n8n vs Make vs Zapier: Which Automation Tool Should Your Business Use?

If you've decided to automate something in your business, you'll hit the same fork almost immediately: n8n, Make, or Zapier? They all connect your apps and run workflows, but they're built for different people, priced on different logic, and pull ahead in different situations. Picking wrong isn't fatal, but it can mean a bill that's 5x higher than it needed to be, or a tool your team can't actually use.

I've built on all three. Here's the no-hype version of how they differ and how to choose.

The one-line positioning

• Zapier: the easiest. 7,000+ app integrations, natural-language workflow building, zero technical skill required. You pay for that simplicity.
• Make: the visual middle ground. A drag-and-drop canvas for multi-step logic, cheaper than Zapier at volume, still no-code.
• n8n: the most powerful. Open-source, self-hostable, deep AI-agent support. Built for developers and teams who want control and low cost at scale.

If you remember nothing else: Zapier for non-technical speed, Make for visual workflows on a budget, n8n for power, scale, and data control.

Pricing is where the real difference hides

The sticker prices look similar. The billing models are not, and at volume they diverge wildly:

• Zapier bills per task: every single action in a workflow counts. A 10-step Zap that runs 10,000 times a month is 100,000 tasks.
• Make bills per operation: similar granularity to Zapier, but generally cheaper per unit.
• n8n bills per execution: the entire workflow run counts as one, no matter how many steps.

That last one is the headline. For a 10-step workflow running 10,000 times a month, n8n can cut costs by 80–90% versus Zapier, simply because it charges once per run instead of once per step. If your automations are simple and infrequent, this barely matters. If they're complex and high-volume, it's the whole ballgame.

AI and agents: n8n pulls ahead

All three have moved hard into AI, but they're not equal:

• n8n offers the deepest integration: native LangChain support, 70+ dedicated AI nodes, local LLM hosting, vector-database connections, and multi-agent orchestration. If you're building actual AI agents that take actions, this is the natural home.
• Zapier has AI Actions, Zapier Agents, and an AI Copilot that builds workflows from a plain-English description.
• Make has Maia (its AI assistant) and Make AI Agents, with native OpenAI, Anthropic Claude and Google integrations.

For most small businesses stitching AI into a few workflows, any of them is fine. For building genuine agentic systems, n8n's depth is hard to beat.

Self-hosting and data: n8n's other trump card

n8n is the only one of the three you can self-host. For a regulated business (healthcare, finance, anything with sensitive customer data) that means the data never leaves your servers. Zapier and Make are cloud-only; your data flows through their infrastructure. That's perfectly acceptable for most businesses and a dealbreaker for a few. Know which one you are.

Self-hosting isn't free. You trade a monthly SaaS bill for the responsibility of running, updating and securing the thing yourself. For a team without technical hands, "free and open source" can quietly become the most expensive option.

So which should you actually use?

Here's the decision the way I'd give it to a client:

• Pick Zapier if nobody on your team is technical, you want it working this afternoon, and your volume is modest. You'll pay a premium, but you'll never touch a config file.
• Pick Make if you want real multi-step, branching logic on a visual canvas, you're cost-conscious, and you're comfortable with a slightly steeper (but still no-code) tool.
• Pick n8n if you have some technical capability, you're running high-volume or complex automations, you're serious about AI agents, or you need to keep data on your own servers. It's the cheapest at scale and the most powerful, at the cost of a learning curve.

And a reminder that matters more than the tool choice: the platform is not the hard part. Choosing the right thing to automate first is. If you get that wrong, the best tool in the world just automates a low-value task faster. I wrote a framework for exactly that, which workflow to automate first, and I'd start there before you sign up for anything. If you want more ideas on what's worth automating, here are 12 real automation examples for small businesses.

Still stuck between two of them? Tell me the workflow you're trying to build, your volume, and how technical your team is, and I'll tell you straight which platform fits, and whether it's worth self-hosting.