n8n vs Zapier vs Make: an honest comparison
Every n8n vs Zapier vs Make comparison you read is written by someone with a preference, and this one is no exception — we build mostly on n8n, and we say why below. What follows first, though, is the factual part: how the three platforms differ in hosting, pricing shape, connectors, and code, so you can judge fit against your own situation.
What kind of products are these?
All three are workflow automation platforms: they watch for a trigger — a form submission, a new row, an incoming webhook in the W3C sense of one system notifying another over HTTP — and then run a sequence of steps across your other tools. The differences are in where they run, how they charge, and how far you can bend them.
How do the hosting models differ?
Zapier and Make are software-as-a-service only: your workflows and the data passing through them run on the vendor's infrastructure. n8n is source-available and self-hostable — you can run it on your own server or private cloud, so workflow data never leaves infrastructure you control, or use n8n's hosted cloud if you prefer not to operate a server. For businesses with data-residency or confidentiality constraints, this is often the deciding difference before any feature comparison starts.
How does the pricing shape differ?
We deliberately quote no dollar amounts — they change too often to print. What is stable is the unit each vendor charges by. Zapier prices per task: each action a workflow performs consumes one. Make prices per operation: each module call counts. n8n's cloud pricing is per execution: one workflow run counts once, however many steps it contains, and a self-hosted instance has no per-run platform fee at all. For long, many-step workflows at volume, that unit difference compounds dramatically, so model your own volumes before comparing tiers.
| Dimension | n8n | Zapier | Make |
|---|---|---|---|
| Hosting | Self-hostable (source-available) or vendor cloud | SaaS only | SaaS only |
| Pricing unit | Per execution (none when self-hosted) | Per task | Per operation |
| Connector breadth | Large, plus a generic HTTP node for anything with an API | Largest catalogue of pre-built app integrations | Large, with strong visual data-mapping tools |
| Code steps | Full JavaScript or Python nodes anywhere in a flow | Limited code steps within plan limits | Limited scripting; logic mostly via visual functions |
| Best fit | Custom logic, AI steps, volume, data residency | Non-technical teams connecting mainstream apps fast | Visual builders wanting more power than Zapier |
Connector breadth versus flexibility
Zapier's catalogue of pre-built integrations is the largest, and for connecting mainstream apps with no technical help it remains the path of least resistance. Make sits between the two: a big catalogue plus a visual mapper that handles branching and arrays better than Zapier's linear model. n8n's catalogue is smaller but its generic HTTP request node and full code steps mean anything with an API is reachable — the question shifts from "is there a connector?" to "is there an API?".
Where we stand, honestly
We build most client work on n8n, for three reasons: code steps make AI-heavy workflows practical, per-execution pricing behaves well at volume, and self-hosting answers the data questions that stop projects in regulated businesses. That is a fit for the kind of workflow automation we deliver, not a verdict on the other two — when a client's needs are simple and their team is non-technical, we say so. Our n8n consulting page covers what a build on that platform involves, Make.com consulting covers the same ground for teams already committed to Make, and our guide to what automation actually costs explains why platform fees are rarely the biggest line anyway.
If you have decided Zapier is the right platform and want expert help building or optimizing Zaps, our Zapier automation consulting covers that engagement specifically. If this comparison has convinced you that Make is the better fit for the workflows you already run, the Zapier to Make.com migration service page maps every Zap building block onto its Make equivalent and sets out how the cutover is sequenced. Microsoft Power Automate is deliberately absent from this comparison; if your business already lives in Microsoft 365, our separate guide to n8n vs Power Automate for small business weighs that pair on its own terms.
Common questions when choosing between the three
Is one of the three platforms simply the best?
No. They optimise for different things. Zapier optimises for reach and ease, Make for visual power at low cost of entry, n8n for control, code, and self-hosting. The right choice depends on who will maintain the workflows, where your data is allowed to live, and how much custom logic the processes need.
Why does the pricing unit matter more than the price?
Because the unit determines how cost scales with your workload. A per-task model charges for every action a workflow performs, a per-operation model for every module call, and a per-execution model once per run regardless of internal steps. The same workflow at the same volume can land in very different places under each scheme, so model your own volumes rather than comparing headline tiers.
Can we switch platforms later if we outgrow one?
Yes, but workflows do not port automatically — a migration is a rebuild, informed by logic that is already proven. This is a reason to document workflows as processes, not just as configurations, and to be more deliberate about platform choice when you expect high volume or heavy custom logic, because those are the workflows that are costliest to rebuild.
Does self-hosting n8n mean it is free to run?
No. Self-hosting removes the per-execution platform fee but adds a server to pay for and maintain, updates to apply, and backups to manage. For many businesses that trade is well worth it for the data-residency control alone; for teams with no technical ownership, n8n's hosted cloud offering or a managed setup is the realistic path.
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