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 LlamaIndex
Pricing, pros, cons, and ideal use cases — side by side.
LlamaIndexFreemium
A data framework for connecting LLMs to private and enterprise data — ingestion, indexing, retrieval, and agent workflows over your own content.
At a glance
| Haystack | LlamaIndex | |
|---|---|---|
| Pricing | FreemiumOpen-source framework is free. The deepset AI Platform is a paid, enterprise-oriented managed offering. | FreemiumOpen-source framework is free. LlamaCloud (managed parsing and indexing) is sold on usage-based paid plans. |
| Category | Agent Development | Agent Development |
| Ideal for | Teams building production RAG and searchEngineering orgs that want inspectable pipelinesEnterprises evaluating managed LLM platforms | Teams building RAG over internal dataEngineering orgs standardizing ingestion and retrievalEnterprises with large, messy document sets |
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
LlamaIndex
Pros
- Deep, well-documented retrieval toolkit
- Handles complex and messy document types
- Managed LlamaCloud option for scale
- Large ecosystem of connectors
Cons
- Retrieval quality still depends on your tuning and evals
- Overlapping features with LangChain can confuse
- Fast-moving API surface
Which should you choose?
Haystack is built around teams building production rag and search; LlamaIndex leans more toward teams building rag over internal data. Shortlist the one whose strengths line up with your biggest constraint.
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