Most comparisons of n8n and Make open with a feature table, and the table ends in a tie. For an online store the decision usually turns on something the table barely mentions: what each tool counts as one unit of work, and who ends up looking after the automation once it matters to revenue.
Here is the short version. Make is the better pick when a marketing or operations person will build and own the automations. n8n is the better pick when the flows are long, touch orders or stock, and someone technical is available to keep them running. The rest of this piece explains why, with the arithmetic.
The two platforms meter different things, and everything else follows from that.
Make counts credits, and a credit is spent every time a step in your scenario does something. Its own pricing page says that each module action, such as adding a Google Sheet row or fetching Gmail account data, counts as one credit. Reading, searching, creating, updating, transforming and looping data all cost credits. Routing is free, and so are the error-handling steps.
n8n counts executions. Its documentation, quoted on the n8n pricing page, defines an execution as a single run of the entire workflow, however many steps it has and however much data it handles. A workflow with three steps and a workflow with thirty are the same price per run.
As of 5 October 2026, Make lists a Core plan at $12 a month with 10,000 credits. n8n lists Starter at 20 euros a month, billed annually, with 2,500 executions, and Pro at 50 euros a month with 10,000. Prices move, so check both pages before you budget.
Take a plain order flow. A new order arrives, the customer is looked up in your CRM, stock is checked, the order is written to the ERP, a shipping label is requested, the tracking number is saved back, a confirmation email goes out, and a row is added to a finance sheet. Call it eight steps. This is a made-up flow for the arithmetic, not a client figure.
On Make that order costs about eight credits. The 10,000 credits in Core cover roughly 1,250 orders a month. A store doing 2,500 orders a month would need around 20,000 credits for this one flow, and that is before the abandoned-cart flow, the returns flow, and the nightly stock sync.
On n8n the same order is one execution. The 2,500 executions in Starter cover 2,500 orders, and adding a ninth or tenth step costs nothing extra.
Notice what the example does not say. At low volume the difference is a few euros a month and nobody should choose a platform over it. The gap only becomes a budget line when flows are long, volumes are high, or both. And n8n's model has its own sharp edge: a flow that loops over a large list inside one run is cheap on the meter, but it can still be heavy on the server that runs it.
If the person who will own the automation is not technical, Make is the safer choice. Its builder is visual, its connectors for common apps are polished, and a marketing manager can read a scenario and see what it does. Make is also cloud-only, which means there is no server to patch and no one to blame when it goes down at the weekend. For lead routing, Slack alerts, simple email sequences and spreadsheet syncing, it is a good default, and the credit bill stays small because the flows are short.
I would also pick Make for a store with a few hundred orders a month and no developer on call. The meter does not matter at that size. Fewer things to look after does.
n8n pulls ahead when the flow has real logic in it: retries, branching on stock levels, splitting a multi-item order, reconciling two systems that disagree. According to n8n's own comparison with Make, code steps in JavaScript or Python are available on every plan, whereas Make restricts custom functions to its Enterprise plan. That is a vendor's claim about a competitor, so verify it before you rely on it, but it matches what we see in practice: the awkward last stretch of an integration is almost always custom logic.
We use n8n ourselves. Our own publishing and reporting automations run on it, and for a Berlin art and science school we built an enrollment pipeline on n8n that turns every booking into a linked parent, child and course record across six platforms, with no manual re-entry. That job needed splitting multi-item orders and mapping product codes to course codes. It is the kind of work where per-step pricing would have punished the design.
Then there is self-hosting, which gets sold as "free" and should not be. The Community Edition costs nothing to install, but n8n describes its licence as fair-code, so read the terms before you build a product on top of it. More to the point, a self-hosted instance is infrastructure. Someone has to run the server, apply updates, take backups and notice when it stops. If your team has nobody for that, the managed cloud plans exist for a reason, and the price gap with Make narrows.
Subscription cost is the smaller number. The larger one is what a broken automation costs you. When the flow that writes orders into your ERP fails quietly, you find out when stock counts drift and a customer buys something you do not have. We wrote about the four places Magento ERP integrations break, and almost every one of them is an automation problem, not a platform problem.
So ask three questions before you compare prices. Who will notice when a run fails? Who will fix it, and how fast? And is this flow close enough to money, stock or customer data that failure has a price?
If the honest answers are "nobody technical" and "yes, very close to money", the cheapest platform is not the cheap option. Put the system integration work in proper hands, or pick a tool that matches the skills you actually have.
Choose Make if a non-developer owns the flows, they are short, and volume is modest. Choose n8n if the flows are long or touch orders and stock, volume is growing, and you have someone who can look after it, or a partner who will. If you cannot answer the ownership questions, settle that before you settle the tool.
If you are weighing this for your own store and not sure which side of the line you are on, this is the sort of decision we help with at Encomage. We usually start by mapping which flows touch revenue and who would be on the hook when one fails, and only then pick a platform.
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