Head-to-head
Make vs Zapier
The bottom line
The bottom line
Choose
Make if…
- The workflow branches, loops or reshapes data. Make's canvas is built for scenarios that are not a straight line, and Zapier's own limitations name heavy data transformation as a reason to look elsewhere.
- Volume is the cost driver. Make prices in operations rather than tasks, and its entry tier carries an order of magnitude more of them than Zapier's does in our data.
- Somebody on the team enjoys this work. Make is classified as low-code here, and the payoff only arrives if a person is willing to climb the curve.
- You work mostly with webhooks, spreadsheets and databases rather than a long tail of SaaS apps, which is the shape Make's native integrations favour.
- You want to see the whole flow at once. A visual scenario is genuinely easier to debug than a linear step list once there are more than a few steps.
Choose
Zapier if…
- The apps in your stack are the point. The largest integration library is the one advantage no amount of cleverness elsewhere can replace.
- The people building automations are not engineers, and the automation has to keep working after they move on.
- The workflows are simple: something happens here, something should happen there. That describes most automations, and Zapier does them with the least ceremony.
- Trigger reliability matters more than cost per run, because the automation sits in the path of revenue or of a customer waiting for a reply.
- You would rather pay more per task than spend a week learning a canvas, and you accept that heavy flows get expensive, which is Zapier's own stated limitation.
Feature by feature
Feature by feature
| Feature | Make | Zapier |
|---|---|---|
| Pricing model | freemium | freemium |
| Starting price | 9 ✓ | 19.99 |
| Free tier | Yes | Yes |
| Learning curve | low_code | no_code ✓ |
| Rating | 4.5 | 4.9 ✓ |
| Reviews | 0 | 0 |
| Integrations | 3 | 4 ✓ |
| API access | Yes | Yes |
| Mobile app | No | Yes ✓ |
| Multilingual | Yes | Yes |
| Data export | Yes | Yes |
| Team collaboration | Yes | Yes |
| Templates | Yes | Yes |
| AI features | Yes | Yes |
| Support tier | priority ✓ |
Pricing
Pricing, side by side
Our verdict
Our pick: Zapier
The choice between these two is almost always decided by a question that has nothing to do with either product: how unusual is your stack. Zapier's advantage is coverage. It connects the long tail of business software, its triggers are dependable, and it asks almost nothing of the person building the automation, which is why it is the default recommendation for a team with no operations engineer. Make gives you a visual canvas with branching, iteration and real data transformation, at a price per run Zapier does not attempt to match, and it is the better tool the moment a workflow stops being a straight line. The cost is a learning curve Make itself acknowledges, and a shorter list of native apps. Our pick is Zapier for most teams, because most automations are simple and the expensive failure mode is an automation nobody but its author can maintain. Choose Make when volume or complexity is the binding constraint, meaning when you are paying for runs rather than for integrations, or when the flow has to loop, branch and reshape data on the way through.
Last reviewed August 2026
FAQ
FAQ
- Is Make really that much cheaper?
- At the entry tier in our data, yes, and the gap is not marginal: Make's paid entry plan costs less than half of Zapier's and includes far more runs. But the two meter differently, because Zapier counts tasks and Make counts operations, and one multi-step Zap can consume several tasks in a way a single scenario does not. The comparison only becomes real once you model your own monthly volume. Vendor pricing changes often, so check before you commit.
- Which is easier to learn?
- Zapier, clearly, and Make does not dispute it: its own limitations note that it is steeper. Zapier's step-by-step editor maps onto how a non-technical person describes a task out loud. Make's canvas asks you to think in modules, routers and data structures first. That investment pays back on complex work and is wasted on simple work, which is why the honest recommendation depends on the automations you actually need rather than on the tools themselves.
- Can Make connect to everything Zapier can?
- No. Zapier's app library is its central advantage, and Make's own limitations acknowledge fewer native apps. In practice the gap matters most in the long tail: mainstream tools are covered by both, and niche software is where you find only Zapier. Make narrows this with a strong webhook and HTTP module that will reach any service with an API, but that is a workaround requiring somebody comfortable reading API documentation.
- Should I run both?
- Teams do, usually by accident, and it is worth deciding deliberately instead. A defensible split is Zapier for the simple connections everybody owns, and Make for the two or three heavy scenarios one person maintains. The cost is two subscriptions and two places to look when something breaks at three in the morning. If you can consolidate onto one, consolidate, and revisit only when a specific limit bites.
- What happens when a workflow fails?
- Both retry and both log, and the practical difference is how quickly you can see why. Make's visual scenario shows the failing module in context, which shortens debugging on complex flows. Zapier's linear history is easier to scan when the flow is short. Whichever you choose, route a failure notification somewhere a human actually reads, because the most expensive automation failure is always the silent one.
- Can I avoid both by using the automations built into my other tools?
- For a surprising amount of work, yes, and it is the cheapest option nobody costs out. Airtable runs record-triggered automations inside a base, and ClickUp runs them inside the task tracker, so work that begins and ends in one of those tools rarely needs a separate subscription at all. The limit is the boundary of that tool: the moment the workflow has to cross into a second system, you are back to needing a connector, and that is the point at which this comparison starts to matter.