Make vs n8n vs Zapier

All three of these tools connect apps and move data between them without you writing a full integration by hand, and all three describe the same basic unit differently: Zapier calls it a Zap, Make calls it a scenario, n8n calls it a workflow. The vocabulary difference is trivial. The real differences are how much you pay per action, whether you can run the tool on your own infrastructure, and how much flexibility you get once a workflow needs to do something none of the built-in nodes anticipated.

How does each tool's core building block actually work?

A Zapier Zap starts with a trigger (a new row, a new form submission, a scheduled time) and runs through one or more actions in a fixed, linear sequence. Zapier's own strength is breadth: more than 9,000 app integrations, according to Zapier's own product pages, which makes it the most likely of the three to already have a native connector for whatever tool you use.

A Make scenario is built on a visual canvas where you connect modules and map fields between them, with more room for branching logic and multiple parallel paths than Zapier's linear structure allows. Make bills in credits rather than a flat task count: most modules consume one credit each, though AI-calling modules can consume more, and the free plan includes 1,000 credits a month.

An n8n workflow starts with the same trigger-then-action shape, but n8n adds two things neither competitor offers: a free, self-hosted Community Edition you run on your own infrastructure, and a JavaScript node for a custom step when no built-in node covers what you need. That combination trades some of the polish of Make's canvas or Zapier's app catalog for control over where your data actually lives and how far a single workflow can flex.

How much does each one cost?

	Zapier	Make	n8n
Free tier	100 tasks/month	1,000 operations (credits)/month	Free, self-hosted Community Edition
Entry paid plan	Professional: $19.99/month, 750 tasks	$9/month, 10,000 credits	Cloud plans with a monthly AI credit allowance
Unit of billing	Tasks (one per completed action)	Credits (roughly one per module run)	Free if self-hosted; Cloud billed by plan tier
Team plan	Team: $69/month, 2,000 tasks, up to 25 users	Priced by credit tier, shared across the team	Self-hosted paid tiers add SSO, environments, secrets
App integrations	9,000+	Large catalog, not separately published as a total	Native integrations plus HTTP/webhook for any API
Self-hosting	Not available	Not available	Yes, free Community Edition
Code escape hatch	No	Limited	Yes, a JavaScript node
AI steps	AI by Zapier, priced by model tier since June 2026	Built-in AI modules, higher credit cost per call	AI nodes available, cost depends on plan

The task-versus-credit distinction matters more than it looks. A Zapier task is one completed action; a Make credit is roughly one module execution, though certain modules (notably AI-calling ones) cost more than one credit each. That means a workflow with the same number of logical steps can consume its monthly allowance at different rates on the two platforms, and the only way to know for sure is to build the actual workflow and watch the usage meter for a week before committing to a paid tier.

What does Builders Camp actually teach among these three?

Automate Workflows with AI is a real Builders Camp bootcamp, 1 week and 2 live sessions taught by Andre Albuquerque, and its curriculum data names Zapier and Make.com directly as syllabus tools, alongside GPT for the judgment steps inside a workflow. n8n is not one of the named tools in that bootcamp's curriculum. That is worth stating plainly rather than blurring: Builders Camp separately publishes a guide on setting up an n8n workflow, and the underlying discipline the bootcamp teaches (pick the right task before you build, add a human-in-the-loop checkpoint on anything high-stakes, test against real data before turning a workflow on) applies to n8n exactly as it applies to Make or Zapier, but the bootcamp's own sessions do not walk through n8n's interface directly.

How do the three handle an AI step inside a workflow?

All three now let a workflow call a language model as one step among others, not just move data between apps. Zapier's AI steps have run on model-tier pricing since June 15, 2026: a Standard-tier model call costs the base task rate, an Advanced-tier call costs three times that, and a Premium-tier call costs five times that, so the choice of model directly changes how fast you burn through your monthly task allowance. Make's built-in AI modules typically consume more than the standard one credit per module, though Make does not publish a fixed multiplier the way Zapier now does. n8n's AI nodes draw on whatever model access you configure yourself, with cost depending on the model provider and your own API arrangement rather than a platform-set multiplier.

That difference matters most for a workflow that leans heavily on AI judgment, like classifying a support ticket or drafting a summary. A workflow with one or two AI steps per run behaves predictably on any of the three. A workflow that calls a Premium-tier model on every single item in a high-volume trigger can consume a Zapier task allowance far faster than the same workflow's non-AI steps would suggest, which is a real budgeting trap worth checking against your actual expected volume before committing to a plan.

Choose Zapier if, choose Make if, choose n8n if

Choose Zapier if the tool you need to connect already has a native Zapier integration and you want the fastest path from idea to a running automation, without touching a visual canvas's branching logic. Choose Make if you need more control over data mapping and branching than a linear Zap allows, and a lower entry price for a comparable volume of actions matters to you. Choose n8n if self-hosting for cost or data-residency reasons is a real requirement, or if you expect to hit the limits of a no-code tool and want a JavaScript escape hatch available before that happens, not after.

Who this is for, and who it is not for

This comparison is for PMs, operators, and founders picking a no-code or low-code automation tool for internal workflows: reporting, triage, status updates, and similar repetitive tasks. It is not for a team that has already decided the automation needs engineering ownership, uptime guarantees, and on-call coverage; at that point, any of these three tools is better used as a working spec for what to build properly than as the production system itself, a distinction n8n workflows for product managers covers directly.

Learn to pick the right task before you touch any of these three

The mechanics of connecting a trigger to an action are the easy part of any of these tools. Choosing which repetitive task actually deserves automation, and building in the human checkpoint a high-stakes step needs, is the actual skill. Builders Camp's Automate Workflows with AI bootcamp covers exactly that in 1 week, 2 live sessions, taught by Andre Albuquerque, with a practical challenge built around diagnosing and fixing a real broken automation under a hard token constraint.

See the Automate Workflows with AI bootcamp

For the full setup walkthrough on the two tools the bootcamp actually teaches, see Make.com for product managers and n8n workflows for product managers. For the wider set of no-code options beyond automation specifically, see no-code tools for product managers, and for how automation tools fit into a PM's broader AI toolkit, see the best AI tools for product managers in 2026.