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DB-GPT

Open-source agentic AI data assistant — connect to databases, ask questions in natural language, and let AI write SQL, analyze data, and generate reports and insights autonomously

★ 19,379 GitHub MIT ragdata-analysisai-agentsqldatabaseopen-source RAG & Knowledge

Overview

DB-GPT is an open-source agentic AI data assistant for the next generation of AI + Data products. It connects to databases, CSV files, Excel files, data warehouses, and knowledge bases, allowing users to ask questions in natural language and let AI write SQL, run Python analysis, execute reusable skills, and generate charts, dashboards, HTML reports, and analysis summaries. Built with a modular architecture featuring multi-model support, RAG capabilities, AWEL workflow engine, and sandboxed code execution, DB-GPT is a complete platform for building AI-native data agents and applications. With over 19K GitHub stars and 136K Docker pulls, it's the leading open-source solution for agentic data analysis.

Requirements

Min vCPU
2
Min RAM
4096 MB
Min Disk
10 GB
Rec vCPU
4
Rec RAM
8192 MB
Rec Disk
20 GB

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Docker Compose

# Generated by Run This Ai — docker-compose.yml
services:
  db-gpt:
    image: eosphorosai/dbgpt:latest
    restart: unless-stopped
    ports:
      - 8080:8080
    volumes:
      - ./data/db-gpt:/data

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Guides & articles

Getting Started with DB-GPT: Setup, SQL Generation, and Data Analysis

Step-by-step tutorial for setting up DB-GPT with Docker, connecting databases, and running AI-powered data analysis. Real performance numbers and common mistakes included.

Jul 6, 2026

DB-GPT: Your Open-Source AI Data Assistant for Smarter Analytics

DB-GPT is an open-source agentic AI data assistant that connects to databases, writes SQL, runs Python analysis, and generates insights. Here's my hands-on review with real usage examples.

Jul 6, 2026