n8n vs Dify: The ultimate comparison of workflow automation and AI applications

In the wave of automation tools and AI development platforms, n8n and dify are undoubtedly two open source stars that have attracted much attention. They each occupy a unique position in the field of workflow automation and AI-driven application development, but which tool is more suitable for your needs? This article will deeply compare the core functions, applicable scenarios, advantages and disadvantages of n8n and Dify to help you make a wise choice.

1. Core positioning: Automation vs AI-driven development

n8n: General workflow automation

n8n is a powerful workflow automation tool that allows users to easily connect various applications and APIs through an intuitive node-based interface. Its core goal is to help users automate tedious business processes, such as data synchronization, file backup, marketing automation, etc. Whether it is an individual developer or an enterprise team, n8n can provide a highly flexible solution.

Dify: Rapid AI Application Development

Dify focuses on AI-driven application development , especially low-code platforms based on large language models (LLMs). It aims to simplify the construction of AI workflows, such as intelligent customer service robots, semantic search, or content generation tools. Dify's design philosophy is to enable non-technical users to quickly deploy AI solutions while providing developers with powerful model integration capabilities.

2. Functional comparison: in-depth analysis

n8n: Flexible node architecture

Core features:

• Visual workflow editor that supports triggers, scheduled tasks, and complex logic.• 400+ pre-built integrations covering databases, cloud storage, CRM, social media, and more.• Supports custom JavaScript and HTTP requests, with strong scalability.

AI capabilities:

AI capabilities are available through third-party services such as the OpenAI API, but lack native LLM support.

deploy:

It is completely open source, supports self-hosting, and is suitable for scenarios where data privacy is sensitive.

Example scenario :

Automatically back up your Google Drive files to Dropbox, or schedule marketing emails.

Dify: AI Workflow Experts

Core features:

• Provide Chatflow (conversational scenarios, such as customer service robots) and Workflow (batch processing, such as data analysis).• Native support for multiple LLMs (such as the GPT series), with built-in data preprocessing, context management, and model fine-tuning.• Low-code WYSIWYG prompt editor with real-time debugging, suitable for rapid prototyping.

Traditional Automation:

It has weak functions in traditional tasks such as database operations and file processing.

deploy:

It supports cloud and self-hosting, provides backend-as-a-service API, and simplifies front-end development.

Example scenario:

Build intelligent customer service bots, or automate content generation and semantic search.

3. Ease of use: Which one is more suitable for beginners?

n8n:

• The node-based editor is intuitive, but complex workflows require a certain technical background and the learning curve is slightly steep.• More suitable for developers and technical teams, especially for scenarios that require high customization.

Dify:

• Provides a simplified low-code experience with an interface designed to be friendly to non-technical users.• Built-in real-time preview and log analysis lowers the development threshold and is suitable for quick start.• Powerful team collaboration capabilities, suitable for rapid prototyping across departments.

4. Community and support: ecology and resources

n8n:

• It has a large open source community, rich GitHub resources, and many nodes and templates contributed by the community.• Adopt a “fair code” model that combines open source flexibility with commercial scalability.• Provides enterprise-level support, suitable for large-scale deployment.

Dify:

• The community is relatively new but growing rapidly, and is ranked high on GitHub Trends.• Provides enterprise edition features (such as SOC2 compliance, GPU optimization) suitable for industries that require advanced support.• Documentation and template resources are quickly iterated, suitable for AI developers.

5. Deployment and Scalability

n8n:

• Supports self-hosting and cloud deployment, and is compatible with enterprise-level environments such as Kubernetes.• Pricing is based on the number of workflow executions, with controllable costs, suitable for complex tasks.

Dify:

• Mainly a cloud platform, but supports self-hosting.• Provides API to simplify front-end development, but support for complex nested structures is limited

6. Applicable scenarios: How to choose?

Choose n8n scenario

• Requires highly customized workflow automation.• Involves integration with multiple third-party services (e.g. CRM, cloud storage, social media).• Prioritize self-hosting and data privacy.• Examples: Automated order processing, cross-platform data synchronization.

Select Dify scene

• Quickly build AI-driven applications such as intelligent customer service or content generation tools.• A low-code platform is needed to support non-technical users or rapid prototyping.• Focus on LLM optimization and AI workflows.• Example: Developing semantic search tools, automating data analysis.

Complementary use

In some scenarios, n8n and Dify can be used together:

• Use Dify to build AI core functions (such as intelligent dialogue systems).• Handle external service integration and traditional automation tasks (such as pushing AI-generated content to CRM) with n8n.

7. Summary of advantages and disadvantages

n8

advantage:

• Flexible node-based architecture, suitable for complex automation.• Extensive third-party integration, open source self-hosted.• Strong community support and rich resources.

shortcoming:

• AI capabilities are weak and need to rely on third-party services.• The learning curve is slightly higher, and non-technical users may need training.

Dify

advantage:

• AI development is efficient and low-code experience is friendly.• Native support for LLM, suitable for rapid deployment of AI applications.• Powerful team collaboration and debugging tools.

shortcoming:

• Traditional automation capabilities are weak.• Complex integration scenarios may be limited.

8. Conclusion: Choose the right tool for you

1. If your goal is general automation and complex business processes, n8n is a more flexible and powerful choice.2. If you focus on AI application development, especially rapid prototyping and deployment based on LLM, Dify is an ideal choice.3. For scenarios that require a combination of AI and traditional automation, consider using both together to leverage their respective strengths.