What is DB-GPT used for?

DB-GPT is an open-source agentic AI data assistant that connects to databases and files, writes SQL and code from natural language, and produces charts, reports and insights. It is a good fit for letting analysts query databases in plain language, automated reporting from CSV and Excel data, and building private data agents.

Is DB-GPT open source?

Yes. DB-GPT is open source under the MIT licence. Its source code is on GitHub at eosphoros-ai/DB-GPT and is written mainly in Python.

Yes. DB-GPT is open source, so the software itself is free to use.

Can I self-host DB-GPT?

Yes. DB-GPT can be self-hosted on your own server or infrastructure; there is no official hosted version.

What is DB-GPT an alternative to?

DB-GPT is an open-source alternative to Julius AI, ThoughtSpot, Tellius and Akkio. Other open-source alternatives to Julius AI include Nao, DeepAnalyze and Pretzel.

Is DB-GPT actively maintained?

Yes. The most recent commit to DB-GPT was on 29 September 2026, and the latest release is v0.8.2, published on 26 August 2026. The project has 20k stars on GitHub.

DB-GPT: open-source alternative to Julius AI, ThoughtSpot

About DB-GPT

DB-GPT is an open-source AI data assistant for the next generation of products that combine AI and data. It connects to databases, CSV and Excel files, data warehouses and knowledge bases, then lets people ask questions in natural language while the AI writes SQL and code to answer them.

Beyond question answering, it supports agentic data analysis: planning a task, breaking it into steps, calling tools and finishing the analysis end to end. It can run Python and code-driven workflows, load reusable skills for domain-specific tasks, and generate charts, dashboards, HTML reports and summaries. Tasks run in sandboxed environments for safety. Beyond the assistant, it serves as a platform for building AI-native data agents and applications with its AWEL workflow language, retrieval-augmented generation and multi-model support, with topics naming models such as DeepSeek and Vicuna.

It is written in Python and licensed under MIT, with documentation, a community and a research paper. Privacy and security are highlighted in the topics, and it can run on your own infrastructure with local models. It suits data teams that want natural-language access to databases while keeping data in-house.

Key features

Natural-language questions answered with generated SQL
Connects to databases, spreadsheets and warehouses
Agentic multi-step analysis workflows
Sandboxed code and skill execution
Chart, dashboard and report generation
AWEL, RAG and multi-model support

Good fit for

→Letting analysts query databases in plain language
→Automated reporting from CSV and Excel data
→Building private data agents

Built with: Python
Tags: ai; text-to-sql; data-assistant; llm; rag; agents; python; database; self-hosted

DB-GPT: questions and answers

What is DB-GPT used for?: DB-GPT is an open-source agentic AI data assistant that connects to databases and files, writes SQL and code from natural language, and produces charts, reports and insights. It is a good fit for letting analysts query databases in plain language, automated reporting from CSV and Excel data, and building private data agents.
Is DB-GPT open source?: Yes. DB-GPT is open source under the MIT licence. Its source code is on GitHub at eosphoros-ai/DB-GPT and is written mainly in Python.
Is DB-GPT free?: Yes. DB-GPT is open source, so the software itself is free to use.
Can I self-host DB-GPT?: Yes. DB-GPT can be self-hosted on your own server or infrastructure; there is no official hosted version.
What is DB-GPT an alternative to?: DB-GPT is an open-source alternative to Julius AI, ThoughtSpot, Tellius and Akkio. Other open-source alternatives to Julius AI include Nao, DeepAnalyze and Pretzel.
Is DB-GPT actively maintained?: Yes. The most recent commit to DB-GPT was on 29 September 2026, and the latest release is v0.8.2, published on 26 August 2026. The project has 20k stars on GitHub.