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LlamaIndex vs LangGraph

Trust Score comparison · March 2026

LlamaIndex
82
Trust
Good
View profile
VS
Trust Score Δ
6
🏆 LangGraph wins
LangGraph
88
Trust
Good
View profile

Signal Comparison

300k / wknpm downloads200k / wk
300 commitsCommits (90d)250 commits
38k ★GitHub stars11k ★
5k q'sStack Overflow2k q's
Large & activeCommunityGrowing fast
LlamaIndexLangGraph

Key Differences

FactorLlamaIndexLangGraph
LicenseMITMIT
LanguageTypeScript / PythonTypeScript / Python
HostedSelf-hostedSelf-hosted
Free tier
Open Source
TypeScript

Pick LlamaIndex if…

  • Building RAG over documents, PDFs, or databases
  • You want a data-centric approach vs LangChain's agent-centric
  • Complex ingestion pipelines with multiple data sources

Pick LangGraph if…

  • Building complex multi-step agent workflows
  • You need stateful agents with memory across steps
  • Human-in-the-loop approval flows

Side-by-side Quick Start

LlamaIndex
import { VectorStoreIndex, SimpleDirectoryReader } from 'llamaindex';

const documents = await new SimpleDirectoryReader().loadData({ directoryPath: './data' });
const index = await VectorStoreIndex.fromDocuments(documents);
const queryEngine = index.asQueryEngine();
const response = await queryEngine.query({ query: 'What is the main topic?' });
console.log(response.toString());
LangGraph
import { StateGraph, END } from '@langchain/langgraph';

const workflow = new StateGraph({ channels: { messages: { value: (x, y) => x.concat(y) } } });

workflow.addNode('agent', async (state) => {
  const response = await llm.invoke(state.messages);
  return { messages: [response] };
});

workflow.setEntryPoint('agent');
workflow.addEdge('agent', END);

const app = workflow.compile();
const result = await app.invoke({ messages: [{ role: 'user', content: 'Hello' }] });

Community Verdict

Based on upvoted notes
🏆
LangGraph wins this comparison
Trust Score 88 vs 82 · 6-point difference

LangGraph leads on Trust Score with stronger signal data across downloads and community health. That said, the other tool is worth considering if your use case matches its specific strengths above.