Make vs n8n
Quick Answer
Choose Make if you want a polished, hosted visual automation platform that is approachable for non-technical users and still handles serious multi-step workflows.
Choose n8n if you want open-source flexibility, self-hosting, code nodes, and deeper control over data and infrastructure, and you have the technical comfort to use them.
Both build workflows on a visual canvas, so the concepts transfer between them. Make optimizes for ease and a smooth hosted experience; n8n optimizes for flexibility, control, and ownership.
Best For
| Use case | Better choice | Why |
|---|---|---|
| Non-technical user | Make | More approachable, hosted, less setup |
| Self-hosting and data control | n8n | Runs on your own infrastructure |
| Developer-heavy workflows | n8n | Code nodes and deep flexibility |
| Fast hosted start | Make | No servers to manage |
| Cost control at scale | n8n | Self-hosting can lower per-run costs |
| Custom AI agents and pipelines | n8n | Native AI nodes plus local model support |
| Visual clarity for simple flows | Make | Clean, guided canvas |
What Is Make?
Make is a hosted visual automation platform. You connect apps as modules on a canvas and define how data flows between them, and you can see the entire scenario at a glance. It suits individuals and teams who want capable automation without managing servers, and it includes Make AI Agents that can reason and make decisions inside a scenario while showing their steps.
It works best for people who value a clean, hosted experience and do not need self-hosting or heavy custom code.
What Is n8n?
n8n is a fair-code, source-available workflow automation tool that can be self-hosted or run in the cloud. It is visual like Make, but it lets you drop into code whenever you need to, with JavaScript or Python nodes, custom API calls, and detailed control over data. It is popular with developers and technical teams who want maximum flexibility and the option to keep everything on their own infrastructure.
It works best when workflows get complex, when data must stay in your environment, or when you are building custom AI pipelines with native LLM and agent nodes.
Ease of Use
Make is generally easier for non-technical people. The canvas is guided, the modules are clearly labeled, and you can build a working scenario without touching code or a server.
n8n is approachable for basic flows but expects more as you go deeper. Self-hosting means running and maintaining a server, and its real strengths reward comfort with APIs and a little code. For someone with no technical background, Make is the gentler on-ramp. For a developer, n8n’s extra depth is worth the steeper start.
Visual Workflow Building
Both are visual, and both show the whole flow on a canvas, which helps with understanding and debugging. Make’s canvas is polished and beginner-friendly, guiding you through connections in a way that feels approachable.
n8n’s canvas is capable and flexible, but it leans slightly more technical, surfacing data structures and options that power users appreciate and beginners can find busy. If you want the cleanest visual experience for straightforward flows, Make edges ahead. If you want the canvas plus the ability to open up the internals, n8n gives you both.
Open-Source Control
This is where n8n stands apart. Its source is available, so you can inspect it, extend it, build custom nodes, and run it entirely under your own control. For teams that care about avoiding lock-in, auditing what their automation platform does, or customizing it deeply, that openness is a real advantage.
Make is a closed, hosted product. It is well built and convenient, but you use it as a service rather than something you can host or modify. If open-source control is a requirement, n8n is the clear choice.
AI Automation
Both put AI within reach. Make’s AI Agents can make decisions inside a scenario and show their reasoning on the canvas, and it has native modules for major model providers, so you can add AI steps to a visual workflow and see what the agent decided.
n8n offers native LLM and AI agent nodes, connects to many providers, and can run local models when self-hosted, which suits sensitive data and custom pipelines. Make favors visible, guided AI inside a scenario; n8n favors technical control over how an AI workflow is built and where it runs. Beginners can start with our AI automation tools for beginners guide before building agents.
Webhooks and APIs
Both handle webhooks and APIs, which is what lets them connect to services without a pre-built module. You can trigger scenarios from incoming webhooks and call external APIs in each.
n8n tends to give developers more direct, granular control here, with a flexible HTTP request node and the ability to shape requests and responses in code. Make supports webhooks and HTTP modules well within its visual model. For deep, custom API work, n8n usually feels more natural; for standard webhook triggers inside a clean scenario, Make is comfortable.
Self-Hosting
n8n can be self-hosted on your own infrastructure through its Community edition, keeping automation data in your environment and enabling unlimited executions for the cost of the server and its upkeep. That control appeals to teams with data-residency needs or sensitive information.
Make is hosted only. It removes the burden of running infrastructure, which many teams prefer, but it means your automation data passes through Make’s cloud. If self-hosting is a hard requirement, n8n is the option; if you would rather not manage servers, Make’s hosted model is the simpler path. Either way, keep a human review step before automation touches sensitive records.
Pricing
Make uses hosted, credit-based pricing, where each module action costs a credit, with a free tier to start and paid plans that scale. n8n’s self-hosted Community edition is free to run with unlimited executions, though you pay for the server and maintenance, and its managed Cloud plans are priced around executions.
At small scale, Make’s hosted simplicity is easy to reason about. At high volume, self-hosted n8n can be significantly cheaper if you can manage the infrastructure. Plans and limits change, so check official pricing before deciding.
Best for Non-Technical Users
Make. It is hosted, visual, and approachable, with no servers to manage and a guided canvas that non-technical people can learn without code. For someone who wants capable automation without a technical lift, Make is the easier and safer starting point.
Best for Developers
n8n. Code nodes, generic API access, custom nodes, self-hosting, and open-source control give developers the flexibility and ownership they usually want. Make can still serve developers who prefer a hosted canvas, but n8n is the stronger fit for teams that want to build and control automation deeply.
Which Should You Choose?
Choose Make if you want a hosted, approachable visual tool that non-technical users can run confidently. Choose n8n if you want open-source flexibility, self-hosting, and developer control, and you have the technical comfort to use them. If you are still unsure, start with the tool that solves your most immediate workflow problem; both share a visual model, so skills carry over.
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Frequently Asked Questions
Is n8n harder to use than Make?
For most non-technical users, yes. n8n is more developer-oriented and rewards comfort with data, APIs, and sometimes a little code. Make is also visual but generally more approachable for people without a technical background. If you have no coding comfort at all, Make is usually the gentler start, while n8n gives more power once you climb the curve.
Can you self-host n8n?
Yes, and it is a major reason teams choose it. n8n's Community edition can be self-hosted on your own infrastructure, which gives more control over data and can lower costs at high volume. Make is a hosted cloud platform, so self-hosting is not part of its model. If data residency or self-hosting matters, n8n has the edge.
Which is better for developers?
n8n is usually better for developers and technical teams because of its code nodes, generic API access, and self-hosting option. Make is capable but leans toward visual, no-code users. Developers who want fine-grained control over logic and data frequently prefer n8n, while Make appeals to those who want a polished hosted canvas.
Do Make and n8n both support AI automation?
Yes. Make has AI Agents that make decisions inside a scenario and show their reasoning on the canvas, plus native modules for major AI providers. n8n has native LLM and AI agent nodes, connects to many model providers, and can run local models when self-hosted. Make favors visual clarity, n8n favors technical control over AI pipelines.
Is Make or n8n cheaper?
It depends on volume and whether you self-host. Self-hosted n8n can be very cost-effective at scale but you manage the infrastructure. Make's hosted, credit-based pricing is simpler to start with. Both change plans over time, so check the official websites for current pricing before deciding.
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