Dify vs Make vs n8n: The Ultimate Workflow Tool Comparison for 2025

In the rapidly evolving landscape of 2025, workflow automation tools have become the cornerstone of enterprise efficiency. Among the myriad options available, Dify, Make, and n8n have emerged as three distinct leaders, each carving out their unique value propositions. This comprehensive analysis will dive deep into their features, use cases, and AI potential to help you make the most informed decision for your automation needs.

Executive Summary: Core Platform Positioning

Dify - The AI-Native Application Development Platform

Dify is an open-source platform specifically designed for AI application development, enabling users to rapidly build LLM-powered intelligent applications through an intuitive drag-and-drop interface. Its core strengths include:

• AI-Native Architecture: Built from the ground up around LLMs and RAG technology
• Visual AI Workflows: Construct complex AI logic through intuitive interfaces
• Multimodal Support: Handle text, images, and structured data simultaneously
• Enterprise-Grade Features: Built-in observability, debugging, and testing utilities

Make - The Enterprise-Grade All-in-One Automation Platform

Make is a powerful visual automation platform with 2000+ app integrations, particularly excelling at complex business process automation. Key characteristics include:

• Operation-Based Pricing: Pay per module execution, ideal for large-scale usage
• Rich Integration Ecosystem: Connect virtually all mainstream business applications
• Enterprise Security: SOC2 Type II compliant with SSO support
• AI-Enhanced Features: 200+ pre-built AI app integrations

n8n - The Developer-Friendly Open Source Automation Tool

n8n is a fair-code workflow automation platform that combines the flexibility of code with the speed of no-code, featuring 400+ integrations and native AI capabilities. Core features:

• Fair-Code Model: Open source with business-friendly licensing
• Self-Hosting Options: Complete control over data and deployment
• Code Integration: Support for JavaScript/Python custom logic
• AI-Native Capabilities: LangChain-based intelligent agent workflows

In-Depth Feature Comparison

Workflow Building Capabilities

AI Integration Capabilities Comparison

Dify's AI Advantages

Dify provides native AI workflow support including multi-step logic, tool integration, knowledge retrieval, and advanced features like parameter extractors and iteration nodes:

• RAG Pipelines: Built-in vector databases and document processing
• Agent Nodes: LLM-driven autonomous decision-making capabilities
• Multi-Model Support: Seamless switching between different AI models
• Real-Time Debugging: Visualize AI reasoning processes

Make's AI Integration

Make enhances automation capabilities through 200+ pre-built AI app integrations, supporting mainstream AI platforms like OpenAI, Anthropic Claude, and Hugging Face:

• Agentic Automation: Intelligent decisions and real-time adjustments
• Pre-Built AI Modules: Out-of-the-box AI functionality
• Data Enhancement: AI-driven customer insight generation
• Content Automation: AI optimization of social media content

n8n's AI Capabilities

n8n provides native AI capabilities based on LangChain framework, supporting complex AI agent system construction including multi-step agents and vector store integration:

• LangChain Integration: Build modular AI applications
• Custom AI Nodes: JavaScript/Python AI functionality extensions
• Human-in-the-Loop: Manual intervention for approval and safety checks
• MCP Server: Seamless integration with external AI systems

Deployment and Scalability

Deployment Options

Dify:

• Cloud hosting service (primary)
• Docker container deployment
• Kubernetes support
• Enterprise private deployment

Make:

• Pure cloud SaaS
• Enterprise-grade infrastructure
• Global CDN support
• 99.9% availability guarantee

n8n:

• Self-hosting first
• n8n Cloud option
• Complete offline deployment
• Flexible infrastructure choices

Scalability Performance

n8n can handle up to 220 workflow executions/second on a single instance, supporting multi-instance deployment in queue mode. Make automatically scales through its cloud infrastructure, while Dify focuses on AI workload optimization.

Integration Ecosystem

Pricing Models Detailed

Dify Pricing Strategy

• Free Plan: Basic AI application development
• Professional Plan: Extended AI capabilities and enterprise features
• Enterprise Plan: Customized AI solutions and professional support

Make Pricing Model

Make charges per operations, where each module execution counts as one operation:

• Free Plan: 1,000 operations/month
• Core Plan: $9/month starting, 10,000 operations
• Pro Plan: $16/month starting, 10,000 operations + advanced features
• Teams Plan: $29/month starting, 10,000 operations + team collaboration
• Enterprise: Custom pricing

n8n Pricing Structure

n8n uses workflow execution billing, where one complete workflow run counts as one execution, even if it includes thousands of task steps:

• Community: Completely free, self-hosted
• Starter: $20/month, 5,000 executions
• Pro: $50/month, 50,000 executions
• Enterprise: Custom pricing, advanced security and support

Real-World Use Case Analysis

Best Scenarios for Dify

1. Intelligent Customer Service Systems

   • Knowledge base-driven Q&A automation
   • Multi-turn conversation management
   • Real-time learning and optimization

2. Content Generation Platforms

   • Marketing copy auto-generation
   • Multi-language content translation
   • Personalized recommendation engines

3. Enterprise Knowledge Management

   • Intelligent document analysis
   • Knowledge graph construction
   • Smart search and recommendations

Make's Typical Applications

1. Sales Automation

   • CRM data synchronization
   • Lead scoring and distribution
   • Automated marketing campaigns

2. Data Integration and ETL

   • Multi-system data sync
   • Automated report generation
   • Business intelligence dashboards

3. Customer Service Optimization

   • Ticket auto-routing
   • Customer feedback analysis
   • SLA monitoring and alerts

n8n's Strength Areas

1. DevOps Automation

   • CI/CD pipeline integration
   • Infrastructure monitoring
   • Automated deployment and rollback

2. Data Science Workflows

   • Model training pipelines
   • Data preprocessing automation
   • Experiment result tracking

3. API Orchestration and Integration

   • Microservice coordination
   • Third-party API aggregation
   • Real-time data processing

AI Potential Assessment: Future Development Trends

Dify's AI Future

Dify continues to enhance its AI workflow capabilities, including parallel branch processing, deep research workflows, and other advanced features:

Technical Roadmap:

• Enhanced multimodal AI processing capabilities
• More intelligent Agent node systems
• Real-time streaming AI processing
• Edge AI deployment support

Expected Breakthroughs:

• Agent collaboration and multi-agent systems
• Automated prompt engineering
• Personalized AI model fine-tuning
• Cross-modal understanding and generation

Make's AI Enhancement

Make is building reusable intelligent agents that can adapt in real-time and work across multiple workflows:

AI Development Direction:

• Intelligent agent management platform
• Pre-built AI module expansion
• Industry-specific AI solutions
• Edge computing AI integration

Market Advantages:

• Massive integration ecosystem empowering AI
• Enterprise-grade AI governance tools
• Industry-vertical AI templates
• Full-stack AI automation solutions

n8n's AI Evolution

n8n focuses on providing developers with the ability to build complex AI agent workflows, constructing modular AI applications based on LangChain framework:

Technical Innovation:

• Native multi-agent orchestration
• Advanced AI workflow debugging
• Adaptive AI model selection
• Decentralized AI networks

Open Source Advantages:

• Community-driven AI node development
• Transparent AI algorithm implementation
• Customizable AI inference engines
• Cross-platform AI standard development

Selection Guide: How to Choose the Right Platform

Choose Dify When:

✅ AI application development is the priority ✅ Need rapid prototype validation ✅ Team includes non-technical members ✅ Value visual debugging of AI workflows ✅ Project is LLM-centric

Choose Make When:

✅ Need extensive third-party integrations ✅ Pursue enterprise-grade reliability and support ✅ Complex business process automation ✅ Large team size requiring collaboration features ✅ Sufficient budget with focus on ROI

Choose n8n When:

✅ Development team has strong technical capabilities ✅ Need complete control over data and deployment ✅ Limited budget but complex requirements ✅ Value open source ecosystem and transparency ✅ Need deep customization and extension

Hybrid Architecture: Best Practices for Combined Usage

Some enterprises adopt a hybrid AI automation architecture where Dify acts as the "Brain" for AI logic and reasoning, while n8n serves as the "Nervous System" connecting enterprise systems and orchestrating workflows.

Recommended Combination Patterns

1. Dify + n8n: AI-native applications + System integration
2. Make + Dify: Enterprise automation + AI enhancement
3. Three-platform Synergy: Division of labor based on specific scenarios

Conclusion and Recommendations

In the 2025 workflow automation landscape, these three platforms each have their unique strengths:

• Dify represents the future direction of AI-native application development, particularly suitable for AI-centric innovation projects
• Make with its mature enterprise-grade functionality and vast integration ecosystem, is the ideal choice for traditional enterprise digital transformation
• n8n with its open-source flexibility and powerful customization capabilities, has become the favorite of technical teams

The key to choosing isn't about which platform is "best," but which is most suitable for your specific needs, team capabilities, and development strategy. As AI technology rapidly evolves, these platforms are continuously advancing, and we may see more feature convergence and innovative breakthroughs in the future.

We recommend taking full advantage of each platform's free trial period before making a final decision, and testing with actual business scenarios to find the workflow automation solution that truly fits your needs.

This article is based on the latest information available as of July 2025. Platform features and pricing may change, so please refer to official sources for the most current information.

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