When to Use LangChain vs LlamaIndex
Both are standard frameworks for building LLM apps. Their strong areas differ, so choose by use.
The Rough Difference
| LangChain | LlamaIndex | |
|---|---|---|
| Strength | Chaining, agents, breadth of integrations | Data ingestion, RAG, indexing |
| Suited use | Complex workflows/tool integration | Proprietary data search / Q&A |
Selection Guidelines
- "Answer from proprietary data" is the main aim → lean LlamaIndex
- "Multi-tool/agent integration" is the main aim → lean LangChain
- Combined use is possible; mix by role
Caution
- The thicker the abstraction, the harder grasping internal behavior and debugging can be
- For thin requirements, raw API without a framework is simpler and more robust
- APIs/recommended patterns change fast; confirm the latest officially
Key Point
Not "a framework for now" but choose in the order requirements → needed features → minimal tool. Excessive abstraction becomes technical debt.
