HaystackFreemium
An open-source framework from deepset for building production LLM applications — RAG, search, and agents — built around composable pipelines.
AI / LLM comparison
Haystack vs LangGraph
Pricing, pros, cons, and ideal use cases — side by side.
LangGraphFreemium
A low-level orchestration framework for building stateful, multi-step agent workflows with explicit control over state, branching, and human-in-the-loop steps.
At a glance
| Haystack | LangGraph | |
|---|---|---|
| Pricing | FreemiumOpen-source framework is free. The deepset AI Platform is a paid, enterprise-oriented managed offering. | FreemiumOpen-source framework, free to use. Paid tiers apply to the surrounding LangSmith platform, not the framework itself. |
| Category | AI / LLM | AI / LLM |
| Ideal for | Teams building production RAG and searchEngineering orgs that want inspectable pipelinesEnterprises evaluating managed LLM platforms | Engineering teams building multi-step agentsEnterprise platform teamsWorkflows needing human-in-the-loop control |
Pros & cons
Haystack
Pros
- Explicit, testable pipeline architecture
- Mature retrieval and evaluation tooling
- Managed deepset platform for governed deployments
- Production-focused rather than demo-focused
Cons
- Pipeline model is less flexible than free-form agents
- Smaller community than LangChain or LlamaIndex
- Managed platform pricing requires a sales conversation
LangGraph
Pros
- Explicit control over agent state and branching
- First-class human-in-the-loop and checkpointing
- Strong fit for durable, long-running workflows
- Large ecosystem and active development
Cons
- Requires real engineering investment
- Lower-level than no-code agent builders
- You own deployment and observability
Which should you choose?
Haystack is built around teams building production rag and search; LangGraph leans more toward engineering teams building multi-step agents. Shortlist the one whose strengths line up with your biggest constraint.