DeepYard

Haystack vs LangChain

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

Direct Answer

Haystack suits teams needing open-source access, pipelines focus, and 26,274 GitHub stars in current listing data. LangChain suits teams needing open-source access, typescript focus, and 144,745 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
H

Haystack

End-to-end LLM framework for building NLP and agent pipelines — 18K+ stars

OSSFree
26.3K600.0K/wtoday415
Visit GitHub
L

LangChain

Build context-aware reasoning applications with LLMs

OSSFree
144.7K850.0K/wtoday467
Visit GitHub
MetricHaystackLangChain
GitHub Stars26.3K144.7K
Contributors415467
Last CommitAug 22, 2026Aug 22, 2026
Open Issues95416
Licenseopen-sourceopen-source
Pricingopen-sourceopen-source
Free TierYesYes
Categoryframeworksframeworks
TrendingNoNo

Choose Haystack if you need

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

Choose LangChain if you need

  • • LangChain stands out for Typescript workflows that are not listed for Haystack.
  • • 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 26,274 for Haystack.

Meaningful differences

  • • Workflow emphasis: Haystack highlights Python, while LangChain highlights Typescript.
  • • GitHub adoption: Haystack shows 26,274 stars versus 144,745 for LangChain.
  • • Contributor count: Haystack lists 415 contributors and LangChain lists 467.

Shared capabilities

  • • Python
  • • Rag
  • • Agents

Shared Tags

pythonragagents

Only in Haystack

pipelinesnlpproductionopen-source

Only in LangChain

llmchainstypescriptorchestration

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 Haystack

Haystack by deepset is a Python framework for building production-ready LLM applications, RAG pipelines, and AI agents. It provides a composable pipeline architecture where components (retrievers, generators, rankers, agents) connect through a directed graph. Haystack supports all major LLM providers and vector databases, with strong emphasis on evaluation, testing, and production deployment.

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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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