Comparisons / CrewAI vs Google ADK
CrewAI vs Google ADK: Which Agent Framework to Use?
CrewAI vs Google ADK, head to head
CrewAI and Google ADK 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.
CrewAI organizes work into Agents, Tasks, and Crews.
Google's Agent Development Kit (ADK) is an open-source framework for building multi-agent systems.
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 CrewAI if
Pick CrewAI if crewAI shines for multi-agent setups where you want named roles ("researcher", "writer"). But the core mechanics — tool dispatch, the agent loop, task scheduling — are the same patterns you can build in plain Python. The tradeoffs in its intro should match how your team already thinks about agents; Google ADK will feel like translation if they don't.
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; CrewAI will feel like translation if they don't.
By the numbers
By the numbers
CrewAI
48.0k
6.5k
Python
MIT
2023-10-27
João Moura
Google ADK
18.7k
3.2k
Python
Apache-2.0
2025-04-01
Google/Alphabet
Vertex AI
Yes
GitHub stats as of April 2026. Stars indicate community interest, not necessarily quality or fit for your use case.
| Concept | CrewAI | Google ADK |
|---|---|---|
| Agent | `Agent(role, goal, backstory, tools, llm)` | `LlmAgent` class with model, instructions, and `sub_agents` list |
| Tools | Tool registration with `@tool` decorator, custom `Tool` classes | `FunctionTool`, built-in tools (Search, Code Exec), third-party integrations |
| Agent Loop | Internal to `Agent` execution, hidden from user | `Runner.run()` with automatic tool dispatch and sub-agent delegation |
| Task Delegation | `Crew(agents, tasks, process=sequential/hierarchical)` | — |
| Memory | `ShortTermMemory`, `LongTermMemory`, `EntityMemory` | — |
| State | Task output passed between agents via `Crew` orchestration | — |
| Multi-Agent | — | Hierarchical agent tree with root agent delegating to specialized sub-agents |
| Workflows | — | `SequentialAgent`, `ParallelAgent`, `LoopAgent` workflow primitives |
| Session | — | Session and State service with typed channels and persistence |
Or build your own in 60 lines
Both CrewAI and Google ADK 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 →