Google ADK vs LangChain
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.
LangChain is the most widely adopted framework for building LLM-powered applications and AI agents. It provides abstractions for chains, agents, tools, memory, and retrieval that make it easy to compose complex AI systems. LangGraph, its agent orchestration layer, enables building stateful, multi-actor workflows with human-in-the-loop capabilities. LangSmith provides tracing, evaluation, and monitoring. The LangChain ecosystem is the largest in the AI application development space.
Key features
Core capabilities each platform advertises.
- LangChain Expression Language (LCEL)
- LangGraph for stateful multi-agent workflows
- 1000+ integrations
- LangSmith observability companion
- Python and JavaScript SDKs
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
- Largest ecosystem and community in AI application development
- Comprehensive abstractions for chains, agents, tools, and memory
- LangSmith provides production-grade tracing and evaluation
- LangGraph enables complex stateful multi-actor agent workflows
- Extensive integrations with LLM providers, vector stores, and tools
Cons
- Steep learning curve for advanced configurations and LangGraph
- High total cost of ownership for complex deployments
- Rapid API changes can break existing implementations
- Trace pricing can escalate quickly at scale ($2.50-$5.00 per 1K traces)
Google ADK or LangChain — which should you choose?
Choose Google ADK if you wantChoose if you want
Choose LangChain if you wantChoose if you want
- Building RAG applications
- Multi-agent orchestration with LangGraph
- Tool-using conversational agents
- Document processing pipelines
- Complex chain-of-thought workflows
Compare Google ADK and LangChain on your own traffic
Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 500+ models through one gateway.
