head to head · open source

ragflow vs langgraph

ragflow has 90,911 GitHub stars, 10,764 forks, 1,525 open issues and last shipped yesterday. langgraph has 41,863 stars, 7,069 forks, 786 open issues and last shipped yesterday. ragflow leads on adoption by 117% (90,911 vs 41,863 stars). ragflow is written in Go under Apache-2.0; langgraph is written in Python under MIT. ragflow has attracted 12% as many forks as stars, langgraph 17%. langgraph was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 2 topic tags (ai, ai-agents), so they are genuine substitutes rather than adjacent tools.

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

ragflow ★ 91K langgraph ★ 42K category AI & Machine Learning

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Side by side

ragflow langgraph
GitHub stars ★ 91K ★ 42K
License Apache-2.0 MIT
Written in Go Python
Last push 2026-09-18 2026-09-18
Forks ⑂ 11K ⑂ 7.1K
Self-hosting Yes Yes
Data ownership Your server Your server

pick ragflow if

  • You weight community size — 91K stars and counting
  • You want the Apache-2.0 license terms
  • Your stack matches Go
  • You value the larger contributor base for long-term maintenance

full ragflow profile →

pick langgraph if

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

full langgraph profile →

About ragflow

RAGFlow is an open source Retrieval Augmented Generation engine that fuses RAG with agent capabilities into a context layer for large language models, built for developers and teams that need to turn complex, unstructured documents into production AI systems.

read the full ragflow overview →

About langgraph

LangGraph is a low level Python orchestration framework for building stateful, long running agents, aimed at developers and platform teams who need durable execution, human in the loop control, and persistent memory instead of a turnkey agent application.

read the full langgraph overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 247K Ollama ★ 181K Dify ★ 156K Open WebUI ★ 152K langchain ★ 147K

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

More AI Development Platforms projects

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

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

Frequently asked questions

Is ragflow or langgraph more popular?

ragflow has 90,911 GitHub stars and langgraph has 41,863. ragflow has the larger community by that measure.

Are ragflow and langgraph free?

Both are open source. ragflow is licensed under Apache-2.0 and langgraph under MIT. Neither carries a licence fee.

What is the difference between ragflow and langgraph?

ragflow is written in Go and langgraph 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, ragflow or langgraph?

Choose ragflow if you want the larger community (90,911 stars) or its Apache-2.0 licence terms. Choose langgraph if its feature set, stack or MIT licence fits better. Both are self-hostable.