The short answer
No technical people and low volume, take Zapier. More logic for less money and someone who can handle it, take Make. High volume or data that must stay on your own servers, look at n8n first, because you can host it yourself. For most small and medium businesses Make is the best starting point.
Where the difference actually sits
Not in what they can do, because that overlaps heavily. The difference is how they charge. Zapier charges per task: every successful step in a scenario costs. Make charges in credits: an ordinary step costs one credit, a step with AI can cost more. For a comparable amount you get considerably more of them. n8n charges per workflow execution, regardless of how many steps it has.
That sounds like a detail until you do the maths. A ten-step workflow running ten thousand times a month costs a hundred thousand tasks on Zapier and ten thousand executions on n8n. At high volume that is a multiple.
| Zapier | Make | n8n | |
|---|---|---|---|
| Charges per | Task, so per step | Credit, one per ordinary step | Workflow execution |
| Entry price | Around 20 dollars per month | Around 9 dollars per month for 10,000 credits | Around 20 dollars per month, or free when self-hosted |
| Self-hosting | No | No | Yes, and then without a per-execution tariff |
| Technical level | Low | Medium | High, or someone who maintains it |
| Strongest point | Most connectors and easiest to learn | A lot of logic for little money | Volume and data under your own control |
When to pick which
Zapier
No technical team, low volume, and you want it to simply work. More expensive per action, but you are done in an afternoon.
Make
Someone on the team dares to build a scenario. More logic, branching and filters for considerably less money. For most small and medium businesses the wisest starting point.
n8n
High volume, or data that has to stay on your own infrastructure for legal reasons. Self-hosting is free, but someone has to maintain it.
When none of the three
These tools move data between systems according to rules you define. They judge nothing. As soon as a step asks for a judgement (is this invoice correct, is this file complete, is this reply good enough) you need a model alongside, and with it an approval step and a stop rule for exceptions.
And sometimes the answer is simpler: if your existing software can already do the step, use that feature. Building a connector to do what your package does out of the box is waste. See which processes are suitable.
Frequently asked questions
Which one is cheapest?
At low volumes the difference is small and convenience weighs more than price. At high volumes self-hosted n8n is almost always cheapest, followed by Make. Calculate with your own number of cases per month, not with the entry tariff.
Can I switch later?
Yes, but you rebuild the scenarios. They are not interchangeable. So choose on your expected volume a year from now, not on that of the first month.
Do I need a developer for this?
Not for Zapier, it helps for Make, and for self-hosted n8n you need someone who maintains the server and runs updates. That maintenance is the hidden cost of n8n.
Do these tools automate the thinking as well?
No. They move and transform data according to fixed rules. For steps that ask for a judgement you connect a language model, with an employee approving the outcome.
About the author
I am Joost, AI specialist and founder of Tamboer AI. I have worked with AI daily since 2022. I tested and developed applications at one of the largest banks in the Netherlands and now build AI workflows for smaller businesses, with a person who checks every outcome. More about me.
