LangChain vs LangGraph: 4 Key Differences and When to Use Each

LangChain is structured as a linear, stateless pipeline, ideal for predictable, forward-moving tasks like standard RAG or summarization. LangGraph, an extension of LangChain, is designed as a stateful graph, naturally handling loops and complex control flows for agentic systems. Key differences include LangGraph's ability to manage a persistent state, natively support human-in-the-loop interruptions, and use checkpointers to resume failed workflows instead of restarting them. LangChain is best for applications understood as a simple pipeline, while LangGraph excels in systems that require statefulness, complex routing, and resilience.