HaystackFreemium
An open-source framework from deepset for building production LLM applications — RAG, search, and agents — built around composable pipelines.
Agent Development comparison
Haystack vs Semantic Kernel
Pricing, pros, cons, and ideal use cases — side by side.
Semantic KernelFree
An open-source SDK from Microsoft for integrating LLMs into applications, with a focus on enterprise-grade orchestration in C#, Python, and Java.
At a glance
| Haystack | Semantic Kernel | |
|---|---|---|
| Pricing | FreemiumOpen-source framework is free. The deepset AI Platform is a paid, enterprise-oriented managed offering. | FreeOpen-source (MIT), free. Costs come from the model APIs you call. |
| Category | Agent Development | Agent Development |
| Ideal for | Teams building production RAG and searchEngineering orgs that want inspectable pipelinesEnterprises evaluating managed LLM platforms | .NET and Java enterprise development teamsOrgs embedding AI into existing applicationsMicrosoft-ecosystem shops |
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
Semantic Kernel
Pros
- First-class C#, Python, and Java support
- Designed to fit into existing enterprise apps
- Backed and maintained by Microsoft
- Clean plugin and function abstractions
Cons
- Smaller ecosystem than Python-first frameworks
- Roadmap is converging with Microsoft Agent Framework
- Less suited to rapid Python prototyping
Which should you choose?
Semantic Kernel is the lighter-weight option (Free), while Haystack sits higher on the pricing ladder (Freemium). Haystack is built around teams building production rag and search; Semantic Kernel leans more toward .net and java enterprise development teams. Shortlist the one whose strengths line up with your biggest constraint.
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