Google Agent Development Kit (ADK) vs Microsoft AutoGen

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

Google Agent Development Kit (ADK)

🔴Developer

AI Automation Platforms

Google's open-source, code-first framework for building, evaluating, and deploying AI agents. Optimized for Gemini but model-agnostic, with built-in multi-agent orchestration and Vertex AI deployment.

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Starting Price

$0

Microsoft AutoGen

AI Automation Platforms

Microsoft's open-source framework for building multi-agent AI systems with asynchronous, event-driven architecture.

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Starting Price

Free

Feature Comparison

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FeatureGoogle Agent Development Kit (ADK)Microsoft AutoGen
CategoryAI Automation PlatformsAI Automation Platforms
Pricing Plans3 tiers11 tiers
Starting Price$0Free
Key Features
  • Code-first agent development in Python and Java
  • Model-agnostic architecture (Gemini, GPT, Claude, LiteLLM)
  • Multi-agent orchestration with Sequential, Parallel, and Loop patterns
  • Multi-agent conversation orchestration with flexible topologies
  • Built-in observability via OpenTelemetry integration
  • Cross-language interoperability between Python and .NET

Google Agent Development Kit (ADK) - Pros & Cons

Pros

  • Completely free and open-source under Apache 2.0 license
  • Model-agnostic — works with Gemini, GPT, Claude, and open-source models via LiteLLM
  • Built-in evaluation framework that LangChain and CrewAI lack out of the box
  • First-class Vertex AI Agent Engine deployment with managed scaling and monitoring
  • Backed by Google's engineering team — same framework powers Agentspace internally
  • Supports both Python (1.0.0+) and Java (0.1.0+), unlike most single-language competitors
  • Native bidirectional streaming for voice and video agent experiences

Cons

  • Requires Python or Java programming knowledge — no visual builder
  • Released April 2025, so community is smaller than LangChain's 90K+ GitHub stars
  • Documentation still maturing for advanced multi-agent patterns
  • Best deployment experience locked to Google Cloud / Vertex AI
  • Fewer third-party integrations than LangChain's 700+ ecosystem connectors
  • Steeper learning curve than no-code alternatives like Relevance AI or BuildShip

Microsoft AutoGen - Pros & Cons

Pros

  • MIT-licensed open source with active development
  • Backed by Microsoft Research with strong academic foundations
  • v0.4's async event-driven architecture enables scalable agent systems
  • Native cross-language support for Python and .NET
  • AutoGen Studio provides a no-code interface for rapid prototyping
  • Tight Azure AI Foundry integration for enterprise deployment

Cons

  • Microsoft's agent strategy is evolving; monitor official announcements for roadmap changes
  • v0.4 introduced major breaking changes from v0.2, requiring significant migration effort
  • Steep learning curve compared to simpler frameworks like CrewAI
  • AutoGen Studio is experimental and not production-ready
  • No commercial support tier outside of Azure AI Foundry

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🔒 Security & Compliance Comparison

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Security FeatureGoogle Agent Development Kit (ADK)Microsoft AutoGen
SOC2
GDPR
HIPAA
SSO
Self-Hosted✅ Yes
On-Prem✅ Yes
RBAC
Audit Log
Open Source✅ Yes
API Key Auth
Encryption at Rest
Encryption in Transit
Data Residency
Data Retentionconfigurable
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