account_treePlatform Comparison

n8n vs Zapier vs Make

Three workflow automation platforms, compared by a team that builds production systems on all of them.

The short answer

Choose Zapier if a non-technical team member needs to own automations and your volumes are modest. Choose Make if you want strong visual branching at a meaningfully lower per-operation cost and can handle a steeper learning curve. Choose n8n — self-hosted — if you run high volume, need data to stay in a specific jurisdiction, or want workflows that call real code without fighting the platform.

The decision is rarely about features, because all three will do most of what you ask. It is about who maintains the workflows, what happens to your bill as volume grows, and whether your data is allowed to sit on someone else's infrastructure.

Compared on what changes the decision

Every one of these platforms connects to your CRM and your inbox. These are the dimensions where they genuinely diverge.

n8n, Zapier and Make compared across pricing model, self-hosting, data residency, app catalogue, custom code support, branching, and day-to-day ownership.
	n8n	Zapier	Make
Pricing model	Per workflow execution on cloud; unlimited on self-hosted infrastructure you pay for.	Per task — every single step in every run counts. Predictable when small, punishing at volume.	Per operation, materially cheaper per unit than Zapier's tasks for the same work.
Self-hosting	Yes. Source-available and designed for it — data never leaves your infrastructure.	No. Cloud only.	No. Cloud only, though an EU data-centre region is available.
Data residency	Wherever you host it. The strongest answer for strict GDPR or data-sovereignty requirements.	US-centric infrastructure; residency controls are limited.	EU region selectable at account level.
App catalogue	Large and growing, plus a generic HTTP node that reaches any REST API.	The largest by a wide margin. If an obscure SaaS tool has an integration anywhere, it is here.	Broad, between the other two.
Custom code	JavaScript and Python nodes as first-class citizens. Effectively no ceiling.	Code steps exist but are constrained; the platform fights you past a point.	Custom functions and solid data mapping, short of a full runtime.
Branching & iteration	Full graph — branches, merges, loops, sub-workflows.	Linear by default. Paths add branching, but complex logic gets unwieldy.	Strong visual branching, routers, and iterators. The best of the three for non-developers.
Who runs it day to day	Needs someone technical, especially self-hosted. Usually a partner or an internal developer.	A non-technical operations person can genuinely own it.	An ops person who enjoys logic puzzles can own it.

The pricing model matters more than the price

Zapier charges per task. Every step in every run is billable. A five-step workflow running a thousand times a month is five thousand tasks, not a thousand. This is the single most common reason teams outgrow Zapier, and it arrives suddenly — the workflow that was fine at pilot volume becomes the largest line on the invoice once it is actually used.

Make charges per operation on a similar principle, but the per-unit cost is low enough that the same growth curve bites considerably later.

Self-hosted n8n decouples cost from volume entirely. You pay for a server. Whether it runs ten thousand or ten million executions changes nothing on the invoice. The honest caveat: you now own the server, and someone has to patch it, monitor it, and restore it when it breaks.

Where the platform stops and engineering starts

Every automation platform has a boundary past which you are no longer configuring, you are building software. Knowing where that line sits saves you from discovering it mid-project.

We build past that line regularly — for example, a resilient data-extraction pipeline pulling structured product and pricing data from heavily-protected retail sites, running on Python and Playwright with proxy rotation and scheduled jobs. No point-and-click platform does that, and attempting it inside one produces something fragile that fails quietly.

The useful pattern is a hybrid: keep the orchestration, scheduling, and notification layer in the automation platform where it is visible and editable, and push genuinely hard work out to purpose-built services the platform calls. n8n supports this most naturally, because calling your own code is a first-class operation rather than an escape hatch.

See how that pipeline was builtarrow_forward

For UK and EU teams specifically

If personal data flows through your workflows and you answer to a DPO, data residency stops being a preference. Self-hosted n8n in an EU or UK region is the cleanest position to defend: you name the jurisdiction, and no additional processor is in the chain to paper over with an agreement.

Make's EU region is a reasonable middle ground when self-hosting is not practical. Zapier is the hardest of the three to justify under scrutiny — not because it is careless, but because its US-centric infrastructure and thin residency controls give you less to point at.

Whichever you pick, the platform is one processor among several. Your DPA coverage across every tool the workflow touches is what actually gets audited.

Automation Platforms: Common Questions

Self-hosted n8n, and it is not close — you pay for a server rather than per execution, so cost stops tracking volume entirely. The catch is that the server, upgrades, monitoring, and backups become your responsibility, and that operational overhead is a real cost even though it does not appear on an invoice. Between the two cloud platforms, Make's per-operation pricing is consistently cheaper than Zapier's per-task pricing for equivalent work. Zapier's premium buys the largest app catalogue and the shallowest learning curve.

Not under an OSI-approved licence. n8n uses a fair-code model — the source is available and you can self-host it freely for internal business use, but the licence restricts offering it as a competing hosted service. For the overwhelming majority of businesses self-hosting it to run their own automations, this distinction has no practical effect. It matters if you intend to resell n8n-as-a-service, which requires a commercial arrangement.

Self-hosted n8n gives the cleanest answer, because you choose the jurisdiction your data is processed in and no third-party processor touches it. Make offers an EU data-centre region, which is sufficient for many organisations. Zapier's US-centric infrastructure and limited residency controls make it the hardest of the three to justify when personal data is flowing through workflows and your DPO is asking specific questions. That said, platform choice is only part of compliance — your processing agreements and retention configuration matter as much as where the server sits.

This is the question that separates a demo from production, and it is worth asking before you choose. All three surface run history and errors. The practical differences: n8n gives you full error-handling workflows, retries, and — self-hosted — your own logs and alerting wired into whatever you already monitor with. Make has solid error handlers and incomplete-execution recovery. Zapier will email you about the failure, which is fine for low-stakes automations and genuinely not fine when the failed workflow was billing a customer.

Yes, and it is a reasonable path — prove the workflow is worth having on the platform with the lowest setup cost, then rebuild the ones that survive where they are cheaper and more robust to run. Nothing ports automatically; a migration means rebuilding each workflow. That is less painful than it sounds, because by then you know exactly what the workflow should do, which is the part that actually takes the time.

Want the decision made properly?

Book a free audit. We will map your actual workflows and volumes against all three, and tell you which one fits — including when the answer is the cheapest one.

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