DB GPT

Free

Interact your data and environment using the local GPT, no data leaks, 100% privately, 100% security ![GitHub Repo stars](https://img.shields.io/github/stars/csunny/DB-GPT?style=social)

FreeFree tier

Inputs: textOutputs: code

Type

Open Source

Company

eosphoros-ai

Visit Website GitHub (40 stars)

About DB GPT

DB-GPT is an open-source agentic AI data assistant designed for the next generation of AI + Data products. It enables users and teams to connect to multiple data sources (databases, CSV/Excel files, warehouses, knowledge bases), ask natural language questions to autonomously generate SQL and code, execute Python-driven analysis workflows in sandboxed environments, and produce charts, dashboards, HTML reports, and analysis summaries. It supports skills-driven extensibility, allowing domain-specific knowledge and analysis methods to be packaged into reusable skills. As a platform, DB-GPT also facilitates building AI-native data agents, workflows, and applications with agents, AWEL, RAG, and multi-model support.

Key Features

Agentic data analysis: Plans tasks, breaks work into steps, calls tools, and completes analysis workflows end to end

Autonomous SQL and code execution: Generates SQL and code to query data, clean datasets, compute metrics, and produce outputs

Multi-source data access: Works across structured and unstructured sources including databases, spreadsheets, documents, and knowledge bases

Skills-driven extensibility: Packages domain knowledge, analysis methods, and execution workflows into reusable skills

Sandboxed execution: Runs code and tools in isolated environments for safer, more reliable analysis

Natural language interface: Users ask questions in plain language and AI writes SQL autonomously

Pros & Cons

Pros

Fully open-source and free to use
No data leaks – runs locally with 100% privacy and security
Handles both structured and unstructured data sources
Supports sandboxed code execution for safety
Extensible through reusable skills and domain workflows
Agentic planning enables complex multi-step analysis

Cons

Requires local deployment and technical setup
May need significant computational resources for large models
Steep learning curve for non-technical users

Best For

Analyze CSV/Excel files and generate visual reportsConnect to databases and produce profiling reportsAsk business questions in natural language and let AI write SQL automaticallyPerform financial report analysis with code, charts, and narrative summariesCreate and reuse SQL analysis skills and domain-specific workflowsCombine code, SQL, retrieval, and tools in a single agentic workflowBuild next-generation AI + Data assistants for teams or products