n8n vs Make vs Zapier: Workflow Automation for AI Workloads

Why this matters

Every team stitching together a content pipeline or a multi-step agent ends up choosing one of these three, usually by accident: a colleague found one, got it running in an afternoon, and it calcified.

They get grouped because they look identical in a demo: a canvas of boxes, a list of popular apps, a monthly invoice. Underneath they are different products for different buyers, and the differences show up in week one.

n8n is a workflow runtime you can run yourself, with a code escape hatch at every node and definitions stored as JSON. Make is a hosted visual builder priced per operation, built around branching. Zapier is a hosted service with the broadest catalogue.

The decision that matters is not feature-by-feature. It is whether your flow needs code, needs self-hosting, or needs to be understood by a non-engineer. Pricing follows from that, because self-hosting moves the bill onto your own infrastructure.

What I compared

Self-hosting feasibility — whether you can run it yourself, and what the licence permits
Code extension — how much you can do when the node library runs out
Billing unit — how a run is counted, and which flow shapes inflate it
Error handling and retries — what happens when step nine of twenty fails overnight
Version control — whether workflow definitions can live in git
Long-flow reliability — timeouts, memory behaviour, history retention
Ecosystem — app catalogue size versus depth of the community

The comparison table

Dimension	n8n	Make	Zapier
Deployment	Self-hostable (source-available licence) or cloud	Hosted only	Hosted only
Code escape hatch	JavaScript and Python code nodes, custom nodes, HTTP requests	Inline JavaScript in some modules, custom apps via the API	Python and Node code steps, developer platform
Billing unit on hosted plans	Executions (workflow runs)	Operations (one per module)	Tasks (one per app action)
Cost driver to watch	Executions fanning out into many node calls	Branching and iteration multiplying module runs	Multi-path flows, where each branch still bills
Retry control	Per-node retry with attempts and wait interval, plus error workflows	Module-level retry and error handlers that resume or break	Limited built-in retry; failures replay from Zap history
App catalogue	Smaller node set, very large community template library	Broad catalogue of mainstream SaaS apps	Largest catalogue, including long-tail tools
Best fit	Code-heavy, self-hosted, stateful automation	Visual branching across many SaaS apps	Straightforward app-to-app moves

Where n8n wins

When the flow has real logic in it. A code node takes anything the node library does not cover, turning n8n from a connector into a programmable runtime. If a workflow needs a loop, a jittered retry, or a JSON transform beyond three fields, n8n saves the time spent fighting a UI.
When credentials cannot leave your network. Self-hosting keeps API keys inside your own boundary, which decides it for anything handling customer data. The agent security checklist covers adjacent risks a self-hosted runtime does not solve.
When the workflow needs reviewing like code. JSON export puts a workflow change in the same pull request as the service change that depends on it, with a diff reviewers can read. Neither Make nor Zapier does this.

Where Make wins

When the flow branches a lot and you want to see it. Make’s canvas was designed around iterators, filters and routers, so a flow that fans out and rejoins stays legible in a way other editors make hard. If you are mapping a business process rather than writing software, that legibility is the point.
When per-operation billing matches your flow shape. Because modules are counted individually, many small steps at moderate volume often cost less than the per-task equivalent. Check the current pricing page, not a comparison written last year.
When the scenario is a business process, not a program. Make has fewer code paths than n8n and fewer apps than Zapier, but for mainstream SaaS and branching approval flows it is the most direct tool, and error handlers keep failure recovery visible.

Where Zapier wins

When the app you need exists and nobody wants to write code. The catalogue is a real reason to choose Zapier: a long-tail integration nobody built as a node usually exists as a Zap. For a team automating a dozen tools, that is the difference between shipping this week and next.
When a human needs to step into the flow. Approvals, triage and exception handling are native, and opening a failed run is a more finished operator experience than building that yourself.
When the workflow is short and readable. A Zap is a list of steps with names a non-engineer understands, which makes it easy to hand over, audit and break.

The tiebreaker

If your team can write code and the workflow has more than about ten steps, or touches anything you would not paste into a third-party SaaS console, choose n8n and self-host it. If the team is mostly non-technical and the flow is a handful of app-to-app moves, choose Zapier and accept task billing. If it is a branching business process, choose Make.

The condition that overrides all of it: if the workflow will change weekly and more than one person makes those changes, pick the one with code and version control — n8n — however small the flow looks today. Rebuilding automation others depend on is the expensive path, and the prompt engineering production guide argues the same for the model half.

What broke along the way

Our first self-hosted n8n instance ran out of memory before it ran out of work. Long workflows with large payloads in memory are the classic failure, and the instance died overnight without a clear error. Smaller payloads and streaming fixed it.

Zapier task counts were not what the invoice suggested. A filter producing downstream paths billed a task per path per app. The workflow looked cheap in the editor and the bill told another story, so the branch logic moved into one loop.

Retries that succeed quietly are worse than retries that fail. A node with automatic attempts plus an error workflow meant partial work applied twice. We moved idempotency to the node that wrote, and disabled retries where the write was not idempotent.

Pros and cons

What it gets you

A working integration today in all three, with the trade-off hidden until you need it
Real error handling and retries in n8n and Make, which separates these from shell scripts
A genuine code escape hatch in n8n, so the platform does not become the ceiling
Clear visual representation of branching logic, most obviously in Make

What it costs

Vendor billing shaped around whichever platform you pick, and the shape differs more than the rate
Self-hosted n8n moves cost and responsibility onto you, including upgrades and uptime
Hosted-only options put your definitions and credentials outside your control
Catalogue depth means the best platform may still lack the one connector you need

Who this is for

This comparison is for a technical lead deciding where long-lived automation should live, not for a one-off task — if you need a form sent to a spreadsheet weekly, all three are overkill and a script serves better.

If you already run one in production, treat migration as settled unless a limit is hit. Rewriting working automation to escape a pricing tier is rarely worth the downtime. See the GEO content checklist.

FAQ

Q: Which is cheapest between n8n, Make and Zapier?

A: It depends on execution count and hosting model, so no single number is honest. Self-hosted n8n costs only infrastructure, while Make bills per operation and Zapier per task.

Q: Can Make or Zapier be self-hosted?

A: No. Both are hosted-only SaaS products with no supported self-hosted edition. n8n is the only one you can run on your own infrastructure, which matters for data residency and untrusted input.

Q: Is n8n just Zapier for developers?

A: Not quite. n8n is a node-based runtime with a code escape hatch in JavaScript and Python, and error handling most hosted platforms approximate. Zapier is a hosted service with a larger app catalogue.

Q: What breaks when a workflow fails in each platform?

A: All three fail mid-run, but recovery differs. n8n exposes per-node retry counts plus error workflows, Make branches into error handlers, and Zapier relies on replaying from history.