Zapier vs Make vs n8n for small business automation in 2026

We build on all three and pick per client. All three handle most small business automations well. The differences show up in where they run, how hard they are to learn, and how they count usage.

Quick naming note, because it trips people up: Zapier calls a workflow a Zap (a trigger plus actions, built step by step), Make calls it a scenario (modules on a visual canvas), and n8n just calls it a workflow (nodes on a canvas).

Learning curve

Zapier is the easiest start. The editor is linear, and Copilot can draft a Zap from a plain-English description. Most people get a simple two-step Zap working in an afternoon.

Make takes a bit longer. The canvas shows every branch, filter and loop, which is great once it clicks. Routers, iterators and aggregators give you a lot of control, but they're new ideas for most people.

n8n is the steepest. It's visual, but it assumes you're comfortable with JSON, and it's easy to drop into a Code node for anything unusual. Developers tend to like it. Non-technical teams usually need help to start.

Judge this on the workflow you actually need, not a demo. Two steps are easy anywhere. Branches, loops and error handling are where the gap shows.

Self-hosting

This is the biggest practical difference: only n8n can be self-hosted.

• Zapier is cloud-only.
• Make is cloud-only too. It has an on-prem agent so scenarios can reach systems inside your network, but the platform runs in Make's cloud.
• n8n runs on n8n Cloud or your own server. The self-hosted Community Edition is free for your own internal business use under the Sustainable Use License.

Self-hosting matters when client data has to stay on infrastructure you control. The trade-off: someone has to patch, back up and monitor that server.

Pricing: compare the unit, not the headline

	Counts	Notes
Zapier	tasks	A task is a successful action step. Triggers and built-ins like Filter, Formatter, Paths and Delay don't count.
Make	credits	Most module actions use one credit. Routers and error handlers don't.
n8n	executions	One full run of a workflow, however many steps it has.

So long, many-step workflows tend to be cheapest on n8n, short ones are fine anywhere, and high-volume multi-step flows are where Zapier's per-task model adds up fastest. Plans change often, so check the current pricing pages before deciding.

AI features

All three now treat AI as core:

• Zapier: Copilot, AI by Zapier steps, Zapier Agents, Zapier MCP.
• Make: Maia for building scenarios by conversation, Make AI Agents, and modules for OpenAI, Claude and Gemini.
• n8n: an AI Agent node, nodes for chat models, memory and vector stores, MCP support, and an AI Assistant in the editor.

For everyday jobs like reading an invoice, classifying an email or drafting a reply, any of them works. n8n gives the most control over how an agent is wired. Zapier gets you to a working result fastest.

Same job, three platforms

A small agency wants every website enquiry added to its CRM, scored by AI and posted to Slack with a suggested reply.

• On Zapier, a sales manager could build it in an afternoon.
• On Make, the whole flow sits on one canvas, with a router sending hot and cold leads down different paths.
• On n8n, it could run on the agency's own server, with an AI Agent node that checks past projects before writing the reply.

All three work. The right one depends on who maintains it and where the data is allowed to live.

How we'd pick

• Zapier when your team will build and maintain it themselves, workflows are short, and you need a connector for a less common app.
• Make when there are lots of branches, loops or data transformation and you want the whole flow on one screen.
• n8n when data must stay on your servers, workflows run many steps per execution, or you want full control over AI agents.

Plenty of businesses end up on more than one. That's fine, as long as someone knows which automation lives where.

One thing people ask: can you move Zaps to Make or n8n? Not automatically. Each stores workflows in its own format, so it's a rebuild. The logic carries over, though, so the rebuild is faster than the original.

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Originally published on dizilus.com.