Independent Evaluation
LangChain vs LlamaIndex: Framework Comparison for Enterprise RAG
Technical evaluation of LangChain vs LlamaIndex for building enterprise Retrieval-Augmented Generation (RAG) and LLM agent applications.
RAG & Indexing
| Feature | LangChain | LlamaIndex |
|---|---|---|
| Data Ingestion Integrations | excellent | excellent |
| Advanced Chunking & Parsing | good | excellent |
| Hierarchical & Node Indexing | average | excellent |
| Vector DB Native Adapters | excellent | excellent |
Agents & Workflow Orchestration
| Feature | LangChain | LlamaIndex |
|---|---|---|
| Multi-Agent Support | excellent | good |
| State Graph Control (LangGraph) | excellent | good |
| Tool & API Execution | excellent | good |
| Observability & Tracing | excellent | good |
Consultant Guidance by Context
Choose LangChain if...
- You are building complex multi-agent workflows requiring fine-grained state control
- You need deep integration with LangGraph for production state machines
- You require broad integrations across hundreds of tools and APIs
Choose LlamaIndex if...
- Your primary objective is high-accuracy enterprise RAG on structured/unstructured docs
- You need advanced document parsing, node indexing, and query transformations out of the box
- You want faster time-to-market for search and Q&A over proprietary knowledge bases
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