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