LangGraph vs LlamaIndex

Pick two tools from the same category to compare side-by-side.

	LangGraph Graph-based agent orchestration framework from the LangChain team.	LlamaIndex Data framework for connecting LLMs to private data, with RAG, agents, and event-driven workflows.
Category	framework	framework
Vendor type	hybrid	hybrid
Pricing	freemium	freemium
Strengths	+ Explicit, debuggable graph model for complex flows + Mature Python ecosystem + Tight LangSmith integration	+ Extensive data connectors and RAG tooling + Strong document parsing and ingestion (LlamaParse/LlamaCloud) + Agents and event-driven workflows built in + Large ecosystem and integrations
Tradeoffs	− Steeper learning curve than linear agent SDKs − LangChain abstractions are opinionated	− Broad API surface can be complex to navigate − Heritage is RAG-centric rather than agent-first − Frequent API changes across versions
Used in stacks	5	0