What Is n8n, and Why Is It Better Than Zapier or Make?
n8n is an open-source workflow automation platform: you connect services and actions into a single workflow through a visual node editor, without writing code for standard tasks. The main difference from Zapier and Make is pricing. n8n charges for running the whole workflow once, not for every single action inside it, plus it can be self-hosted for full control of your data.
How n8n Works
A workflow in n8n is built from nodes. A trigger (a new form submission, an incoming Gmail message) starts a chain of actions: write a row to Google Sheets, send a message in Telegram, call a GPT model, update a CRM record. Each node is a ready-made block for a specific service, and you can drop in JavaScript or Python code between them whenever a ready-made block isn't enough. In Zapier, custom code is a paid add-on that isn't available on every plan.
Pricing: Execution vs. Task
Zapier and Make count every single action inside a scenario separately. If a workflow runs five steps, that's five "tasks" or "operations" pulled from your plan's quota. n8n Cloud counts the entire run as one execution, no matter how many nodes fire inside it. In practice, a workflow with 10-15 steps costs the same as a simple one with two.
Take a typical lead-intake scenario: log the lead in a CRM, send a Slack alert, add the contact to a mailing list, update a spreadsheet. In Zapier, that's four tasks per run. At a thousand leads a month, that's four thousand tasks, and you end up on a pricier plan simply because of step count, not actual workload. In n8n, the same thousand leads are a thousand executions, regardless of how many steps each one has. You can test this difference on your own workflows with n8n Cloud, which has a free plan for early testing.
Self-Hosting and Data Control
You can run n8n on your own server (the official Docker image takes about 15 minutes to set up), and then there's no cap on executions, and none of your leads', messages', or payment data passes through a third-party cloud. For businesses handling personal data or working under compliance requirements, that's often the deciding factor: Zapier and Make don't offer this option at all. Updates, backups, and access control stay under your own management instead of a vendor's policy.
Flexibility for Non-Standard Tasks
n8n has a Code node where you can drop in JavaScript or Python: process an array of data, run a custom calculation, or call an API with no ready-made integration. If there's no native node for a service, an HTTP Request node handles any REST API. Zapier and Make offer similar code blocks, but with tighter limits on lines of code or execution time on lower-tier plans.
When Zapier or Make Make More Sense
If your team isn't ready to deal with even minimal technical setup and wants the simplest possible interface without self-hosting, Zapier wins on sheer number of ready-made integrations and a shorter learning curve. Make handles complex branching scenarios well visually and works fine if you only run two or three automations and aren't planning to scale soon. n8n takes a bit more time to set up, but it pays off at scale, once you're running ten or more scenarios, each with several steps.
If you're already on Make or Zapier and your scenario count is creeping past three or four, work out what the same automation would cost in n8n. The pricing gap is usually noticeable by the second month.
Frequently asked questions
Is n8n free?
Yes. There's an open-source, self-hosted version you can run on your own server for free (you only pay for hosting). n8n Cloud has paid plans billed per execution rather than per action, plus a free trial.
Do you need to know how to code to use n8n?
No. Most workflows are built through the visual node editor without any code. JavaScript or Python is only needed for edge cases that no ready-made node covers.
What's the biggest difference between n8n and Zapier?
Pricing (execution instead of task-per-step) and the option to self-host with full control over your data. Those two factors usually tip the decision toward n8n once automation needs to scale.