LangGraph vs LlamaIndex

Detailed side-by-side comparison to help you choose the right tool

LangGraph

🔴Developer

AI agent framework

LangGraph is LangChain's open-source framework for building stateful, durable, multi-agent workflows in Python and JavaScript with graph-based control flow.

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Starting Price

Free

LlamaIndex

🔴Developer

AI agent framework

LlamaIndex is an open-source Python and TypeScript framework for building RAG, document workflows, and AI agents — with LlamaCloud for managed parsing, extraction, and indexing.

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Starting Price

Free

Feature Comparison

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FeatureLangGraphLlamaIndex
CategoryAI agent frameworkAI agent framework
Pricing Plans8 tiers8 tiers
Starting PriceFreeFree
Key Features
  • Graph-based workflow orchestration
  • Deterministic state machine execution
  • Human-in-the-loop workflows
  • LlamaParse for 50+ unstructured file types
  • Document parsing, extraction, indexing, and retrieval
  • Open-source repos plus LiteParse for local document parsing

LangGraph - Pros & Cons

Pros

  • Open-source library is MIT-licensed and runs anywhere without platform lock-in
  • Native checkpointing makes durable, resumable, human-in-the-loop agents straightforward
  • First-class multi-agent patterns: supervisor, hierarchical, sequential, parallel branches
  • Tight integration with LangSmith for production observability, evaluations, and replays
  • Active maintenance from the LangChain team with frequent releases and strong community

Cons

  • More verbose than LangChain for simple agents — explicit state schemas and edge functions add overhead
  • LangSmith trace pricing ($2.50/1k base traces) is a real cost at production scale
  • LCU + deployment-minute billing makes pricing harder to predict than seat-only competitors
  • Steeper learning curve than role-based frameworks like CrewAI for newcomers
  • Best documented in Python; JavaScript SDK exists but lags in features

LlamaIndex - Pros & Cons

Pros

  • Best-in-class retrieval strategies: hybrid, parent-child, summary indexes, knowledge graphs
  • LlamaParse is the strongest PDF/document parser for enterprise RAG today
  • Open-source library is MIT-licensed and runs anywhere
  • Workflows agent layer is a clean alternative to LangGraph for stateful task graphs
  • 10,000 free LlamaCloud credits make evaluation painless

Cons

  • LlamaCloud paid pricing is credit-based and harder to model than seat pricing
  • Workflows ecosystem is younger than LangGraph's; fewer multi-agent examples in the wild
  • Library API has churned over major releases — older tutorials are often out of date
  • Visual builder UX is not part of the product; teams that want no-code go elsewhere
  • Pure agent orchestration with complex branching is still cleaner in LangGraph

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🔒 Security & Compliance Comparison

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Security FeatureLangGraphLlamaIndex
SOC2✅ Yes
GDPR✅ Yes
HIPAA
SSO✅ Yes🏢 Enterprise
Self-Hosted🔀 Hybrid🔀 Hybrid
On-Prem✅ Yes
RBAC✅ Yes
Audit Log✅ Yes
Open Source✅ Yes✅ Yes
API Key Auth✅ Yes✅ Yes
Encryption at Rest✅ Yes
Encryption in Transit✅ Yes
Data Residencynot publicly confirmed
Data Retentionconfigurablecached data retained for 48 hours by default for LlamaParse, with caching optional
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