Make vs Zapier vs n8n: an honest comparison

Short answer: Zapier if you need the widest app library and want to move fast. Make if you need more logic per dollar. n8n if you need control, scale, or data sovereignty. And if none of those fit, a custom build is on the table — we’ll tell you when that’s the right call.

No affiliate links here. We don’t resell any of these platforms. We’ve used all three with clients, and we have opinions.

The comparison at a glance

Dimension	Zapier	Make	n8n
Ease of setup	Highest	Moderate	Low (especially self-hosted)
App library	Largest (~7,000+ apps)	Large (~2,000+ apps)	Smaller (+ community nodes)
Logic and branching	Basic	Strong	Most powerful
Pricing model	Per-task	Per-operation	Per-execution or self-hosted
Relative cost at volume	Most expensive	Moderate	Cheapest
Self-hosting	No	No	Yes
Best for	Simple, broad integrations	Power-per-dollar	Control, scale, sensitive data

Zapier: the widest reach, the highest ceiling

What Zapier is actually best at

Zapier has the largest app library of the three. If your business runs on a mix of mainstream SaaS tools — a CRM, a form builder, a project management tool, an email platform — there is a very good chance Zapier connects all of them out of the box, no custom code required.

The setup experience is the smoothest. If you can describe a workflow in plain English (“when a form submission comes in, create a row in my spreadsheet and send me a Slack message”), Zapier can probably implement that in under an hour. For a business owner with no technical background who needs something working today, that matters.

Zapier is also the platform most non-technical staff can actually maintain without a handoff. The interface is linear and explicit. You can hand a Zap off to someone who has never seen it before and they’ll understand what it does.

Where Zapier bites you

Per-task pricing compounds fast. Every time a workflow runs, you spend tasks. Multi-step workflows multiply the cost. A workflow that runs a few hundred times a month feels cheap. The same workflow running ten thousand times a month starts to look like a line item.

The logic layer is also genuinely limited compared to Make or n8n. Conditional branching exists but gets clunky at depth. Data transformation options are narrower. If your workflow has more than three or four decision points, you’ll feel the ceiling.

Zapier works well early. It can become a constraint when your automation needs grow.

Make: more power per dollar

What Make is actually best at

Make’s scenario builder is visual in a way Zapier’s isn’t — you’re drawing a flowchart, not configuring a linear chain. That visual layer makes complex logic more legible once you understand it, and Make’s branching, filtering, and data transformation options are meaningfully stronger than Zapier’s.

The pricing model is also fundamentally different. Make charges per operation (each module that runs), and the per-operation cost is lower than Zapier’s per-task rate at comparable workloads. Once you’re running anything at moderate volume, the difference is material.

For workflows with conditional logic — route this record one way if it meets condition A, another way if it meets condition B, ignore it if it meets condition C — Make handles that natively and cleanly. It also has solid support for iterators, aggregators, and data structure manipulation that makes it genuinely useful for workflows involving arrays, JSON, or non-trivial data shapes.

If we’re starting a new client project and the workflow has meaningful complexity, Make is usually the first platform we reach for.

Where Make bites you

The learning curve is steeper than Zapier’s. The visual builder is powerful, but it takes a few hours to internalize the mental model. Non-technical staff who need to maintain workflows will need more onboarding.

The app library is large but not as deep as Zapier’s. For niche apps or newer SaaS tools, you may hit a gap and end up using an HTTP module to call the API directly — which works, but requires more setup.

n8n: control, scale, and data that stays home

What n8n is actually best at

n8n is open-source and self-hostable. That single fact changes the calculus for two categories of client.

The first is businesses with data sensitivity. Legal, healthcare, financial, government-adjacent — anywhere your compliance posture means you can’t route customer records, case data, or financial information through a third-party SaaS platform. Self-hosted n8n runs on infrastructure you control. The data never leaves your environment.

The second is high-volume workflows where per-operation pricing becomes material. Self-hosted n8n charges for infrastructure, not executions. If you’re running a workflow thousands or tens of thousands of times a month, the cost difference versus Make or Zapier is significant.

n8n also has the most powerful logic layer of the three. JavaScript functions, full-featured code nodes, complex branching, and a flexible data model make it capable of things that would require workarounds or compromise in the other two platforms.

Where n8n bites you

You need someone technical to set it up, and for self-hosted deployments, someone to maintain the infrastructure. That is not a knock on n8n — it’s an honest description of the trade-off. The platform is not designed for non-technical users starting from zero.

The app library is smaller out of the box, though the community node ecosystem is active and growing. Cloud-hosted n8n (n8n.cloud) removes the infrastructure burden but also removes the data sovereignty advantage.

If your team doesn’t have technical staff and you don’t want to hire a consultant to set it up, start with Make.

When none of them is the answer

Platform tools like Zapier, Make, and n8n solve a specific class of problem well: connecting existing SaaS apps with moderate logic in between. They abstract the infrastructure in exchange for some constraints. Most of the time, that’s the right trade.

But not always.

High volume with per-operation economics

If your workflow runs at scale, platform pricing eventually loses to custom infrastructure. The break-even point varies — it depends on your specific workflow, the platform, and your tier. But it exists. When we model out workflows running hundreds of thousands of executions per month, a custom-built pipeline on serverless infrastructure or a dedicated worker often costs less than a platform subscription.

Brittle vendor APIs you can’t control

Platform connectors are built to a vendor’s API as it exists today. When that API changes — rate limits shift, endpoints deprecate, authentication methods update — the connector breaks. If you’re dependent on a connector for a business-critical workflow, you’re at the mercy of both the API vendor and the platform maintaining the connector. A custom integration gives you full control over retry logic, error handling, versioning, and fallback behavior.

Data you can’t send to a third party

Even self-hosted n8n has a control plane that touches their infrastructure. If your data handling requirements mean you need to account for every byte, a custom build on your own infrastructure is the cleaner answer. For some regulated industries, it’s not optional.

When these conditions apply, we’ll tell you. The custom build vs. platform decision tool walks through the criteria in about five minutes and gives you a concrete recommendation.

How to pick one

If you’re making this decision, here’s the shortest version of the framework we use with clients.

Start with Zapier if: your workflow connects mainstream SaaS apps, you need it working this week, and you’re not running it at high volume.

Start with Make if: your workflow has real branching logic or data transformation, you’re cost-conscious about moderate volume, or you need something maintainable by a small technical team.

Start with n8n if: you have a developer on staff, your data can’t leave your infrastructure, or you’re running at high enough volume that per-operation pricing is a constraint.

Consider a custom build if: you’re running at significant scale, you can’t route your data through a third party, or you need reliability guarantees that platform connectors can’t provide.

One more decision factor that doesn’t get mentioned enough: what happens when it breaks at 2 PM on a Friday? Platform tools have support teams and status pages. Custom builds have whoever built them. Make sure that answer is acceptable before you commit.

Not sure which fits your situation?

If you have a specific workflow in mind, the custom build vs. platform tool handles the automation architecture question. If you’re still mapping out which workflows to tackle first, the first AI project post covers how to find the high-ROI work before you pick a platform.

If you’d rather talk through it, the free 30-minute blueprint call is the fastest way to get a straight answer. Bring the workflow you’re trying to automate. We’ll tell you which tool fits — or whether any of them do.