Comparisons / Google ADK vs Haystack

Google ADK vs Haystack: Which Agent Framework to Use?

Google ADK vs Haystack, head to head

Google ADK and Haystack both let you build an agent, but they sit in different parts of the stack and they assume different things about who's writing the code.

Google's Agent Development Kit (ADK) is an open-source framework for building multi-agent systems.

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

Underneath, both wrap the same thing: a model call, a tool dispatch, a loop. The decision is about which abstraction your team wants to think in day to day, and which ecosystem you're willing to inherit along with it. There's an honest, framework-free version of the same pattern in about 60 lines of Python in the lesson at the bottom of this page — useful as a baseline regardless of which framework wins.

Pick Google ADK if

Pick Google ADK if aDK earns its complexity when you need multi-agent orchestration on Google Cloud with Vertex AI deployment. If you're using Gemini and need production-grade agent infrastructure, it's well-designed. For single-agent use cases or non-Google stacks, plain Python keeps things simpler. The tradeoffs in its intro should match how your team already thinks about agents; Haystack will feel like translation if they don't.

Full Google ADKcomparison →

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. The tradeoffs in its intro should match how your team already thinks about agents; Google ADK will feel like translation if they don't.

Full Haystackcomparison →

What both add

Whichever you pick, you're inheriting a dependency tree and a vocabulary your team has to learn before they ship anything. Google ADK has its own class hierarchy and tool registration conventions; Haystack has its. Either way, when something misbehaves you'll be reading framework source before you reach the actual HTTP call.

If the real workload is one model and a handful of tools, both can feel like a workbench for driving a nail. The lesson below builds the same pattern in plain Python — useful as a comparison point even if you ultimately keep the framework.

By the numbers

By the numbers

Google ADK

GitHub Stars

18.7k

Forks

3.2k

Language

Python

License

Apache-2.0

Created

2025-04-01

Created by

Google

Backed by

Google/Alphabet

Cloud/SaaS

Vertex AI

Production ready

Yes

github.com/google/adk-python

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

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

ConceptGoogle ADKHaystack
Agent`LlmAgent` class with model, instructions, and `sub_agents` list`Agent` component with `ChatGenerator`, tool definitions, and message routing
Tools`FunctionTool`, built-in tools (Search, Code Exec), third-party integrations`Tool` dataclass with function reference, name, description, parameters schema
Agent Loop`Runner.run()` with automatic tool dispatch and sub-agent delegation
Multi-AgentHierarchical agent tree with root agent delegating to specialized sub-agents
Workflows`SequentialAgent`, `ParallelAgent`, `LoopAgent` workflow primitives
SessionSession and State service with typed channels and persistence
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

Or build your own in 60 lines

Both Google ADK and Haystack 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 →