Short answer: Pick Zapier for the fastest setup and simple, low-volume automations. Pick Make for visual, mid-complexity workflows with branching. Pick n8n if you need complex logic, high volume, custom code, or your data has to stay on your own servers — it’s the cheapest at scale and the only one you can self-host. But treat all three as the easy on-ramp: they’re low-code tools for starting fast; robust, adaptable automation you own eventually moves into real code. The pricing model matters more than the sticker price: Zapier bills per task, Make per operation, n8n per workflow run.

I’m a full-stack engineer who builds automation for a living, and I use all three where they fit. Here’s the honest framing up front: these are low-code tools — the easy way to start. Which one is right depends on your volume, complexity, and how sensitive your data is. Here’s how they compare on the things that actually change the decision.

The comparison at a glance

Dimension	n8n	Make	Zapier
Hosting	Self-host or cloud	Cloud only	Cloud only
Pricing basis	Per workflow execution (steps are free)	Per operation (each module counts)	Per task (each action counts)
Cost at scale	Lowest — free when self-hosted	Medium	Highest
Time to first automation	Slowest	Medium	Fastest
Branching & complex logic	Best	Good	Limited
Custom code	Full JavaScript & Python nodes	Limited functions	Code steps (paid plans)
App integrations	Many + call any REST API	Many	Most (largest catalog)
AI / LLM nodes	Native, extensive	Growing	Growing
Data residency (DSGVO)	Data stays on your infra when self-hosted	US cloud	US cloud
Best for	Complex, high-volume, privacy-sensitive	Visual mid-complexity	Quick simple connects

The one thing most comparisons get wrong: the pricing model

Sticker prices change every year, so don’t anchor on them. What doesn’t change is what each tool charges for, and that’s what decides your bill at scale:

Zapier charges per task. A five-step “Zap” that runs 1,000 times a month costs you 5,000 tasks. Volume gets expensive fast.
Make charges per operation. Similar idea, but usually cheaper per unit and more generous, so mid-complexity flows cost less than the Zapier equivalent.
n8n charges per execution. One run of a workflow is one execution no matter how many steps it has. A 40-step workflow costs the same as a 3-step one. Self-host it and executions are effectively unlimited.

If you run a handful of automations a few hundred times a month, all three are cheap and the price gap barely matters. If you run high-volume, multi-step workflows, the per-task model is the one that hurts.

When Zapier is the right call

Zapier wins on speed and breadth. It has the largest app catalog and the gentlest learning curve, so a non-technical person can connect two tools in an afternoon.

Choose Zapier when your automations are simple (“when a form is submitted, add a row and send a Slack message”), your volume is low, and you have no developer time to spend. See common automation mistakes before you build your first one.

When Make is the right call

Make sits in the middle. Its visual canvas handles branching, loops, and error handling that Zapier struggles with, and its operation-based pricing is friendlier for flows with several steps.

Choose Make when you want a visual builder, your workflows have real logic (conditions, iterations, multiple paths), and you’re fine staying on a hosted cloud.

When n8n is the right call

n8n is where I spend most of my time, and it’s the one I recommend for DACH companies with growing volume or data-residency requirements.

Self-hosting means your customer data never leaves your infrastructure — which matters under the DSGVO and for anyone in a regulated industry.
Per-execution pricing (or unlimited when self-hosted) keeps cost flat as workflows grow more complex.
Code nodes and native AI let you build things the no-code-only tools can’t: custom parsing, LLM steps, calling any API.

The trade-off is the steepest learning curve of the three. That’s exactly the gap I fill — I build and document the workflows, then hand them to your team. See integrations & APIs or watch the live demos run on real documents.

A quick decision guide

Data must stay in the EU / on your servers? → n8n (self-hosted). No debate.
High volume, multi-step workflows? → n8n or Make; avoid per-task billing.
Simple connects, low volume, no dev time? → Zapier.
Want a visual builder with real branching? → Make.
Need custom code or AI logic? → n8n.

Prices and free tiers shift constantly — check each vendor’s current pricing page before you commit. The pricing basis above is the part that rarely changes and the part that decides your cost at scale.

Low-code is the on-ramp, not the destination

Here’s the part most tool comparisons skip: all three are low-code tools — the easy way to start. That’s genuinely valuable. You get a working automation in days, cheaply, without a project.

But “easy to wire up” isn’t the same as durable, adaptable, or yours. As a workflow becomes load-bearing — more volume, more edge cases, tighter coupling to your own systems — a low-code canvas starts to fight you. That’s the point where a full-stack engineer builds it properly: real code, your own APIs, running on infrastructure you control and can extend, not rented from a SaaS you can’t change.

So the honest sequence is: start on low-code (usually self-hosted n8n, so you own it from day one), then move the load-bearing parts into code you own as they matter. The tool is the on-ramp. Owning and understanding your automation is the destination — the difference between wiring tools together and engineering a system.

Where I’d start

Most of my clients start on self-hosted n8n — owned from day one, with a flat cost curve — then we move the load-bearing pieces into code as they grow. You get the fast start and something you own. If you want a second opinion on where that line sits for your workflows, book a free 20-minute call and we’ll map it to your actual processes.

n8n vs Make vs Zapier: Which Automation Tool for Your Business (2026)