Google ADK vs Semantic Kernel
Updated March 10, 2026
Overview
Google's Agent Development Kit (ADK) is a modular framework for building AI agents that integrates natively with Gemini models and Vertex AI. It supports multi-agent architectures, tool use, memory, and deployment to Google Cloud, providing an end-to-end solution for building agents in the Google ecosystem.
Semantic Kernel is Microsoft's enterprise SDK for integrating AI into applications. It provides planners for multi-step task execution, plugin architectures for tool use, memory systems, and connectors for all major LLM providers. Available in C#, Python, and Java, Semantic Kernel is designed for enterprise .NET shops building AI-powered features into existing applications.
Key features
Core capabilities each platform advertises.
- Enterprise AI orchestration by Microsoft
- C# and Python SDKs
- Plugin architecture for tools
- Memory and planning capabilities
- Azure and Microsoft 365 integration
Strengths and tradeoffs
What each tool does well, and the limitations to keep in mind.
Pros
- Code-first approach enables testable, maintainable agent development
- Comprehensive evaluation framework builds trustworthy agents
- Modular design supports scalable multi-agent architectures
- Open source with active community contributions
Cons
- Optimized primarily for Google Cloud ecosystem
- May be overly structured for simple use cases
- Less flexibility for multi-cloud or non-Google deployments
Pros
- Free open-source
- Microsoft-backed
- Multi-language
Cons
- Learning curve
- Microsoft focus
Google ADK or Semantic Kernel — which should you choose?
Choose Google ADK if you wantChoose if you want
Choose Semantic Kernel if you wantChoose if you want
- Enterprise AI on Microsoft stack
- Copilot-style applications
- Integrating AI into .NET applications
- Microsoft 365 automation
- Enterprise workflow orchestration
Compare Google ADK and Semantic Kernel on your own traffic
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