All three platforms connect the same few hundred apps and can move data between them on a trigger. The comparison that matters is not which has more integrations — it is which one you will still be happy with at ten times your current volume.
The short version
| Zapier | Make | n8n | |
|---|---|---|---|
| Best at | Speed to first working automation | Visual branching logic | Volume, code, self-hosting |
| Pricing model | Per task (each step counts) | Per operation (cheaper per step) | Per execution, or free self-hosted |
| Branching / loops | Limited, paid tiers | Strong | Strong |
| Custom code | JS/Python snippets | Limited | Full — any npm package when self-hosted |
| Self-host | No | No | Yes |
| Ops burden | None | None | Real — you run it |
| Breaks down at | Multi-step cost, complex logic | Very high volume | When nobody owns the infrastructure |
Zapier: buy speed, pay for it
Zapier's advantage is that a non-technical person can build a working two-step automation in ten minutes, and it will run reliably without anyone thinking about it again. That is worth real money and the platform charges accordingly.
The problem is the pricing unit. Every step consumes a task, so a five-step workflow burns five tasks per run. A workflow processing 2,000 records a month costs 10,000 tasks — and the cost curve gets steep quickly. Teams routinely discover this after they have built twenty workflows and migration is painful.
Make: the middle ground
Make (formerly Integromat) gives you a genuine visual canvas — branching, iterators, aggregators, error handlers as first-class objects — at meaningfully better economics than Zapier for the same work. For a workflow with real conditional logic that still needs to be readable by a non-developer, it is usually the best of the three.
Its limits show up in two places. Complex scenarios become visually unmanageable — a canvas with sixty modules is harder to reason about than sixty lines of code. And at high volume the operation count still adds up, just more slowly than Zapier's.
n8n: power, and a server to look after
n8n's distinguishing feature is that you can self-host it. That takes per-execution pricing off the table entirely and lets you run volume that would be economically absurd on either hosted competitor. It also lets you drop into real JavaScript inside a node, with access to npm packages — which means the workflow can do things the other two structurally cannot.
The cost is honest ops work: a server, updates, backups, monitoring, and someone who owns all of it. Teams that adopt n8n to save on subscription fees and then do not staff the maintenance end up in exactly the orphaning failure mode — a critical automation running on a VPS nobody has logged into since it was set up.
How to actually choose
Four questions, in order
Step 1: How many operations per month, realistically, in a year?
Under ~5,000: any of them, choose on comfort. 5,000–100,000: Make, or n8n cloud. Above 100,000: self-hosted n8n or custom code.
Step 2: Who maintains it?
If the answer is a non-developer, that rules out self-hosted n8n regardless of every other consideration.
Step 3: Does the logic fit on a canvas?
If describing the workflow needs more than a few branches and a loop, the visual tools stop being an advantage and start being a constraint.
Step 4: What does leaving cost?
None of the three export to anything the others can import. Keep the business logic documented in plain language outside the tool so a migration is a rebuild, not an archaeology project.
When the answer is none of them
There is a threshold past which a no-code platform is the more expensive option — in money, in reliability, and in the time spent fighting the tool's model of the world. Signs you have crossed it:
- The workflow has more than ~30 nodes and no one can explain it from the canvas.
- You are writing substantial code inside code nodes anyway.
- Platform costs exceed what a developer would charge to build and host the equivalent.
- You need real version control, code review, staged environments or automated tests.
- Latency matters and the platform's queueing adds seconds you cannot afford.
A small service on a serverless platform handling the same job costs a few euros a month, is version-controlled, and can be tested. The trade is that it needs a developer to change it — which is the right trade once the logic is complex enough that a non-developer should not be changing it anyway.
Frequently asked questions
Is n8n cheaper than Zapier?
Per execution, dramatically — self-hosted n8n has no per-task fee at all, so the marginal cost of volume is near zero. Total cost is closer than it looks once you include hosting, updates, monitoring and the staff time to own the instance. For a team without technical operations capacity, Zapier is often genuinely cheaper all-in despite the higher invoice.
Can I migrate workflows between Zapier, Make and n8n?
Not automatically. There is no common export format and each platform models triggers, iteration and error handling differently, so migration means rebuilding each workflow by hand. This is the strongest argument for documenting what each automation does in plain language outside the tool — that document is what makes a future migration a day of work rather than a month.
Which platform is best for AI agent workflows?
n8n has the most developed native tooling for LLM chains, vector stores and agent loops, and self-hosting keeps data in your own environment — which often decides it for anything touching customer records. Make and Zapier both call AI APIs perfectly well for simpler single-shot tasks like classification or drafting.
Do I need a developer to use these tools?
Not for the first few workflows on Zapier or Make — that is precisely what they are built for. You need one when workflows start touching money, when failures need real error handling and monitoring, or when you self-host. The common failure pattern is a business becoming dependent on twenty non-technical-built automations with no logging, no owner and no documentation.