Pyyan / Compare / LlamaIndex vs LangChain & LangGraph vs Haystack vs GraphRAG

LlamaIndex vs LangChain & LangGraph vs Haystack vs GraphRAG

4 of 5

RAG & Knowledge Graphs · verified 13 Aug 2026

×LlamaIndexLlamaIndexcurrent
×LangChain & LangGraphLangChaincurrent
×Haystackdeepsetcurrent
×GraphRAGMicrosoftcurrent
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SpecificationLlamaIndexLangChain & LangGraphHaystackGraphRAG
SummaryThe strongest option for document-centric retrieval.Orchestration, with retrieval as one piece.A strict pipeline abstraction, built for regulated work.Build a knowledge graph first, then query it.
KindFrameworkFrameworkFrameworkLibrary
GraphYes, property graph indexVia integrationsVia integrationsYes, core
LanguagePython, TypeScriptPython, TypeScriptPythonPython
LicenceMITMITApache 2.0MIT
GitHub stars~45k~120k~20k~25k
CategoryRAG & Knowledge GraphsRAG & Knowledge GraphsRAG & Knowledge GraphsRAG & Knowledge Graphs
OfficialLlamaIndexLangChaindeepsetMicrosoft

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.

Full spec sheet →

LangChain & LangGraph

  • LangGraph adds durable state and checkpointing
  • Widely used, and widely argued about

Best for agents that retrieve as one step among many.

Full spec sheet →

Haystack

  • Every step is declared, which is what audits need
  • Cleanest option where a wrong answer has consequences

Best for finance, health, legal and government.

Full spec sheet →

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.

Full spec sheet →