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LangGraph vs n8n

Side-by-side comparison · AI Agents & Automation

At a glance

DimensionLangGraphn8n
PricingFree open-source libraries; LangGraph Platform is a separate managed offering with its own paid tiers - verify current pricing on the official pageFree self-hosted community edition; managed cloud plans start at a modest monthly tier and scale with executions - verify current pricing on the official page
Free planYesYes
Rating★★★★☆★★★★★
Best forproduction agents, long-running workflows, complex branching logic and research systemstechnical teams, self-hosted automation, ai agent workflows and internal tooling
CategoryAI Agents & AutomationAI Agents & Automation

LangGraph - strengths & limits

Strengths

  • Fine control over branching, retries and recovery
  • Checkpointing makes long agent runs survivable
  • Works with many model providers and existing LangChain tools

Watch out for

  • More boilerplate than higher-level agent frameworks
  • Concept-heavy: state, reducers and graphs take time to learn
  • Documentation and APIs have moved quickly between versions

n8n - strengths & limits

Strengths

  • Self-hosting keeps sensitive data inside your own infrastructure
  • AI agents and ordinary automation live in one workflow
  • Code steps prevent the visual editor from becoming a dead end

Watch out for

  • Self-hosting means you own upgrades and uptime
  • Complex workflows need real engineering discipline
  • The learning curve is steeper than simpler no-code tools

Which should you choose?

If your priority is production agents, long-running workflows, complex branching logic and research systems, LangGraph is the stronger pick. If instead you care more about technical teams, self-hosted automation, ai agent workflows and internal tooling, go with n8n. For most people, trying both on a free tier is the fastest way to decide - they serve the same AI Agents & Automation space but differ in workflow and output style.

FAQ

Which is better, LangGraph or n8n?

It depends on your task. LangGraph leads on production agents, long-running workflows, complex branching logic and research systems; n8n is better when you need technical teams, self-hosted automation, ai agent workflows and internal tooling. Try both free tiers.

Can I use LangGraph and n8n together?

Yes - many users keep one as the daily driver and the other for specific tasks where it is stronger.