Google ADK vs LangGraph: Agent Frameworks Comparison

Google's Agent Development Kit (ADK) is a flexible and modular framework launched in 2024 for developing and deploying AI agents using a code-first approach. The ADK was designed to make agent development feel more like traditional software development, enabling developers to create, deploy, and orchestrate agentic architectures ranging from simple tasks to complex multi-agent workflows. Available for both Python and TypeScript, ADK emphasizes writing clean, testable, and maintainable code rather than relying heavily on prompt engineering.

The framework's modular design enables developers to build specialized agents and compose them into hierarchical, scalable systems. ADK is not just a wrapper around language models but a comprehensive ecosystem for agent composition, workflow orchestration, behavior evaluation, and production deployment. The framework includes robust evaluation capabilities that help developers build trustworthy agents with clear feedback loops. TypeScript's type system makes data contracts between agents clear and robust, enhancing reliability in production environments.

While ADK offers deployment-agnostic capabilities that work with various hosting options, it is optimized for the Google Cloud ecosystem, particularly with Gemini models and Vertex AI. The open-source nature of ADK allows community contributions and evolution based on real-world usage. Developers appreciate ADK's structured approach, comprehensive evaluation framework, and software engineering principles, though teams working outside the Google ecosystem may find alternatives like Genkit more flexible for their needs.

LangGraph is LangChain's graph-based orchestration framework for building stateful, multi-step AI agents. Unlike linear chains, LangGraph models agent workflows as directed graphs with nodes (functions or LLM calls) and edges (conditional routing), enabling cycles, branching, parallel execution, and durable state across long-running interactions.

Together, LangChain and LangGraph have 90M monthly downloads and power production applications at Uber, JPMorgan, BlackRock, and Cisco. LangGraph 1.0 (released 2026) added enterprise certifications, durable execution with checkpointing, time-travel debugging, and human-in-the-loop interrupts. LangChain 1.0 now uses LangGraph under the hood — start with the simple LangChain API and drop down to LangGraph for advanced control when needed.

LangGraph is fully MIT-licensed open-source and free. LangSmith (the observability and eval companion) and LangGraph Platform (managed deployment) are paid SaaS offerings on top. Positioned as the production-control framework for teams that need reliability, observability, and durability — the most enterprise-ready open-source agent framework in 2026.