head to head · open source

ragflow vs haystack

ragflow has 90,911 GitHub stars, 10,764 forks, 1,525 open issues and last shipped today. haystack has 26,534 stars, 3,144 forks, 143 open issues and last shipped today. ragflow leads on adoption by 243% (90,911 vs 26,534 stars). ragflow is written in Go under Apache-2.0; haystack is written in Python under Apache-2.0. ragflow has attracted 12% as many forks as stars, haystack 12%. ragflow was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 4 topic tags (agentic-ai, ai, ai-agents, context-engineering), 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 haystack ★ 27K category AI & Machine Learning

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Side by side

ragflow haystack
GitHub stars ★ 91K ★ 27K
License Apache-2.0 Apache-2.0
Written in Go Python
Last push 2026-09-18 2026-09-18
Forks ⑂ 11K ⑂ 3.1K
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 haystack if

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

full haystack 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 haystack

Haystack is an open source AI orchestration framework written in Python under the Apache 2.0 licence, for building context engineered, production ready large language model applications as modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation, and it is aimed at developers and teams building scalable agents, retrieval augmented generation, multimodal applications, semantic search, question answering, and conversational systems.

read the full haystack overview →

More in AI & Machine Learning

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

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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 haystack more popular?

ragflow has 90,911 GitHub stars and haystack has 26,534. ragflow has the larger community by that measure.

Are ragflow and haystack free?

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

What is the difference between ragflow and haystack?

ragflow is written in Go and haystack 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 haystack?

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