Make vs Zapier 2026: an in-depth comparison for small businesses

Both tools have a free plan, and paid plans are based on how much work gets done, but they count it differently. Zapier counts tasks: each successful action step is one task, while the trigger and filters generally are not counted. Make counts credits (previously called operations): every module run uses a credit, including the trigger that checks for new data.

In practice, a simple two-step workflow costs about the same in both. As a scenario grows longer, with conditions, loops over rows and data processing, Make usually comes out cheaper, because its plans give you considerably more units for the same price. But Make credits can disappear unexpectedly: if a scenario checks for new records every 15 minutes, it uses credits even when there is nothing new.

My advice is to count your real volume before choosing: how many times a month the workflow runs and how many steps each run has. Then compare with the current prices on both vendors’ sites, because plans and rates change several times a year. The prices in the table above are indicative.

Zapier is still the easiest start. A workflow is built as a top-to-bottom list: “when this happens, do that.” If you are a manager or office administrator who wants to connect a form to a spreadsheet yourself, you can usually do it in Zapier in one evening.

Make’s editor is visual: modules sit on a canvas, connected by lines, and branches (routers) are visible at a glance. That is very handy when the logic gets complex, but at first you need to understand a few concepts: how data flows between modules, what iterators and aggregators are, and how error handling works. It usually clicks after a few tries, but the first scenario takes longer than in Zapier.

Both let you add code: Zapier has Code by Zapier (JavaScript and Python), and Make has an HTTP module for any API plus functions for processing data. If nobody on your team wants to dig in, what matters more than the tool is who will maintain the workflows when something stops.

The gap here is smaller than the integration counts suggest. Zapier has the larger library of ready-made apps, Make a smaller one, but in both you usually will not find ready connectors for Lithuanian systems such as Rivilė or B1 (local accounting software), Montonio (a Baltic payment provider) or SAF-T reporting tools. In those cases you connect directly through the system’s API or a webhook.

This is where Make is often more convenient: the HTTP module is available on every plan, and requests and responses are easy to lay out visually. Zapier has Webhooks by Zapier and API request actions for this, but they are available only on paid plans. Either way, someone has to read the Lithuanian system’s API documentation, which is why clients usually leave this part to me.

One more point is where data lives. Make lets you choose an EU data center when you create your account, while Zapier’s infrastructure is mainly in the US. If customer personal data passes through your workflows, check both vendors’ data processing agreements and record this in your GDPR documentation.

Take an illustrative case: a small online store in Vilnius with about 300 orders a month. The owner wants each order to land in a Google Sheets file, each customer to get a personal email, and an invoice to be created in the accounting software. On top of that, the owner wants a daily summary by email.

In Zapier this would be a multi-step workflow: several actions per order, so a thousand or more tasks a month. Because the accounting software has no ready connector, you would need a webhook or API step, which means a paid plan. In Make the same scenario would use a similar or slightly higher number of credits, but Make’s plans include more units for the same price, so the monthly bill would usually be lower.

For a case like this I would recommend Make, unless the team already uses Zapier heavily and has dozens of working workflows there. If you expect orders to grow several times over, or you want the data to stay on your own server, it is worth looking at n8n too.

It also matters what happens when you hit the monthly limit. Each tool has its own rules: some plans let you buy extra units, while on others workflows pause until the next month. If the store’s sales are seasonal, for example much busier before Christmas, I would check what happens in the peak month before picking a plan.

There is no automatic transfer between these tools; workflows are rebuilt from scratch. So the first thing I do is list every running workflow: what triggers it, what data it passes and where it ends. Often it turns out that some workflows are no longer used, and a few others can be merged into one.

Then I run the new scenarios in parallel with the old ones and compare the results for a few days. Only once I am sure the data matches do I switch the old ones off. Do not forget the account connections: every app has to be connected again in the new tool.

For a small setup with a handful of workflows, switching usually takes a few days. If you have dozens, move in stages, starting with the ones that burn the most tasks or credits.