The real question isn't "which is better", it's "which is for you"
Make and n8n do, broadly, the same thing: they connect your apps and let a flow handle the repetitive work for you. That's why asking "which is better" leads nowhere: both are good and nobody wins the feature comparison in a landslide. The useful question is another one: which fits your case, your team and the way you operate. This guide is about that — the three or four axes that actually decide — not a table with a hundred green boxes.
Before comparing tools, it helps to be clear on the step before: what processes to automate with AI and why. The tool is the "with what"; the "what" and the "what for" come first. Choosing Make or n8n before knowing what you're going to automate is buying the toolbox before knowing whether you're building a shelf or a house.
The axis that decides almost everything: where the flow lives and who's in control
Here's the big difference, the one that orders almost all the others. Make is a closed cloud: it's a proprietary service, hosted by them, that you log into with your account. You build the flow in their visual editor and they make sure it runs. No server of yours, nothing to install. n8n is the opposite by design: its code is open (fair-code model, not exactly classic open source) and it's built for you to host it yourself, on your server, your cloud or your own machine. They also have a managed version, but self-hosting is its DNA.
Translated into a business decision: the question under "Make or n8n" is usually "where do I want my data to live and who do I want in control?". If your flows touch personal data, sensitive information or something your security committee wants hosted inside your perimeter, n8n's self-hosting stops being a technical whim and becomes the argument. If what you want is no servers, nothing to maintain and someone else answering for uptime, Make's cloud is exactly that.
The other axis: how they bill you (and why that changes at scale)
The two bill differently, and that difference — which looks like accounting — decides the real cost when volume grows. Make charges per operation: every step a flow runs counts. A three-step flow spends three; one with loops, retries and error-handling branches, many more. It's cheap and transparent when flows are short, and it balloons when they get complex. n8n charges per execution (on its paid tier): one full run of the flow counts as one, whether it has five steps or fifty. And if you self-host, the software cost disappears and you only pay for the server.
The practical consequence: for simple flows and moderate volume, Make's per-operation model works out well and doesn't force you to maintain anything. For long flows, with many steps, or high volume, n8n's per-execution model — or self-hosting outright — usually comes out quite a bit cheaper by year's end. The classic mistake is looking only at the entry price: almost everyone starts on the cheap plan and discovers the real cost when the flow they threw together multiplies. Putting this into the numbers is part of calculating the ROI of automation before you sign, not after.
The technical ceiling: how far the mouse gets you
Both are visual: you drag blocks, connect them and the flow runs without writing a line. The difference shows up at the edge. n8n lets you drop in code — JavaScript or Python — inside any node, so when the pre-built block falls short, you drop to code on that specific step without leaving the tool. Make is more block-based: it covers a huge range of cases with its catalog, but when you hit odd logic, you have to solve it with more modules, workarounds, or by stepping out to another tool.
This connects with something the automate without coding guide already tells: no-code has a ceiling, and the ceiling shows up in the edge case. Make is more "pure no-code" and so it's faster to start for a business person. n8n is more "no-code with stairs to the basement": it asks for a slightly more technical profile, but it doesn't leave you stranded the day the flow needs something that doesn't fit in a block. If your team has no one technical and you don't want to depend on anyone, that nuance carries weight.
| Decision axis | Make | n8n |
|---|---|---|
| Where it lives | Proprietary cloud (they host it) | Self-hosting or managed cloud |
| Data control / GDPR | Inside their infrastructure | You can keep it in yours |
| How it charges | Per operation (each step counts) | Per execution, or free if you self-host |
| Technical ceiling | Blocks; odd logic is costly | Code nodes (JS/Python) when needed |
| Who runs it well | Business profile, fast start | Slightly technical profile, control and cost at scale |
The factor almost nobody looks at: who maintains it
Choosing a tool is half the decision. The other half is who takes care of it the day after. Make removes the infrastructure maintenance — no server to patch — but not the flow's: someone has to watch that it keeps deciding well and fix the edge cases that show up with use. Self-hosted n8n gives you all the control and all the hidden cost: the server, the updates and the flow are yours, and "yours" means someone with a name on your team.
That's why the real choice isn't "Make or n8n", it's "Make or n8n, and who answers for this in production". An automation with no owner degrades in silence regardless of the tool — the maintenance of automations guide covers it in detail. And connecting either one to your CRM, your ERP or your email opens the can of worms of integrating AI with your systems, which is where flows break when a system changes on its own.
So, which do I pick?
The honest version: pick Make if you want to start now, have no servers, your team is more business than systems, and your flows are of reasonable complexity. Pick n8n if data control is a requirement (GDPR, regulated sector, security committee), if you have or can have someone technical nearby, or if you foresee volume and long flows where the per-operation cost will hurt. In between there's a pile of cases that work equally well with either; there, the one your team will actually use wins, not the one that wins the table.
And there's a third answer that's sometimes the right one: the tool isn't what matters. Plenty of serious systems start in Make or Zapier to validate the idea and then move to n8n or to code when they scale. Choosing well today isn't marrying forever; it's not painting yourself into a corner that costs a full rebuild to get out of.