Pyyan / Compare / LLMWare vs LangChain & LangGraph vs Haystack vs RAGFlow

LLMWare vs LangChain & LangGraph vs Haystack vs RAGFlow

4 of 5

RAG & Knowledge Graphs · verified 13 Aug 2026

×LLMWareLLMWarecurrent
×LangChain & LangGraphLangChaincurrent
×Haystackdeepsetcurrent
×RAGFlowInfiniFlowcurrent
1 slot left
SpecificationLLMWareLangChain & LangGraphHaystackRAGFlow
SummaryRAG aimed at CPUs and small models.Orchestration, with retrieval as one piece.A strict pipeline abstraction, built for regulated work.Visual pipeline builder, deep document understanding.
KindFrameworkFrameworkFrameworkPlatform
GraphNoVia integrationsVia integrationsYes
LanguagePythonPython, TypeScriptPythonPython
LicenceApache 2.0MITApache 2.0Apache 2.0
GitHub stars~13k~120k~20k~35k
CategoryRAG & Knowledge GraphsRAG & Knowledge GraphsRAG & Knowledge GraphsRAG & Knowledge Graphs
OfficialLLMWareLangChaindeepsetInfiniFlow

Highlighted rows are where these differ.

LLMWare

  • Small specialised models rather than a frontier call
  • Built for regulated, air-gapped estates

Best for on-premise with no GPU budget.

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 →

RAGFlow

  • Strong document parsing built in
  • The usual entry point for non-developers

Best for teams without a Python engineer.

Full spec sheet →