n8nn8n vs Make (Integromat): Which Automation Tool to Choose?
Last updated 2026-03-06
Quick answer
n8n is open source, self hostable, and charges per execution (a 50 step workflow counts as 1 execution). Make is a polished cloud platform that charges per operation (each step in a workflow is a separate operation). If you are technical and want full control, unlimited free executions via self hosting, and the ability to drop into JavaScript or Python, choose n8n. If you want the easiest visual builder with a gentler learning curve and no server management, choose Make.
Feature comparison
| Feature | n8n | make |
|---|---|---|
| Free tier | Community (self hosted): unlimited executions, unlimited workflows, all features, forever free | Free plan: 1,000 operations/month, 2 active scenarios, 5 min scheduling interval |
| Entry paid tier | Starter Cloud $20/mo: 2,500 executions/month, 5 concurrent | Core $10.59/mo: 10,000 operations/month, unlimited scenarios, 1 min scheduling |
| Mid tier | Pro Cloud $50/mo: 10,000 executions/month, 20 concurrent | Pro $18.82/mo: 10,000 operations/month, custom variables, priority execution |
| Enterprise | Custom pricing: SSO, Git environments, external secrets, audit logging, SOC 2 | Custom pricing: SSO, SCIM, OData API, custom roles, SLA guarantee |
| Pricing model | Per execution (a workflow run = 1 execution regardless of steps) | Per operation (each step in a workflow = 1 operation) |
| Self hosting | Yes, via Docker. Free forever with unlimited executions, npm packages, custom nodes | No. Cloud only. |
| Native integrations | 400+ integrations plus HTTP Request node for any API | 1,800+ integrations plus HTTP module for any API |
| Code support | Full JavaScript and Python with Code nodes. Import npm packages on self hosted. | JavaScript only (limited sandbox). No package imports. |
| AI capabilities | Built-in LangChain integration: AI agents, RAG, vector stores, tool calling, 70+ AI nodes | OpenAI and other AI modules available, but no native agent framework |
| Visual builder | Node based canvas with drag and drop. Step by step debugging with pinned data. | Flowchart style canvas with drag and drop. Visual data mapping with dot notation. |
| Error handling | Custom error workflows, automatic retries, execution logging with search | Error handlers per module, break/retry/ignore directives, incomplete execution queue |
| Learning curve | Moderate to steep. Expects familiarity with APIs, JSON, and data structures. | Gentle to moderate. Visual data mapping and guided setup reduce the barrier. |
| Community | 175,000+ GitHub stars, 200,000+ community members, 1,700+ workflow templates | Large community, official Academy with courses, template library, partner ecosystem |
Free tier
n8n
Community (self hosted): unlimited executions, unlimited workflows, all features, forever free
make
Free plan: 1,000 operations/month, 2 active scenarios, 5 min scheduling interval
Entry paid tier
n8n
Starter Cloud $20/mo: 2,500 executions/month, 5 concurrent
make
Core $10.59/mo: 10,000 operations/month, unlimited scenarios, 1 min scheduling
Mid tier
n8n
Pro Cloud $50/mo: 10,000 executions/month, 20 concurrent
make
Pro $18.82/mo: 10,000 operations/month, custom variables, priority execution
Enterprise
n8n
Custom pricing: SSO, Git environments, external secrets, audit logging, SOC 2
make
Custom pricing: SSO, SCIM, OData API, custom roles, SLA guarantee
Pricing model
n8n
Per execution (a workflow run = 1 execution regardless of steps)
make
Per operation (each step in a workflow = 1 operation)
Self hosting
n8n
Yes, via Docker. Free forever with unlimited executions, npm packages, custom nodes
make
No. Cloud only.
Native integrations
n8n
400+ integrations plus HTTP Request node for any API
make
1,800+ integrations plus HTTP module for any API
Code support
n8n
Full JavaScript and Python with Code nodes. Import npm packages on self hosted.
make
JavaScript only (limited sandbox). No package imports.
AI capabilities
n8n
Built-in LangChain integration: AI agents, RAG, vector stores, tool calling, 70+ AI nodes
make
OpenAI and other AI modules available, but no native agent framework
Visual builder
n8n
Node based canvas with drag and drop. Step by step debugging with pinned data.
make
Flowchart style canvas with drag and drop. Visual data mapping with dot notation.
Error handling
n8n
Custom error workflows, automatic retries, execution logging with search
make
Error handlers per module, break/retry/ignore directives, incomplete execution queue
Learning curve
n8n
Moderate to steep. Expects familiarity with APIs, JSON, and data structures.
make
Gentle to moderate. Visual data mapping and guided setup reduce the barrier.
Community
n8n
175,000+ GitHub stars, 200,000+ community members, 1,700+ workflow templates
make
Large community, official Academy with courses, template library, partner ecosystem
Our verdicts
Best for developers
n8nFull code support with JavaScript and Python, npm package imports, custom nodes, CLI access, Git based version control, and self hosting make n8n the natural choice for technical teams.
Best for non-technical users
n8nMake wins this one. Its visual data mapping, gentler learning curve, guided module setup, and 1,800+ native integrations make it more accessible for people without a technical background. (Make is not in our hub yet, but it is the better pick here.)
Best for AI workflows
n8nn8n's native LangChain integration with 70+ AI nodes, agent workflows, RAG pipelines, vector stores, and the ability to use any workflow as a custom AI tool puts it far ahead of Make for AI use cases.
Best for budget-conscious teams
n8nThe self hosted Community Edition is completely free with unlimited executions. Even on the cloud, n8n's per execution pricing is dramatically cheaper for complex workflows: a 50 step workflow costs 1 execution in n8n versus 50 operations in Make.
Best for quick integrations
n8nMake is stronger here with 1,800+ native integrations compared to n8n's 400+. If your main need is connecting common SaaS tools quickly without code, Make has more pre-built modules ready to go. (Make is not in our hub yet.)