n8n vs Make vs Zapier for Business Automation: Pricing Models, GDPR and AI

n8n vs Make (and Zapier) comes down to three things: how you’re billed, where your data runs, and how technical your team is. Zapier is the easiest and bills per task, Make is visual and cheaper for multi-step scenarios and bills per credit, and n8n bills per whole workflow execution and is the only one of the three you can self-host, which makes it the default pick for GDPR-sensitive or high-volume work.

That’s the short version. The long version matters because the wrong pick doesn’t hurt on day one. It hurts six months later when a workflow that cost almost nothing at 200 runs a month costs real money at 20,000, or when your DPO asks where customer data is processed.

Quick comparison

All three change their plans regularly. Treat the descriptions below as how the models work, and check Zapier’s, Make’s and n8n’s pricing pages for current numbers before you commit.

Pricing models: why the unit matters more than the price

Zapier: per task

According to Zapier’s pricing page, a task is counted each time Zapier successfully completes an action step. Triggers and built-in utilities like Filter, Formatter, Paths and Delay don’t consume tasks, which is fairer than it used to be. But a five-action Zap that runs 1,000 times is still about 5,000 tasks. Zapier also notes that some AI steps cost more than one task. Overage is optional (pay-per-task) and billed at a premium over your plan rate.

Make: per credit

Make’s pricing page now bills in credits. Most module actions cost one credit each: reading a row, creating a record, transforming data, iterating over items. Routers and error handlers don’t count. Make tends to be cheaper than Zapier for the same multi-step logic, but loops can surprise you: iterating over 500 rows means hundreds of credits for a single scenario run.

n8n: per execution

n8n’s pricing page is explicit: an execution is a single run of your entire workflow, no matter how many steps it has. That flips the economics. A 30-step workflow costs the same per run as a 2-step one. For long workflows with lots of data transformation, n8n Cloud is usually the cheapest of the three. For a handful of simple two-step automations, the difference barely matters.

Self-hosted n8n: no per-run fee, but not free

The n8n Community Edition is free to self-host. It runs under n8n’s Sustainable Use License, which allows using it for your own internal business purposes. What it doesn’t allow is reselling n8n itself, for example hosting it and charging others for access, or white-labeling it. Some features (such as SSO and advanced permissions) sit in paid editions.

The honest costs of self-hosting:

• A server or container platform, backups and monitoring.
• Updates and security patches, which someone has to own.
• Debugging when a workflow fails at 2 am.

If nobody on your team is comfortable with Docker and a Linux server, self-hosting is a false economy. n8n Cloud or Make will be cheaper in total.

Self-hosting and GDPR

For EU companies, data location is often the deciding factor, not price.

Three things people forget:

1. The connected apps matter too. If your n8n server is in Frankfurt but the workflow sends every invoice to a US-hosted AI API, the data still leaves the EU. Map the whole flow, not just the automation tool.
2. Logs store data. All three tools keep execution history with the actual payloads. Set retention so customer data isn’t kept for years in run logs.
3. AI steps are processors too. Sending personal data to an LLM provider needs a legal basis and a DPA with that provider.

None of this is legal advice. If you process health data, financial data or large volumes of personal data, have your DPO review the architecture.

AI features: agents, LLM steps and where each stands

All three now market AI heavily, and all three can call large language models.

Zapier offers AI steps inside Zaps, its own agents product and an MCP server so AI assistants can trigger Zapier actions. Good for adding a “summarize this” or “classify this email” step without any setup.

Make offers AI modules and AI agents inside scenarios, with a visual canvas that makes branching on AI output easy to follow.

n8n has the deepest toolbox for building agents: an AI Agent node with memory, tools and connections to many model providers, plus the option to run local models when you self-host. That’s the reason many teams building AI agents for business end up on n8n.

The trade-off is the same as everywhere else: the more control, the more you have to understand what you’re building.

When you need code instead of a no-code tool

No-code tools are great until they aren’t. Move to code (or to n8n’s Code node with someone who can maintain it) when:

• The workflow is the product. If customers depend on it and downtime costs money, it needs version control, tests and monitoring.
• Volume is high and steady. Tens of thousands of runs with heavy transformation are often cheaper as a small service.
• The logic is unreadable. When a scenario has 80 modules and nobody dares edit it, it’s already code, just badly documented code.
• You need precise error handling. Retries, idempotency and partial failures are easier to get right in code.

A common, sensible setup: n8n or Make for orchestration and integrations, small code functions for the tricky bits.

Which one should you choose?

• Choose Zapier if a non-technical person will build and own a handful of simple automations, and speed matters more than cost per run.
• Choose Make if you want visual, branching scenarios, have moderate volume, and are happy in the cloud with EU hosting.
• Choose n8n if workflows are long or high-volume, data has to stay on your infrastructure, or you’re building AI agents and want full control over models and tools.

Illustrative example: a 20-person distributor wants new web orders checked against stock, written to the ERP, and confirmed by email, with an AI step that reads free-text delivery notes. That’s around 15 steps per run. On a per-task or per-credit tool, every order costs 15 units; on n8n, one execution. With a few thousand orders a month and customer data involved, self-hosted n8n or n8n Cloud would be the natural shortlist.

For costs beyond tool subscriptions, see AI implementation cost, and for sequencing the whole project, how to implement AI in business.

Get the automation built, not just the tool picked

We design and build business automations on n8n and Make, including AI steps and self-hosted, GDPR-conscious setups, and hand them over documented. Book an automation discovery call and bring the process that eats the most hours.