DeepYard

LangChain vs LangGraph

Side-by-side comparison built from DeepYard's structured catalog. Content updated Aug 21, 2026.

Direct Answer

LangChain suits teams needing open-source access, javascript focus, and 144,745 GitHub stars in current listing data. LangGraph suits teams needing open-source access, graph focus, and 40,209 GitHub stars in current listing data. This summary reflects catalog metadata only for decision support, not independent testing.

What this comparison weighs

  • Pricing and free-tier availability
  • License model and deployment fit
  • GitHub adoption and contributor depth
  • Catalog tags, integrations, and supported workflows
L

LangChain

Build context-aware reasoning applications with LLMs

OSSFree
144.7K850.0K/wtoday467
Visit GitHub
L

LangGraph

LangChain's framework for building stateful agent graphs — 26K+ stars

OSSFree
40.2Ktoday278
Visit GitHub
MetricLangChainLangGraph
GitHub Stars144.7K40.2K
Contributors467278
Last CommitAug 22, 2026Aug 22, 2026
Open Issues416708
Licenseopen-sourceopen-source
Pricingopen-sourceopen-source
Free TierYesYes
Categoryframeworksframeworks
TrendingNoNo

Choose LangChain if you need

  • • LangChain stands out for Javascript workflows that are not listed for LangGraph.
  • • LangChain is the stronger pick when Chain matters because that capability is listed only on its profile.
  • • LangChain shows broader GitHub adoption with 144,745 stars versus 40,209 for LangGraph.

Choose LangGraph if you need

  • • LangGraph is the stronger pick when Graph matters because that capability is listed only on its profile.
  • • LangGraph is the cleaner fit if you specifically need Graph workflows from the catalog tags.

Meaningful differences

  • • Workflow emphasis: LangChain highlights Javascript, while LangGraph highlights Python.
  • • GitHub adoption: LangChain shows 144,745 stars versus 40,209 for LangGraph.
  • • Contributor count: LangChain lists 467 contributors and LangGraph lists 278.

Shared capabilities

  • • Python

Shared Tags

python

Only in LangChain

llmagentschainsragtypescriptorchestration

Only in LangGraph

graphstatefulmulti-agentlangchainpersistenceopen-source

Limitations and evidence

  • • DeepYard compares structured public metadata; this is not an independent benchmark unless a test record is shown.
  • • Signals such as stars, contributors, and last commit indicate public activity, not purchase fit or runtime quality.
  • • Pricing and feature coverage reflect the stored listing snapshot and may lag vendor changes between refreshes.

Source links

Manifest content date: 2026-08-21

About LangChain

LangChain is the most widely adopted framework for building LLM-powered applications. It provides modular abstractions for chains, agents, memory, retrievers, and tools, enabling developers to compose complex pipelines from reusable components. Available in both Python and JavaScript/TypeScript, LangChain integrates with every major LLM provider, vector store, and data source. Its ecosystem includes LangSmith for observability and LangGraph for stateful, graph-based agent workflows.

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About LangGraph

LangGraph is LangChain's framework for building stateful, multi-actor agent applications as graphs. Define agents as nodes and their interactions as edges, with built-in persistence, streaming, human-in-the-loop, and time-travel debugging. The standard for production agent orchestration in the LangChain ecosystem.

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