data products | Chat with your database or your datalake using LLMs and RAG. | | Stars | 19,740 | 23,746 | | Forks | 2,882 | 2,342 | | Open issues | 428 | 22 | | Language | Python | Python | | Adopt for | DB-GPT is an open-source framework that integrates with various LLM services, streamlining tasks from reasoning to SQL execution and planning. | 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 | | Persona | - | - | | Runtime | - | - | | License | MIT | Other | | Categories | Data & Retrieval, LLM Frameworks | Data & Retrieval, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [DB-GPT](/tools/eosphoros-ai-db-gpt.md) | [pandas-ai](/tools/sinaptik-ai-pandas-ai.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 292d | | Open issues (now) | 428 | 22 | | Stars delta | +239 (30d) | +90 (30d) | | Open issues delta | -5 (30d) | +1 (30d) | | Full report | [trust report](/tools/eosphoros-ai-db-gpt/trust.md) | [trust report](/tools/sinaptik-ai-pandas-ai/trust.md) | ## Shared compatibility - **Python**: [DB-GPT](/tools/eosphoros-ai-db-gpt.md) - Python runtime; [pandas-ai](/tools/sinaptik-ai-pandas-ai.md) - Python runtime ## Decision facts: DB-GPT - **Adopt for:** DB-GPT is an open-source framework that integrates with various LLM services, streamlining tasks from reasoning to SQL execution and planning. ## 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 ## Choose when ### Choose DB-GPT if… - License: DB-GPT is MIT, pandas-ai is Other. - Tags unique to DB-GPT: agents, bgi, deepseek, gpt. - - You need a tool that can handle complex data processing and task automation using AI. ### Choose pandas-ai if… - License: pandas-ai is Other, DB-GPT is MIT. - 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, datalake. - - When you need to perform complex data analysis tasks interactively through natural language commands. ## When NOT to use DB-GPT - - You are looking for a heavily community-customized or fine-tuned experience as,DB-GPT's flexibility might be limited compared to more customizable systems. - - Your use case strictly requires proprietary services and you seek a tool without dependency on third-party LLM services which DB-GPT inherently relies upon. - - Deployment contexts that strictly adhere to closed-source frameworks or environments where open-source software is restricted might not align well with DB-GPT’s licensing model. ## 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. ## Common questions ### What is the difference between DB-GPT and pandas-ai? DB-GPT: open-source agentic AI data assistant for the next generation of AI + Data products. pandas-ai: Chat with your database or your datalake using LLMs and RAG.. See the comparison table for live GitHub stats and shared categories. ### When should I choose DB-GPT over pandas-ai? Choose DB-GPT over pandas-ai when License: DB-GPT is MIT, pandas-ai is Other; Tags unique to DB-GPT: agents, bgi, deepseek, gpt; - You need a tool that can handle complex data processing and task automation using AI. ### When should I choose pandas-ai over DB-GPT? Choose pandas-ai over DB-GPT when License: pandas-ai is Other, DB-GPT is MIT; 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, datalake; - When you need to perform complex data analysis tasks interactively through natural language commands. ### When should I avoid DB-GPT? - You are looking for a heavily community-customized or fine-tuned experience as,DB-GPT's flexibility might be limited compared to more customizable systems. - Your use case strictly requires proprietary services and you seek a tool without dependency on third-party LLM services which DB-GPT inherently relies upon. - Deployment contexts that strictly adhere to closed-source frameworks or environments where open-source software is restricted might not align well with DB-GPT’s licensing model. ### 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. ### Is DB-GPT or pandas-ai more popular on GitHub? pandas-ai has more GitHub stars (23,746 vs 19,740). Stars measure visibility, not whether either tool fits your constraints. ### Are DB-GPT and pandas-ai open source? Yes - both are open-source projects on GitHub (DB-GPT: MIT, pandas-ai: Other). ### Where can I find alternatives to DB-GPT or pandas-ai? GraphCanon lists graph-backed alternatives at [DB-GPT alternatives](/tools/eosphoros-ai-db-gpt/alternatives) and [pandas-ai alternatives](/tools/sinaptik-ai-pandas-ai/alternatives) ([DB-GPT markdown twin](/tools/eosphoros-ai-db-gpt/alternatives.md), [pandas-ai markdown twin](/tools/sinaptik-ai-pandas-ai/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/eosphoros-ai-db-gpt-vs-sinaptik-ai-pandas-ai.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, DB-GPT or pandas-ai? DB-GPT: Very active. pandas-ai: Slowing. 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 DB-GPT and pandas-ai? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [DB-GPT trust report](/tools/eosphoros-ai-db-gpt/trust); [pandas-ai trust report](/tools/sinaptik-ai-pandas-ai/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=eosphoros-ai-db-gpt`](/api/graphcanon/graph?tool=eosphoros-ai-db-gpt) - 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/_