head to head · open source

Agent-Reach vs DB-GPT

Agent-Reach has 83,525 GitHub stars, 7,317 forks, 137 open issues and last shipped 5 days ago. DB-GPT has 20,014 stars, 2,936 forks, 439 open issues and last shipped 4 days ago. Agent-Reach leads on adoption by 317% (83,525 vs 20,014 stars). Agent-Reach is written in Python under MIT; DB-GPT is written in Python under MIT. Agent-Reach has attracted 9% as many forks as stars, DB-GPT 15%. DB-GPT was the more recently maintained of the two, and both are self-hostable with no licence fee.

Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.

Agent-Reach ★ 84K DB-GPT ★ 20K category AI & Machine Learning

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Side by side

Agent-Reach DB-GPT
GitHub stars ★ 84K ★ 20K
License MIT MIT
Written in Python Python
Last push 2026-09-15 2026-09-16
Forks ⑂ 7.3K ⑂ 2.9K
Self-hosting Yes Yes
Data ownership Your server Your server

pick Agent-Reach if

  • You weight community size — 84K stars and counting
  • You want the MIT license terms
  • Your stack matches Python
  • You value the larger contributor base for long-term maintenance

full Agent-Reach profile →

pick DB-GPT if

  • You want the DB-GPT feature set and don't need the biggest community
  • You prefer the MIT license terms
  • Your stack matches Python
  • You evaluated both and DB-GPT fits your workflow better

full DB-GPT profile →

About Agent-Reach

Agent Reach is an open source Python command line tool that gives AI agents the ability to read and search the wider internet — Twitter/X, Reddit, YouTube, GitHub, Bilibili, and XiaoHongShu among others — for developers and agent builders who want that reach without paying for platform APIs.

read the full Agent-Reach overview →

About DB-GPT

DB GPT is an open source, MIT licensed agentic AI data assistant written in Python that connects to databases, CSV and Excel files, warehouses, and knowledge bases so large language models can write SQL and code, run reusable skills in sandboxed environments, and turn analysis into charts, dashboards, HTML reports, and written insights.

read the full DB-GPT overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 247K Ollama ★ 181K Dify ★ 157K Open WebUI ★ 153K langchain ★ 147K

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openclaw vs dify openclaw vs multica openclaw vs langgraph n8n vs dify dify vs langflow dify vs open-webui dify vs langchain dify vs ponytail openclaw vs hermes-agent openclaw vs opencode openclaw vs n8n openclaw vs open-webui openclaw vs comfyui openclaw vs odysseus openclaw vs lobechat openclaw vs anythingllm openclaw vs ollama ollama vs llama-cpp ollama vs vllm ollama vs odysseus ollama vs gpt4all ollama vs llama-index ollama vs localai open-webui vs gpt4all

More AI Development Platforms projects

Compare either of these against the rest of the AI Development Platforms field.

Agent-Reach vs Dify Agent-Reach vs langchain Agent-Reach vs ponytail Agent-Reach vs generative-ai-for-beginners Agent-Reach vs graphify Agent-Reach vs claude-mem Agent-Reach vs ragflow Agent-Reach vs PaddleOCR Agent-Reach vs headroom Agent-Reach vs Mem0 Agent-Reach vs daily_stock_analysis Agent-Reach vs LiteLLM

Frequently asked questions

Is Agent-Reach or DB-GPT more popular?

Agent-Reach has 83,525 GitHub stars and DB-GPT has 20,014. Agent-Reach has the larger community by that measure.

Are Agent-Reach and DB-GPT free?

Both are open source. Agent-Reach is licensed under MIT and DB-GPT under MIT. Neither carries a licence fee.

What is the difference between Agent-Reach and DB-GPT?

Agent-Reach is written in Python and DB-GPT in Python. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.

Which should I choose, Agent-Reach or DB-GPT?

Choose Agent-Reach if you want the larger community (83,525 stars) or its MIT licence terms. Choose DB-GPT if its feature set, stack or MIT licence fits better. Both are self-hostable.