n8n vs Dify
Detailed side-by-side comparison to help you choose the right tool
n8n
🟡Low CodeAI Automation
Source-available workflow automation platform with native AI agent and LangChain nodes, popular for self-hosted AI workflows.
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FreeDify
LLM app platform
Dify is an open-source LLM app development platform that combines a visual workflow builder, RAG pipelines, agent tools, and an LLMOps backbone.
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FreeFeature Comparison
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n8n - Pros & Cons
Pros
- ✓Self-hosted Community edition is free and runs anywhere — no per-task pricing tax
- ✓Native AI Agent node and LangChain blocks let you build real agents on a visual canvas
- ✓MCP Client node integrates n8n into the emerging MCP agent ecosystem
- ✓JavaScript code nodes provide escape hatches for anything the visual editor cannot express
Cons
- ✗Visual editor becomes noisy on workflows with dozens of branches and tool calls
- ✗Debugging long-running agent loops is still painful versus a real code IDE
- ✗Cloud tier execution caps can surprise heavy users — self-hosting is the practical path at scale
- ✗Sustainable Use License is fair-code, not OSI-approved open source, which some procurement teams flag
Dify - Pros & Cons
Pros
- ✓Open-source self-hosted path keeps long-term costs and data residency under your control
- ✓Model-agnostic gateway lets you swap providers without rewriting workflows
- ✓Strong built-in RAG with rerankers, metadata filters, and multiple chunking strategies
- ✓Production-ready observability: traces, prompt versioning, annotations, cost tracking
- ✓Active plugin marketplace with growing MCP-compatible integrations
Cons
- ✗Complex agent logic with many branches is harder to express than in code-first frameworks
- ✗Cloud message credits get expensive fast at production volume — most heavy users self-host
- ✗Plugin ecosystem is smaller than n8n or Zapier; niche integrations often need custom work
- ✗Visual editor learning curve is real for non-technical users despite the no-code framing
- ✗Self-hosting requires Docker, Postgres, Redis, and a vector DB — not a zero-ops deployment
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