Why the usual comparison is useless
Almost every comparison you will find lists features: how many integrations each one has, whether there is a visual editor, whether loops are supported. It is accurate and useless, because all three have a visual editor, all three support loops and all three integrate with what 95% of companies use.
What really separates them are three things nobody puts in the table: how they charge, who will maintain this a year from now and where the data lives. Let's go there.
How each one charges, which is what ends up deciding
This is the difference that hurts the most over time.
- Zapier charges per task. Every action a workflow runs counts as a task. A five-step workflow that fires a thousand times a month is five thousand tasks. It is transparent, and it is what makes the bill explode as soon as you automate something with real volume.
- Make charges per operation. Similar in concept, but the quotas are more generous for the same price and the free plan leaves room to experiment. In practice, the same workflow usually costs two to four times less than on Zapier.
- n8n charges per workflow execution, not per step. A twenty-step workflow counts as one execution. And if you host it on your own server, the license does not cap executions: you pay for the server and that is it. For high volume it is by far the cheapest.
Zapier: when yes and when no
Zapier is the one that needs the least explaining. Anyone on your team opens it, connects two tools and has something working in ten minutes. Its integration catalogue is the largest and the more obscure apps are often only here.
It makes sense when there is nobody technical, when the workflows are simple (something happens in A, do something in B) and when volume is low. A form that creates a CRM contact and pings Slack is the perfect case.
It stops making sense as soon as you want real logic: nested conditions, data transformation, iterating over lists. It can be done, but it becomes a chain of steps that is hard to understand and that charges for each of them. And if one day the workflow processes ten thousand records, the bill shows it.
Make: when yes and when no
Make is Zapier for people who have grown tired of Zapier. The editor is a canvas where you see the whole flow, with branches, loops and error handling as first-class citizens. For workflows with logic it is far more comfortable.
It makes sense when someone will maintain it, even if they are not a developer, and when volume is starting to be a problem on Zapier. Also when you need to transform data between systems that do not understand each other.
Its weak point is the learning curve: the editor has its own logic and the first weeks are hard. And it is still a third party's cloud service: your data goes through their servers and you cannot change that.
n8n: when yes and when no
n8n is what we use for almost everything, and it is worth explaining why without selling it as free, because it is not.
It is the only one of the three you can host on your own infrastructure. That solves two problems at once: cost at volume (no execution limits) and privacy (data never leaves your server). For a company handling customer data, medical records or financial information, this is not a preference, it is a requirement.
It is also the one that integrates best with AI models. It has native nodes for OpenAI, Anthropic, Google and local models, conversation memory, agent tools and vector database queries. When we wrote about AI agents for businesses in an earlier article, most of the ones we have built run on n8n.
And when the node you need does not exist, you write JavaScript or Python inside the workflow and move on. That is what makes it the most flexible and also what tells you who should use it.
It stops making sense when nobody will maintain it. Hosting it means a server, backups, updates and keeping an eye on uptime. There is a cloud version managed by n8n that removes that part, priced comparably to Make, but then you lose the advantage of keeping data at home.
The three questions that decide it
Before choosing, answer these. It is almost always enough.
- Will someone maintain the automations a year from now? If the answer is nobody, Zapier. If it is a motivated operations person, Make. If there is a technical profile or a provider in charge, n8n.
- Can the data go through third-party servers? If you handle sensitive data or your sector is regulated, the answer is self-hosted n8n. The other two do not offer that option.
- How many executions per month will there be in six months, not today? Under a thousand, any of them. Between one and twenty thousand, Make or n8n. Beyond that, self-hosted n8n, because the others' price grows with usage and n8n's does not.
What we see in clients
Over time we have seen a pattern repeat. The company starts with Zapier because it is what they know, automates three things, it works, and a year later there are thirty workflows nobody documented and a bill nobody reviews. At that point migrating costs more than starting right would have.
Our recommendation by client type:
Small business with no technical team and few workflows: Zapier. Do not overcomplicate it.
Company with an operations person who wants to automate seriously: Make, plus a month of support so the first workflows are built properly and documented.
Company where automation is part of the product, with AI involved or sensitive data: self-hosted n8n, with someone to operate it. This is where we come in, either setting it up and handing it over or maintaining it as part of a fractional CTO service.
And one last piece of advice that saves money: whichever you choose, document every workflow with what it does, what triggers it and who asked for it. Automations without an owner are the ones that break silently one day.
If you want us to look at it with you
We have built automations on all three and migrated from one to another more times than we would like. That leaves us fairly clear on which fits each case.
Book a thirty-minute call. Tell us what you want to automate, how much volume it has and who will maintain it, and we leave with a concrete recommendation and an estimate of the monthly cost. No strings attached. And if the answer is "stick with Zapier", we will tell you that too.
Frequently asked questions
The version you install yourself is free for internal business use and does not cap executions, but you need a server and someone to maintain it. The cloud version managed by n8n is paid, priced in the same range as Make. In practice none of them is entirely free: you either pay for the service or for the server and the time of whoever looks after it.
n8n, by a wide margin. It has native nodes for the main models, conversation memory, agent tools and vector database queries. Make and Zapier let you call a model, but building an agent that decides and acts is far more awkward and more expensive because of the step count.
There is no automatic import: workflows are rebuilt by hand. What carries over is the knowledge of what each one does, which is why we insist on documentation. A typical migration of twenty or thirty workflows takes two to four weeks if they are documented, and considerably longer if you first have to discover what each one did.
Zapier and Make are US providers that process data on their servers, so you need them listed as data processors and you should check where they host the information. With n8n hosted on your infrastructure, or on a European provider you choose, data stays wherever you decide, which greatly simplifies compliance.
It depends on how many workflows and how complex they are. A first batch of simple automations, on the chosen tool, documented and handed over, is usually a project of a few weeks. If AI agents or integration with internal systems are involved, it falls within the range of our fixed-scope projects. We estimate it with concrete data in a first call.