Dify
TypeScript · NOASSERTION
Dify is an open-source LLM application development platform with a visual agent orchestration interface, supporting workflows, knowledge bases, and multiple models.
platformworkflowragtypescript
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Overview
Dify vs n8n: two paths to AI workflow automation
Dify (150k+ stars) is an AI-native app builder with built-in RAG, agent, and workflow primitives. n8n (198k+ stars) is a general-purpose workflow automation platform with hundreds of system integrations that has been adding AI capabilities. We compare positioning, integrations, AI depth, learning curve, and typical users.
Projects Compared
n8n
TypeScript · NOASSERTION
n8n is a powerful workflow automation platform with native AI agent nodes, enabling multi-step agent workflow orchestration and hundreds of external service integrations.
workflowautomationai-agentintegrationtypescript
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Feature Comparison
| Best for | Dify | n8n |
|---|---|---|
| Product positioning | AI-native app builder: from zero to a \"document upload + Q&A + tool use + Agent\" application, with every AI component treated as a first-class citizen. | General-purpose workflow automation: hundreds of system integrations (Slack, GitHub, Salesforce, MySQL, etc.), with AI added recently as an AI Agent node. |
| Integration ecosystem | LLM-centric: OpenAI, Anthropic, Mistral, self-hosted Ollama, Qwen, DeepSeek, plus vector stores (Qdrant, Weaviate, Milvus). Limited SaaS coverage. | Business-systems-centric: Google Workspace, Microsoft 365, Slack, Notion, Airtable, databases, APIs, webhooks. Covers nearly every enterprise SaaS. |
| AI capability depth | RAG, agent, and workflow orchestration are core: built-in knowledge base, document parsing, agent ReAct loops, visual prompt editor, production monitoring. | The AI Agent node is newer but improving fast; most AI work happens in code nodes that call LLM APIs in JS or Python — flexible but few AI-specific abstractions. |
| Learning curve | Dify Studio is a drag-and-drop editor; you can ship a first LLM app in 5 minutes. AI concepts are friendly to non-developers. | n8n is also visual-node based, but hundreds of nodes plus complex expressions (JSON / JMESPath) raise the bar for non-engineers. The AI Agent node is approachable on its own. |
| Best fit | Teams building an AI-first app (customer support, knowledge base, agent) where the LLM is the core capability; they do not need to wire 200 internal SaaS together. | Teams wiring many business systems into end-to-end automation, with AI as one step in a larger workflow; the workflow is about business orchestration, not AI apps. |
GitHub Stats
| Metric | Dify | n8n |
|---|---|---|
| Stars | 152.6k | 200.9k |
| Forks | 24.1k | 60.2k |
| Language | TypeScript | TypeScript |
| License | NOASSERTION | NOASSERTION |
| Last commit | August 16, 2026 | August 17, 2026 |
Which one should you choose?
Choose based on your primary workflow, language ecosystem, and integration needs. Review each project's documentation and recent GitHub activity before adopting it in production.
Frequently asked questions
Can Dify and n8n be used together?
Yes. A common pattern is Dify for the AI layer (RAG, agent) and n8n for external system orchestration, with n8n calling Dify as an HTTP service via the HTTP Request node. This layered setup is common in enterprise AI projects.
Do I need to write code in Dify?
Not for basic flows. Dify Studio is a visual editor with prompt templates that covers about 80% of common cases. When you need customization, you can add Python function nodes or call external services via webhooks. Code demand is much lower than n8n.
How does n8n handle AI workflows?
n8n ships an AI Agent node (built on LangChain) where you configure an LLM provider plus tools. For other AI work, you call LLM APIs through OpenAI or Anthropic nodes. Complex logic falls back to JavaScript or Python code nodes.
Which is cheaper?
Both have self-hosted editions (free plus your own ops). n8n self-hosted is under the Sustainable Use License, which limits use to internal business purposes or non-commercial; Dify is under a modified Apache 2.0 with commercial-use restrictions (multi-tenant SaaS without authorization and tampering with the LOGO). Cloud pricing is usage-tiered for both, so neither is expensive for small projects.