LangGraph vs. Google ADK – UnicMinds

From the world of SDKs, we moved into the world of ADKs. ADKs are frameworks to develop and deploy AI agents. They’re designed to make AI agent development feel simple and create, design agentic architectures and deploy them for a range of tasks from simple to complex nature.

Google ADK is a brand-new, open-source framework built to simplify the end-to-end development of both single and multi-agent systems. 

LangGraph vs Google ADK

To put it simply, think of agent to agent interaction as function calls. LangGraph is highly customizable in the agent to agent interaction architecture and they share data, whereas Google ADK largely passes most of the stuff to the next agent. 

If you’re using Google Cloud tools, then Google essentially offers a plug-and-play model for deployment into its AI infrastructure. The framework also offers LiteLLM integration letting you choose from a wide selection of models from providers like Anthropic, Meta, Mistral AI, AI21 Labs, and more. While the Agent Development Kit (ADK) offers flexibility to work with various tools, it is optimized for seamless integration within the Google Cloud ecosystem, specifically with Gemini models and Vertex AI.

Building Multi-Agent Applications with ADK

Google ADK Documentation for Common Multi-Agent Patterns

Google ADK Agentic Framework

LangChain remains the most coveted name in AI agent development, and LangGraph has elevated it to new levels. 90% of non-tech companies are planning to use LangChain for agent deployment due to its maturity and extensive ecosystem. LangGraph offers battle tested reliability and it has a massive community (80K+ GitHub stars), comprehensive documentation, and proven enterprise adoption. LangGraph introduces visual workflow design that makes complex agent interactions manageable.

LangGraph is highly customizable where you can decide which agent will be the main handler and which other agents will be like the helper agents and how much data is shared and control is maintained. Personally, the other major thing I like about LangGraph is the visual debugging tool. Google ADK still lacks the visual debugging tool.

Other than LangGraph and Google ADK, CrewAI is another startup favorite. CrewAI has emerged as one of the top frameworks alongside LangChain and AutoGen, gaining rapid adoption for its developer-friendly approach and robust multi-agent orchestration.

Clean API design, excellent documentation, and focus on real-world business applications rather than academic use cases. Startups and middle companies have found CrewAI to be an efficient and quick way to deploy agents.

Hope this is useful for a quick overview of agent development framework comparison between Google ADK and LangGraph, thank you.

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