Pyyan / Compare / RAGFlow vs LlamaIndex vs GraphRAG
RAGFlow vs LlamaIndex vs GraphRAG
3 of 5RAG & Knowledge Graphs · verified 13 Aug 2026
| Specification | RAGFlow | LlamaIndex | GraphRAG |
|---|---|---|---|
| Summary | Visual pipeline builder, deep document understanding. | The strongest option for document-centric retrieval. | Build a knowledge graph first, then query it. |
| Kind | Platform | Framework | Library |
| Graph | Yes | Yes, property graph index | Yes, core |
| Language | Python | Python, TypeScript | Python |
| Licence | Apache 2.0 | MIT | MIT |
| GitHub stars | ~35k | ~45k | ~25k |
| Category | RAG & Knowledge Graphs | RAG & Knowledge Graphs | RAG & Knowledge Graphs |
| Official | InfiniFlow ↗ | LlamaIndex ↗ | Microsoft ↗ |
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.
GraphRAG
- Extracts entities and relationships, then summarises communities
- Answers “what are the themes here” which vector search cannot
- Expensive to index
Best for questions no single chunk can answer.