Pyyan / Compare / RAGFlow vs LlamaIndex vs LangChain & LangGraph
RAGFlow vs LlamaIndex vs LangChain & LangGraph
3 of 5RAG & Knowledge Graphs · verified 13 Aug 2026
| Specification | RAGFlow | LlamaIndex | LangChain & LangGraph |
|---|---|---|---|
| Summary | Visual pipeline builder, deep document understanding. | The strongest option for document-centric retrieval. | Orchestration, with retrieval as one piece. |
| Kind | Platform | Framework | Framework |
| Graph | Yes | Yes, property graph index | Via integrations |
| Language | Python | Python, TypeScript | Python, TypeScript |
| Licence | Apache 2.0 | MIT | MIT |
| GitHub stars | ~35k | ~45k | ~120k |
| Category | RAG & Knowledge Graphs | RAG & Knowledge Graphs | RAG & Knowledge Graphs |
| Official | InfiniFlow ↗ | LlamaIndex ↗ | LangChain ↗ |
Highlighted rows are where these differ.
RAGFlow
- Strong document parsing built in
- The usual entry point for non-developers
Best for teams without a Python engineer.
LlamaIndex
- Deep document handling and many indexing strategies
- The common advice is LlamaIndex for retrieval, LangGraph for orchestration
Best for PDFs, knowledge bases, structured data.
LangChain & LangGraph
- LangGraph adds durable state and checkpointing
- Widely used, and widely argued about
Best for agents that retrieve as one step among many.