Pyyan / Compare / R2R vs LlamaIndex vs LangChain & LangGraph vs Haystack vs RAGFlow
RAG & Knowledge Graphs · verified 13 Aug 2026
| Specification | R2R | LlamaIndex | LangChain & LangGraph | Haystack | RAGFlow |
|---|---|---|---|---|---|
| Summary | RAG as a service you deploy yourself. | The strongest option for document-centric retrieval. | Orchestration, with retrieval as one piece. | A strict pipeline abstraction, built for regulated work. | Visual pipeline builder, deep document understanding. |
| Kind | Platform | Framework | Framework | Framework | Platform |
| Graph | Yes | Yes, property graph index | Via integrations | Via integrations | Yes |
| Language | Python | Python, TypeScript | Python, TypeScript | Python | Python |
| Licence | MIT | MIT | MIT | Apache 2.0 | Apache 2.0 |
| GitHub stars | ~7k | ~45k | ~120k | ~20k | ~35k |
| Category | RAG & Knowledge Graphs | RAG & Knowledge Graphs | RAG & Knowledge Graphs | RAG & Knowledge Graphs | RAG & Knowledge Graphs |
| Official | SciPhi ↗ | LlamaIndex ↗ | LangChain ↗ | deepset ↗ | InfiniFlow ↗ |
Highlighted rows are where these differ.
Best for a working RAG API without building one.
Best for PDFs, knowledge bases, structured data.
Best for agents that retrieve as one step among many.
Best for finance, health, legal and government.
Best for teams without a Python engineer.