We have entered the world of ADK from the world of SDK. ADK is a framework for developing and deploying AI agents. They are designed to make AI agent development simple and create, design, and deploy agent architectures to perform a range of tasks from simple to complex.
Google ADK is a new open source framework designed to simplify end-to-end development of single-agent and multi-agent systems.
LangGraph and Google ADK
In short, think of agent-to-agent interactions as function calls. LangGraph is highly customizable in its inter-agent interaction architecture, and they share data, whereas Google ADK largely passes most of it on to the next agent.
If you use Google Cloud tools, Google essentially provides a plug-and-play model for deployment into its AI infrastructure. The framework also offers LiteLLM integration, allowing you to choose from a variety of models from providers such as Anthropic, Meta, Mistral AI, AI21 Labs, and more. While the Agent Development Kit (ADK) provides the flexibility to work with a variety of tools, it is optimized for seamless integration within the Google Cloud ecosystem, specifically with Gemini models and Vertex AI.
Build multi-agent applications using ADK
Google ADK documentation for common multi-agent modes
Google ADK proxy framework
LangChain remains the most coveted name in AI agent development, and LangGraph takes it to the next level. Due to Langlian’s maturity and extensive ecosystem, 90% of non-tech companies plan to use Langlian for agent deployment. LangGraph delivers proven reliability with a large community (80K+ GitHub stars), comprehensive documentation, and proven enterprise adoption. LangGraph introduces visual workflow design to make complex agent interactions manageable.
LangGraph is highly customizable, you can decide which agent will be the primary handler, which other agents will be secondary agents, and how much data is shared and how much control is maintained. Personally, another major feature I like about LangGraph is the visual debugging tools. Google ADK still lacks visual debugging tools.
Besides LangGraph and Google ADK, CrewAI is another startup favorite. CrewAI has become one of the top frameworks along with LangChain and AutoGen, gaining rapid adoption for its developer-friendly approach and powerful multi-agent orchestration.
Clean API design, excellent documentation, and focus on real-world business applications rather than academic use cases. Startups and mid-sized companies find CrewAI an efficient and fast way to deploy agents.
Hope this helps give a quick overview of the proxy development framework comparison between Google ADK and LangGraph, thanks.
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