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Haystack vs LangChain

Two fact sheets from our own research, side by side — pricing, platforms, API access and status re-checked by us rather than quoted from the vendors.

The short answer

Free plan
Both — Haystack has a free plan, LangChain is free to use
Public API
Haystack has one; not confirmed by us for LangChain
Best fit
Haystack: Python teams building production RAG or search applications · LangChain: Teams prototyping agents quickly against many models and tools
Trust score
About even — Haystack 90, LangChain 94
Status
Both up at our last check — Haystack Oct 2, 2026, LangChain Sep 6, 2026

From our own records as of each tool's last check. Anything we have not confirmed is left out rather than guessed. How we verify

Side by side

FactHaystackLangChain
CategoryLLM Orchestration FrameworksLLM Orchestration Frameworks
Pricing modelFreemiumFree
Public APIYesNot confirmed
Trust score90 / 10094 / 100
PlatformsLinux, macOS, Windows, APImacOS, Windows, Linux
CompanydeepsetLangChain, Inc.
Launched20192022
Last verifiedOct 2, 2026Sep 6, 2026

What our research says

Haystack

Haystack is a mature, component-based alternative to LangChain for teams that want explicit, inspectable pipelines instead of hidden chains. It is code-first and aimed at engineers, so non-developers will not get far without the commercial platform. Pick it when retrieval quality and debuggability matter more than a huge ecosystem of ready-made recipes.

Pros

  • Apache 2.0 licence with an active repository maintained by a funded company
  • Modular components for retrieval, routing, memory and generation
  • Many model providers and vector databases supported out of the box
  • Pipelines are serializable and suitable for Kubernetes deployment

Cons

  • Code-only; building pipelines requires Python skills
  • Smaller community and fewer tutorials than LangChain
  • Enterprise features and support are sold separately with no published price

LangChain

The default starting point for agent development: no other framework matches its integration catalog, documentation volume or hiring-market familiarity. The catch is churn and depth — major versions have repeatedly rewritten core APIs, and once you need observability or managed deployment you are steered toward the paid LangSmith platform.

Pros

  • Integrations for 1,000+ models, tools, vector stores and databases
  • MIT license with a large contributor community
  • LangGraph runtime adds persistence, rewind and human-in-the-loop control
  • Python and JavaScript keep parity for most features

Cons

  • History of breaking API changes between major versions
  • Layers of abstraction complicate debugging versus direct SDK calls
  • Production observability and deployment funnel into commercial LangSmith

Which one fits

Choose Haystack if you need

  • Python teams building production RAG or search applications
  • Engineers who want explicit pipeline graphs they can serialize, test and deploy
  • Organizations that want an Apache-licensed core with optional vendor support

Choose LangChain if you need

  • Teams prototyping agents quickly against many models and tools
  • Projects that expect to swap LLM providers without rewrites
  • Developers who want abundant examples, courses and community answers

Haystack vs LangChain: the questions people ask

Does Haystack or LangChain have a free tier?

Both: Haystack has a free tier, and LangChain is free to use.

Which has a public API, Haystack or LangChain?

Haystack ships a public API, as of our last verification. A public API for LangChain is not confirmed by us — check its developer docs before you plan an integration.

All LangChain alternatives →Browse all LLM Orchestration Frameworks →