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LangChain vs LlamaIndex

A side-by-side comparison of LangChain and LlamaIndex, two Orchestration tools, drawn from Ignaite's continuously-verified listings.

Compared from listings verified as of

LangChain

Orchestration

The default open-source framework for composing LLM apps.

View LangChain

LlamaIndex

Orchestration

The data framework for LLM apps — RAG, agents, and document workflows.

View LlamaIndex

At a glance

Feature comparison of LangChain and LlamaIndex
AttributeLangChainLlamaIndex
CategoryOrchestrationOrchestration
Pricing (differs)FREEFREEMIUM
License (differs)Open sourceOpen core
Deployment
PlatformsAPI, CLIAPI, CLI
Model supportModel-agnosticModel-agnostic
Vendor (differs)LangChainLlamaIndex
Capabilities (differs)
  • Agent framework
  • Tool / function calling
  • Multi-model access
  • RAG pipeline
  • Embeddings
  • Agent framework
  • RAG pipeline
  • Vector search
  • Chat with documents
  • Document parsing (structured)
  • Structured extraction

The honest brief

LangChain

The default, most-integrated LLM framework — broadest connector ecosystem plus LangGraph + LangSmith in one stack.

  • Huge ecosystem of integrations
  • Python + TypeScript parity
  • Pairs with LangGraph + LangSmith
  • Ubiquitous docs and examples
  • Abstraction layers add overhead
  • Often overkill for simple RAG
  • Black-box debugging at scale
  • Frequent breaking API churn

LlamaIndex

Retrieval-first where LangChain is orchestration-first — LlamaParse is the go-to for PDFs that defeat normal parsers.

  • Best-in-class RAG primitives
  • LlamaParse for hard documents
  • Python + TypeScript
  • Managed LlamaCloud option
  • Narrower than full orchestration frameworks
  • LlamaCloud parsing is paid
  • API churn between versions

When to pick which

Both cover Agent framework and RAG pipeline.

Pick LangChain if you need Tool / function calling, Multi-model access, and Embeddings.

  • Tool / function calling (secondary capability)
  • Multi-model access (secondary capability)
  • Embeddings (secondary capability)

Pick LlamaIndex if you need Vector search, Chat with documents, Document parsing (structured), and Structured extraction.

  • Vector search (secondary capability)
  • Chat with documents (secondary capability)
  • Document parsing (structured) (primary capability)
  • Structured extraction (secondary capability)

LangChain leans on Agent framework as a headline capability; LlamaIndex treats it as secondary.

  • Agent framework (primary capability)

They also differ on:

Pricing
FREE · FREEMIUM
License
Open source · Open core