Comparisons / Haystack vs OpenAI Agents SDK

Haystack vs OpenAI Agents SDK: Which Agent Framework to Use?

Haystack by deepset is a framework for building NLP and LLM pipelines. OpenAI's Agents SDK (evolved from Swarm) provides Agent, Runner, handoffs, and guardrails. Here is how they compare — paradigm, ecosystem, and the use cases each one is actually built for.

By the numbers

Haystack

GitHub Stars

24.7k

Forks

2.7k

Language

Python

License

Apache-2.0

Created

2019-11-14

Created by

deepset

github.com/deepset-ai/haystack

OpenAI Agents SDK

GitHub Stars

20.6k

Forks

3.4k

Language

Python

License

MIT

Created

2025-03-11

Created by

OpenAI

github.com/openai/openai-agents-python

GitHub stats as of April 2026. Stars indicate community interest, not necessarily quality or fit for your use case.

ConceptHaystackOpenAI Agents SDK
Agent`Agent` component with `ChatGenerator`, tool definitions, and message routing`Agent(name, instructions, model, tools)`
Tools`Tool` dataclass with function reference, name, description, parameters schemaPython functions with type hints, auto-converted to schemas
Pipeline Architecture`Pipeline()` with `add_component()` and `connect()` — a directed graph of typed components
RAG / Retrieval`DocumentStore` + `Retriever` + `PromptBuilder` + `Generator` wired in a `Pipeline`
Memory`ChatMessageStore` with `ConversationMemory` component in pipeline
DeploymentPipeline YAML serialization, `Hayhooks` REST server
Agent Loop`Runner.run()` handles the loop internally
Handoffs`Handoff` between `Agent` objects for multi-agent routing
Guardrails`InputGuardrail` and `OutputGuardrail` with tripwire pattern
ContextTyped context object passed through the agent lifecycle

Haystack vs OpenAI Agents SDK, head to head

Haystack Haystack by deepset is a framework for building NLP and LLM pipelines.

OpenAI Agents SDK OpenAI's Agents SDK (evolved from Swarm) provides Agent, Runner, handoffs, and guardrails.

Both wrap the same underlying agent pattern — an LLM call, a tool dispatch, a loop — in different abstractions. The choice between them is mostly about which mental model and ecosystem fits the team you have, not which one is technically more capable.

Pick Haystack if

Pick Haystack if haystack earns its complexity when you're building RAG pipelines with multiple retrieval stages, document processing, and production deployment needs. But for straightforward agents with a few tools, the plain Python version is simpler to write and debug. Haystack is the right fit when the tradeoffs in its intro line up with how your team actually wants to work day-to-day; OpenAI Agents SDK would force you to translate.

Full Haystack comparison →

Pick OpenAI Agents SDK if

Pick OpenAI Agents SDK if the Agents SDK is the thinnest framework on this list — it barely abstracts beyond what you'd write yourself. Use it when you want OpenAI's conventions and auto-schema generation. Skip it when you want full control or use non-OpenAI models. OpenAI Agents SDK is the right fit when the tradeoffs in its intro line up with how your team actually wants to work day-to-day; Haystack would force you to translate.

Full OpenAI Agents SDK comparison →

What both add

Both Haystack and OpenAI Agents SDK pull in a class hierarchy and a dependency tree to wrap what is, at the core, an HTTP POST in a while loop. If your use case is straightforward — one provider, a handful of tools, a single agent — the framework cost may exceed the framework benefit. The lesson below shows the same pattern in ~60 lines without either dependency.

Or build your own in 60 lines

Both Haystack and OpenAI Agents SDK implement the same 8 patterns. An agent is a function. Tools are a dict. The loop is a while loop. The whole thing composes in ~60 lines of Python.

No framework. No dependencies. No opinions. Just the code.

Build it from scratch →