Pyyan / Compare / LlamaIndex vs RAGFlow vs GraphRAG
LlamaIndex vs RAGFlow vs GraphRAG
3 of 5RAG & Knowledge Graphs · verified 13 Aug 2026
| Specification | LlamaIndex | RAGFlow | GraphRAG |
|---|---|---|---|
| Summary | The strongest option for document-centric retrieval. | Visual pipeline builder, deep document understanding. | Build a knowledge graph first, then query it. |
| Kind | Framework | Platform | Library |
| Graph | Yes, property graph index | Yes | Yes, core |
| Language | Python, TypeScript | Python | Python |
| Licence | MIT | Apache 2.0 | MIT |
| GitHub stars | ~45k | ~35k | ~25k |
| Category | RAG & Knowledge Graphs | RAG & Knowledge Graphs | RAG & Knowledge Graphs |
| Official | LlamaIndex ↗ | InfiniFlow ↗ | Microsoft ↗ |
Highlighted rows are where these differ.
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.
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.