head to head · open source

graphify vs ragflow

graphify has 118,991 GitHub stars, 11,505 forks, 1,350 open issues and last shipped 2 days ago. ragflow has 90,889 stars, 10,759 forks, 1,525 open issues and last shipped yesterday. graphify leads on adoption by 31% (118,991 vs 90,889 stars). graphify is written in Python under Apache-2.0; ragflow is written in Go under Apache-2.0. graphify has attracted 10% as many forks as stars, ragflow 12%. ragflow was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (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.

graphify ★ 119K ragflow ★ 91K category AI & Machine Learning

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Side by side

graphify ragflow
GitHub stars ★ 119K ★ 91K
License Apache-2.0 Apache-2.0
Written in Python Go
Last push 2026-09-16 2026-09-17
Forks ⑂ 12K ⑂ 11K
Self-hosting Yes Yes
Data ownership Your server Your server

pick graphify if

  • You weight community size — 119K stars and counting
  • You want the Apache-2.0 license terms
  • Your stack matches Python
  • You value the larger contributor base for long-term maintenance

full graphify profile →

pick ragflow if

  • You want the ragflow feature set and don't need the biggest community
  • You prefer the Apache-2.0 license terms
  • Your stack matches Go
  • You evaluated both and ragflow fits your workflow better

full ragflow profile →

About graphify

graphify is an Apache 2.0 Python CLI and /graphify skill that turns a whole project — code, docs, SQL schemas, configs, PDFs, images, and video — into a queryable knowledge graph, built for developers and AI agent users in Claude Code, Cursor, Codex, and Gemini CLI who want to query a codebase instead of grepping through files.

read the full graphify overview →

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 →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 246K Ollama ★ 181K Dify ★ 156K Open WebUI ★ 152K langchain ★ 147K

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dify vs graphify langchain vs graphify ponytail vs graphify dify vs ragflow dify vs langchain dify vs ponytail langchain vs ponytail dify vs claude-mem openclaw vs hermes-agent openclaw vs open-webui openclaw vs lobechat openclaw vs anythingllm openclaw vs cherry-studio openclaw vs nanobot openclaw vs jan openclaw vs librechat ollama vs llama-cpp ollama vs vllm ollama vs gpt4all ollama vs llama-index ollama vs localai llama-cpp vs vllm ollama vs pageindex ollama vs langfuse

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

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

Frequently asked questions

Is graphify or ragflow more popular?

graphify has 118,991 GitHub stars and ragflow has 90,889. graphify has the larger community by that measure.

Are graphify and ragflow free?

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

What is the difference between graphify and ragflow?

graphify is written in Python and ragflow in Go. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.

Which should I choose, graphify or ragflow?

Choose graphify if you want the larger community (118,991 stars) or its Apache-2.0 licence terms. Choose ragflow if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.