Agentic AI Comparison:
Make AI vs n8n
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Introduction
This report compares two popular workflow automation platforms: n8n and Make AI. Both tools offer powerful capabilities for integrating applications and automating business processes, but they have distinct approaches and strengths.
Overview
n8n
n8n is an open-source, self-hostable workflow automation tool that emphasizes flexibility and extensibility. It allows users to create complex workflows connecting various apps and services through a node-based visual interface.
Make AI
Make AI (formerly Integromat) is a cloud-based platform that focuses on ease of use and a wide range of pre-built integrations. It offers AI-powered features to enhance workflow creation and execution.
Metrics Comparison
Autonomy
Make AI: 6
Make AI provides some autonomy in workflow creation and execution, but as a cloud-based solution, users are dependent on Make's infrastructure and cannot self-host.
n8n: 8
n8n offers high autonomy through its self-hosting option, allowing full control over data and infrastructure. Users can extend functionality by creating custom nodes.
n8n offers greater autonomy due to its open-source nature and self-hosting capabilities, while Make AI trades some autonomy for ease of use and managed infrastructure.
Ease of Use
Make AI: 9
Make AI is known for its user-friendly interface, drag-and-drop workflow creation, and AI-assisted features that simplify automation tasks for non-technical users.
n8n: 7
n8n features a visual workflow builder and extensive documentation, but may have a steeper learning curve due to its more technical nature and self-hosting requirements.
Make AI edges out n8n in ease of use, particularly for non-technical users, thanks to its intuitive interface and AI-powered assistance.
Flexibility
Make AI: 8
Make AI offers considerable flexibility with its large number of pre-built integrations and the ability to create custom webhooks and HTTP requests. However, it may be less customizable than n8n at the code level.
n8n: 9
n8n's open-source nature, custom node creation, and ability to run JavaScript code within workflows provide exceptional flexibility for advanced users and developers.
Both platforms are highly flexible, but n8n's open-source nature and deeper customization options give it a slight edge for advanced users and specific use cases.
Cost
Make AI: 7
Make AI provides a free plan with limited operations, with paid plans starting at $9/month. Pricing is based on the number of operations, which can become costly for complex or high-volume workflows.
n8n: 8
n8n offers a free, self-hosted option for unlimited users and workflows. Cloud-hosted plans start at €20/month, with pricing based on active workflows rather than operations.
n8n may be more cost-effective for organizations with the resources to self-host or those with complex workflows, while Make AI's pricing model suits lighter users but can scale up quickly with usage.
Popularity
Make AI: 8
Make AI (formerly Integromat) has a large user base across various industries and is well-known in the no-code/low-code community. Its recent AI features have further increased its appeal.
n8n: 7
n8n has gained significant traction in the developer community, with over 30,000 GitHub stars. However, it may be less known among non-technical users.
Make AI appears to have broader popularity across different user types, while n8n has strong support within the developer community. Both platforms are growing in recognition.
Conclusions
Both n8n and Make AI are powerful workflow automation platforms with distinct strengths. n8n excels in flexibility, customization, and cost-effectiveness for self-hosted deployments, making it ideal for technical users and organizations with specific infrastructure requirements. Make AI stands out for its ease of use, extensive pre-built integrations, and AI-powered features, catering to a wide range of users, especially those seeking a user-friendly, cloud-based solution. The choice between the two will depend on factors such as technical expertise, hosting preferences, specific integration needs, and budget considerations.