Zapier Alternatives: An Honest Look at Make and n8n

A ten-step automation that runs 10,000 times a month produces a four-figure dollar bill on Zapier. The same flow, at the same volume, fits inside about 60 euros on n8n. Both move the same data and produce the same result. What separates them is how the invoice gets calculated.

Most searches for Zapier alternatives start at a specific moment: the monthly bill arrives, and it has grown in proportion to the number of steps inside your automations rather than the number of automations you built. This guide compares the three platforms on pricing logic, learning curve, and the practical constraints that show up once real business data starts flowing through them.

The question we are answering is narrower than "which one is best". It is: which one makes sense at your volume? If you have not yet decided which process to automate, our process automation roadmap is the better starting point; this article assumes the need is already defined.

Why do these three price the same work so differently?

All three bill on usage, but they count different units. Zapier counts every action after the trigger as one task. Make counts every module run inside a scenario as one operation. n8n counts one complete run of a workflow as a single execution, no matter how many steps that workflow contains.

In practice this means every step you add to a workflow shows up in your Zapier and Make bill on every single run. On n8n it does not. Take a three-step flow to ten steps and your Zapier cost roughly triples while your n8n cost stays flat.

The reverse holds too. For a two-step flow that runs two hundred times a month, standing up n8n is wasted effort. Zapier's free tier covers it and setup takes ten minutes.

As step count grows, Zapier and Make get linearly more expensive while n8n does not. The decision point sits where those curves cross, and no feature comparison table will tell you where that is.

What do the 2026 plans actually cost?

As of August 2026, the entry and mid-tier plans land in roughly these bands. Annual billing is meaningfully cheaper than monthly, and all three change prices often enough that you should check the official pages before committing.

• Zapier: the free tier allows 100 tasks a month and only two-step Zaps. Professional starts around $20 per month on annual billing and closer to $30 monthly, scaling up in tiers as your task allowance grows. Team plans open around $70.
• Make: the free tier gives 1,000 operations a month. Core lands somewhere between $9 and $16 for 10,000 operations, Pro slightly above that, Teams around $30. Per dollar spent, Make delivers noticeably more operations than Zapier delivers tasks.
• n8n: cloud Starter runs about 24 euros for 2,500 executions, Pro about 60 euros for 10,000. The self-hosted community edition carries no licence fee and no execution cap, which moves the cost onto your server instead.

Laying those allowances side by side and comparing 10,000 to 10,000 is the single most common mistake in this decision. A workflow that does identical work consumes a different number of units on each platform. The only number worth comparing is your own monthly consumption.

What does one real workflow cost on each platform?

Here is a concrete flow we build often: an order arrives from a sales channel, the customer is looked up in the CRM, created if missing, registered with the shipping provider, sent a notification message, and logged to a spreadsheet. Six actions after the trigger.

Assume 3,000 orders a month. On Zapier that is 18,000 tasks, which sits in the upper tiers of Professional and pushes the monthly cost into three figures. On Make it is 18,000 operations, so the 10,000 package falls short and you move up a band, landing somewhere in the $20 to $30 range. On n8n it is 3,000 executions, which overshoots cloud Starter and puts you on Pro at roughly 60 euros.

Notice what happened: at this volume n8n is not the cheapest option. Make is. That result rarely appears in automation content, because n8n's cloud tiers jump at fixed thresholds and mid-volume workloads land awkwardly between them.

Now scale up. Take the same flow to ten steps and 10,000 runs a month. Zapier sees 90,000 tasks, Make sees 100,000 operations, n8n still sees 10,000 executions. The first two climb into the hundreds of dollars while n8n holds at its Pro tier, or at the price of a server if you host it yourself.

That crossover is the whole decision. A few workflows with many steps running frequently favours n8n by a wide margin. Many simple workflows running occasionally favours Zapier, where setup speed is worth more than the price gap.

Is n8n really free?

Free as in licence fee, yes. Free as in total cost, no. The self-hosted community edition costs nothing to run and imposes no execution limit, but somebody has to install it, patch it, back it up, monitor it, and fix it when it breaks at an inconvenient hour. That time never shows up on an invoice; it shows up in your team's calendar.

The infrastructure itself is cheap. A small VPS runs $5 to $7 a month and comfortably handles a modest workload. The real question is whether anyone on your team can run Docker, read logs, and bring a stalled workflow back up. If the answer is no, the free platform plus outsourced maintenance can easily cost more than Zapier would have.

One licensing note worth flagging: n8n is not distributed under a conventional permissive open-source licence. You can use it without limit for your own business, but repackaging it and reselling it as a service is restricted. If you plan to embed it inside a commercial product, read the licence text on n8n's own site before you build. That is not something to settle from a blog post.

For a sense of what people actually build on it, we walked through five real n8n automation scenarios in a separate piece.

Where does your data actually live?

All three platforms are hosted services billed in dollars or euros, which raises three separate issues for any business outside the United States: currency exposure, data residency, and integration coverage for regional tools.

On currency, a $30 monthly subscription can drift significantly in local terms over a year. Annual prepayment looks attractive but locks in a rate for twelve months, which is its own kind of exposure. Budget against the upper band of the local-currency equivalent rather than the headline dollar figure.

Data residency matters more. When you run Zapier or Make, your records pass through their infrastructure, which usually means crossing a border. Self-hosted n8n keeps the data on a server you control, in a jurisdiction you choose. Under most data protection regimes that is a genuine advantage, not a marketing point.

But there is a caveat almost every comparison skips: self-hosting alone does not make you compliant. If any step in your workflow sends data to a language model API hosted elsewhere, that data has left your jurisdiction regardless of where the automation server sits. Evaluate compliance by tracing the full path your data travels, not by checking where the platform is installed.

On regional integrations, set expectations correctly. Local marketplaces, accounting packages and ERP systems rarely have prebuilt blocks on any of these platforms. You connect them with an HTTP request and an API key, which works everywhere. The difference is that on Zapier and Make each of those calls consumes a billable unit, while on n8n it does not.

Where do AI agents fit in 2026?

All three now let you put a language model step inside a workflow, but the depth varies. n8n leads here, with a dedicated agent node, persistent memory across runs, sandboxed code execution, and the ability to reach into your own systems. Zapier leans on agents that can act across its very large app directory, plus a copilot that builds Zaps from a plain-language description. Make offers a conversational scenario builder, with its agent capabilities still maturing.

Do not let that ranking drive the decision on its own. Most teams reaching for their first automation need a reliable chain of rules that runs correctly every time. Agent architecture becomes relevant much later, and adopting it early tends to add failure modes rather than capability.

How hard is it to switch platforms later?

There is no automated migration path. Each platform stores workflows in its own internal format and no reliable converter moves them between vendors. Switching means rebuilding by hand, which is why the second choice deserves more scrutiny than the first.

The time sink is not redrawing the logic. It is reauthorising connections: signing into every app again, regranting permissions, regenerating API keys. Webhook addresses change, so the upstream systems calling them need updating too. Miss one and the flow fails quietly, and you usually learn about it from a customer complaint rather than an alert.

As a rough estimate, a simple two or three step flow takes half an hour to rebuild, while a complex one with branching and error handling takes half a day. For a company running fifteen automations, that is a week of work.

The safe way to migrate is to run both platforms in parallel for a while. Build the new flow, leave the old one running, compare the outputs for a week, then switch off the original. You pay two subscriptions during that week, which is trivial next to the cost of orders disappearing silently.

Quick answers by profile

Compressed into a single line: low volume with no technical staff points to Zapier, mid volume with a tight budget points to Make, high volume or strict data requirements points to n8n. The profiles below unpack that.

• A few hundred runs a month, two or three steps, no developer: Zapier. The free tier probably covers it and you finish the same day.
• A few thousand runs a month, moderately complex flows, cost-sensitive: Make. It delivers the most throughput per dollar in this band.
• Many-step flows running frequently, someone who can manage a server: n8n. Self-hosted, the cost stops tracking your volume.
• Healthcare, legal, finance, or anywhere data sensitivity is high: n8n on your own infrastructure. The argument here is control over the data path, and price is secondary.

Five misconceptions worth clearing up

• "Zapier is expensive." At low volume with few steps it is both the cheapest and the fastest option. Cost becomes a problem only when volume and step count rise together.
• "n8n is free." The licence is. The server, the maintenance and the incident response are not.
• "Zapier has 8,000 integrations, so it wins." A typical small business connects five to fifteen apps. Total catalogue size tells you nothing; coverage of your specific stack tells you everything.
• "I compared the plans and 10,000 is 10,000." It is not. The same workflow consumes a different number of units on each platform.
• "Self-hosting solves compliance." A single outbound call to an external API inside your workflow undoes that assumption.

What should you do?

• Calculate your consumption first. Multiply the number of steps in your workflow by how many times it runs each month. That one multiplication tells you which band you are in.
• Build the first workflow on a free tier. Whichever platform you lean toward, run it before you pay. Real consumption almost never matches the estimate.
• Be honest about in-house technical capacity. Choosing self-hosted n8n without anyone to run the server produces delay, not savings.
• Map the data path. Write down which country each step sends data to. That sheet of paper is where the compliance conversation begins.
• Assume migration will be manual. Since there is no clean export between platforms, treat this decision as one you will live with for a while.

Choosing an automation platform looks like a product preference and behaves like an arithmetic problem. Any comparison made without knowing your own step count and run frequency gets corrected a few months later by an unexpected invoice. Do the multiplication first; picking the platform after that takes about five minutes.