Make vs n8n: which automation tool to start with
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Both tools do the same job: when something happens in one app, do something in another, with no code. The short version is that Make is easier to start with, and n8n gives you more control and can run for free on your own machine.
How they differ
| Make | n8n | |
|---|---|---|
| Where it runs | In the browser, hosted for you | Hosted cloud, or self-hosted on your own computer or server |
| Free option | Free plan with a monthly credit allowance | Self-hosted Community Edition; cloud has a free trial with no card needed |
| Learning curve | Gentle. Visual, lots of templates | Steeper. Closer to how developers think |
| Custom code | Limited | JavaScript or Python inside any workflow |
| AI steps | Built-in modules for the main AI services | AI agent nodes, and you can call any API |
| How usage is counted | In credits: each action a module performs uses credits | Per workflow execution on cloud, however many steps it has |
The same workflow in both
The fairest test is to build one small thing twice. A good first one: new row in a Google Sheet, then summarize it with an AI model, then post the summary to Slack or email.
In Make
- Create a scenario and add the Google Sheets “Watch new rows” module.
- Add an AI module and map the row’s text into the prompt.
- Add Slack or Email and map the AI output into the message.
- Run once to test, then switch scheduling on.
In n8n
- Create a workflow and add the Google Sheets trigger node.
- Add an AI node, connect your API key as a credential, and reference the row with an expression.
- Add the Slack or Email node.
- Execute the workflow to test, then activate it.
Who should pick which
Choose Make if you want the quickest path to a working automation, you prefer templates, and your workflows are small enough to fit a monthly allowance.
Choose n8n if you are comfortable with a little setup, you expect to run a lot of executions, you need custom code, or you want your data to stay on your own server.
Cost traps to know about
- In Make, every module action uses credits, and some AI features use more than one. A scenario that checks for new data every few minutes spends credits even when nothing has changed. Use webhooks or longer intervals.
- In n8n Cloud, one run of a whole workflow is one execution, so long workflows cost the same as short ones.
- Self-hosting n8n has no subscription fee, but the computer it runs on has to stay on, and you are responsible for updates and backups.
- Both charge separately from the AI service. API usage for the AI step is billed by that provider.