CrewAI vs Google ADK

Detailed side-by-side comparison to help you choose the right tool

CrewAI

πŸ”΄Developer

AI Agents

Open-source Python framework for orchestrating role-playing, autonomous AI agents that collaborate as a 'crew' to complete complex tasks.

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Starting Price

Free

Google ADK

πŸ”΄Developer

Agent framework

Google’s development kit for constructing, evaluating, and deploying modular AI agents.

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Starting Price

Free

Feature Comparison

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FeatureCrewAIGoogle ADK
CategoryAI AgentsAgent framework
Pricing Plans46 tiers4 tiers
Starting PriceFreeFree
Key Features
  • β€’ Workflow Runtime
  • β€’ Tool and API Connectivity
  • β€’ State and Context Handling
  • β€’ Multi-language SDKs: Python 2.0 Beta, TypeScript 1.0, Go, and Java
  • β€’ LLM agents, sequential, parallel, loop, and custom workflow agents
  • β€’ Built-in evaluation framework with criteria, user simulation, and environment simulation

πŸ’‘ Our Take

Choose Google ADK if you need a built-in evaluation framework, multi-language SDKs (Python/TypeScript/Go/Java), native MCP support, and plan to deploy on Google Cloud with Gemini. Choose CrewAI if you want a simpler role-based agent model with a larger community ecosystem and less opinionated structure.

CrewAI - Pros & Cons

Pros

  • βœ“Most opinionated multi-agent framework β€” easy to read, easy to maintain
  • βœ“Free tier includes the full visual Studio editor and 50 executions/month
  • βœ“Trusted by 63% of the Fortune 500 according to CrewAI
  • βœ“MCP-native: crews can consume and expose MCP tools
  • βœ“Enterprise tier has FedRAMP High and dedicated VPC options that competitors lack
  • βœ“Active GitHub community and frequent releases

Cons

  • βœ—Less flexible than LangGraph if you need fine-grained control over state transitions
  • βœ—Free tier capped at 50 workflow executions per month β€” easy to hit
  • βœ—Enterprise pricing is sales-led with no public numbers, making budget planning hard
  • βœ—Hierarchical process can burn tokens fast with a chatty manager agent

Google ADK - Pros & Cons

Pros

  • βœ“Code-first abstractions support versioning and testable agent behavior
  • βœ“Evaluation and deployment workflows address more than prompt prototyping
  • βœ“Natural fit for teams already using Gemini and Google Cloud

Cons

  • βœ—Requires software engineering skills and operational ownership
  • βœ—End-to-end cost depends on separate model and cloud services
  • βœ—Deep Google integration may reduce portability to other stacks

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πŸ”’ Security & Compliance Comparison

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Security FeatureCrewAIGoogle ADK
SOC2β€”β€”
GDPRβ€”β€”
HIPAAβ€”β€”
SSO🏒 Enterpriseβ€”
Self-Hostedβœ… Yesβ€”
On-Premβœ… Yesβ€”
RBAC🏒 Enterpriseβ€”
Audit Logβ€”β€”
Open Sourceβœ… Yesβ€”
API Key Authβœ… Yesβ€”
Encryption at Restβ€”β€”
Encryption in Transitβ€”β€”
Data Residencyβ€”β€”
Data Retentionconfigurableβ€”
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