This decision is usually made on feature comparisons. The two questions that actually decide it are how cost behaves as volume grows, and who maintains it when it breaks.
The short version
Zapier. Fastest to start, the widest integration catalogue, the friendliest to non technical users. Cost scales with every task, which is fine until it is not.
Make. Visual, cheaper per operation than Zapier, more logic available in the builder. A reasonable middle for teams with real volume and no appetite for infrastructure.
n8n. Available as cloud or self hosted. Self hosting is the point for many teams: the cost stops tracking execution count and the data stays in your infrastructure. In exchange you take on updates, backups and uptime.
The cost curve is the real decision
At low volume, all three are cheap enough that the choice does not matter. Pick the one your team will actually use.
At volume, the curves diverge sharply. Per task pricing is comfortable at hundreds of runs and uncomfortable at hundreds of thousands. This is the point where teams migrate, usually later than they should, and usually under time pressure.
Model it before you commit: take your realistic monthly execution count in twelve months, not today, and price all three.
The maintenance question
Self hosting sounds like a saving and is an operational commitment. The platform documents several installation and update paths, and all of them assume somebody owns the box.
The honest rule: if nobody on your side will own a server, do not self host, whatever the spreadsheet says. An unmaintained automation layer fails silently, which is the worst failure mode available.
Where data lives
For regulated industries, or where customer records cannot leave your infrastructure, this moves from preference to requirement and the decision is made for you.
What does not differ enough to decide on
AI nodes. All three have them now. The hard parts of running AI in production are error handling, cost control and verifying the output, and those live outside the node whichever platform you pick.
Integration counts. Beyond the top hundred connectors, what matters is whether the platform can call an arbitrary HTTP endpoint, and all three can.
A practical way to choose
- Estimate executions per month at twelve months, not today
- Name who maintains it, by person, before choosing
- Check whether your data can legally leave your infrastructure
- Price all three at that volume
- Pick, and write the business logic down somewhere outside the tool
Step five is the one that makes a future migration mechanical instead of archaeological.
The thing that matters more than the choice
Whichever you pick, every flow needs an error route and an alert, because what has no error route fails in silence. That single practice separates automation that can be trusted from automation that everyone quietly works around.