Capability · Comparison
LangChain vs LlamaIndex
LangChain and LlamaIndex are often treated as rivals but solve different problems. LangChain is general-purpose orchestration — chains, agents, tools, memory. LlamaIndex is retrieval-over-your-data — ingestion, indexing, query engines over structured and unstructured documents. Most production systems use both.
Side-by-side
| Criterion | LangChain | LlamaIndex |
|---|---|---|
| Primary purpose | Agent & chain orchestration | Retrieval over your data |
| Tool / function calling | First-class (LangGraph) | Supported, less central |
| Document ingestion & indexing | Basic loaders | Rich — 160+ loaders, query engines |
| Agent framework | LangGraph (state-machine style) | Agent & workflow APIs — simpler |
| Observability | LangSmith (first-party, strong) | Third-party (Arize, Phoenix) |
| Production deployments | Strong via LangServe / LangGraph Cloud | Llama Cloud + community hosts |
| Learning curve | Steeper — many abstractions | Gentler for RAG-first use cases |
Verdict
Use LangChain when the problem is orchestration — multi-step tool use, agent graphs, human-in-the-loop, memory, and observability through LangSmith. Use LlamaIndex when the problem is getting your data into the LLM — loaders, chunking strategies, query engines over mixed structured / unstructured sources. Many teams combine them: LlamaIndex owns the retrieval layer, LangChain owns the agent / chain layer.
When to choose each
Choose LangChain if…
- You need agent graphs, state machines, human-in-the-loop workflows.
- You want first-party observability (LangSmith).
- You're shipping complex multi-step tool use.
Choose LlamaIndex if…
- Your primary challenge is RAG over messy enterprise documents.
- You need pre-built ingestion for 160+ formats / sources.
- You want query engines (keyword + semantic + hybrid) out of the box.
Frequently asked questions
Are LangChain and LlamaIndex competitors?
Not really. LangChain is an agent and orchestration framework; LlamaIndex is a retrieval-over-your-data framework. They solve different parts of the stack and are frequently used together in production.
Which is easier to learn — LangChain or LlamaIndex?
LlamaIndex has a gentler on-ramp for the classic 'RAG over my documents' use case. LangChain has more surface area and is steeper, but pays off once you need agents, state machines, or observability.
Sources
- LangChain — docs — accessed 2026-04-20
- LlamaIndex — docs — accessed 2026-04-20