n8n vs Dify

Detailed side-by-side comparison to help you choose the right tool

n8n

🟡Low Code

Automation & Workflows

Open-source workflow automation platform with 500+ integrations, visual builder, and native AI agent support for human-supervised AI workflows.

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Starting Price

Free

Dify

🟡Low Code

Automation & Workflows

Dify is an open-source platform for building AI applications that combines visual workflow design, model management, and knowledge base integration in one tool.

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Starting Price

Free

Feature Comparison

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Featuren8nDify
CategoryAutomation & WorkflowsAutomation & Workflows
Pricing Plans4 tiers4 tiers
Starting PriceFreeFree
Key Features
  • Workflow Runtime
  • Tool and API Connectivity
  • State and Context Handling
  • Workflow Runtime
  • Tool and API Connectivity
  • State and Context Handling

n8n - Pros & Cons

Pros

  • Strong visual interface makes complex AI workflows accessible to non-developers
  • Self-hosting options provide complete data control and privacy
  • Native MCP support enables seamless integration with modern AI platforms
  • Built-in monitoring and debugging tools specifically designed for AI workflows
  • Over 175k GitHub stars indicate strong community adoption and trust
  • Comprehensive security features including SOC2 compliance for enterprise use

Cons

  • Pricing structure based on executions can become expensive for high-volume automations
  • Learning curve exists for building complex multi-step AI agent workflows
  • Self-hosted deployments require technical expertise for setup and maintenance
  • Documentation for AI-specific features may be less comprehensive than traditional automation

Dify - Pros & Cons

Pros

  • Most comprehensive open-source LLMOps platform combining all AI development needs
  • Production-grade RAG pipeline with advanced document processing and chunking
  • Complete self-hosting option with no enterprise feature paywalls
  • Visual interface accessible to non-developers while maintaining technical depth
  • Built-in quality monitoring and evaluation systems for production applications

Cons

  • Docker deployment complexity requires DevOps knowledge and significant resources
  • Platform approach limits flexibility for highly customized agent architectures
  • Visual workflow builder becomes unwieldy for very complex multi-step processes
  • Smaller plugin ecosystem compared to established automation platforms

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🔒 Security & Compliance Comparison

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Security Featuren8nDify
SOC2✅ Yes
GDPR✅ Yes
HIPAA
SSO✅ Yes✅ Yes
Self-Hosted🔀 Hybrid✅ Yes
On-Prem✅ Yes✅ Yes
RBAC✅ Yes✅ Yes
Audit Log✅ Yes✅ Yes
Open Source✅ Yes✅ Yes
API Key Auth✅ Yes✅ Yes
Encryption at Rest✅ Yes✅ Yes
Encryption in Transit✅ Yes✅ Yes
Data ResidencyUS, EU
Data Retentionconfigurableconfigurable
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