Make vs n8n for business: which one to choose

Once a company decides to automate seriously, the question comes up fast: Make vs n8n, which one? Both are visual platforms for connecting apps and building workflows, both have hundreds of integrations and both cover most everyday use cases. But they start from different philosophies, and that difference shows up in cost, in data control and in who can maintain the flows.

This article compares them from the point of view of a business that needs dependable automation, not a hobbyist trying out tools. Pricing and plans change often, so check the official pages before you decide.

What Make and n8n are

Make (formerly Integromat) is a cloud automation platform. You build "scenarios" by dragging modules onto a visual canvas, each connected to an app or an operation (filter, transform, iterate). You pay a subscription based on how many operations your scenarios run each month.

n8n is an automation platform with a "fair-code" model: its source is available and it can be installed on your own servers, alongside a cloud version run by n8n itself. It is just as visual, built from nodes, and makes it very natural to drop JavaScript or Python into a flow.

Both are used for the same job: an event in one tool triggers actions in others. The difference is in how they are deployed, how they charge and how much control they give you.

Make vs n8n: the differences that matter to a business

Ease of use

Make has a gentler learning curve for business users. The interface is highly visual, each app's modules are well documented and mapping data between steps is intuitive. An operations lead who is reasonably comfortable with tech can build useful flows quickly.

n8n is just as visual but aimed at a slightly more technical user. It shines when you need to transform data, call APIs that have no connector or write your own logic. For a team with nobody technical, the curve is steeper.

Pricing model

Make charges by operations: each module that runs in a scenario uses one. At moderate volume it is very affordable, but a flow that processes thousands of records a day, with several steps each, can push usage up quickly.

n8n cloud charges per full workflow execution rather than per step, which tends to favour long flows. Self-hosted, the cost becomes your infrastructure and upkeep, with no volume fee on the community edition. Those savings are not free: someone has to look after the server, the updates and the backups.

Where your data lives

With Make, the data passing through your scenarios goes through Make's infrastructure. It offers EU hosting and data processing agreements, which covers many cases, but the data does leave your environment.

With self-hosted n8n, data never leaves your servers. For companies with sensitive data (health, financial, customers with strict contracts) or internal policies that limit cloud services, this point is usually decisive.

Connectors

Make has a very broad and mature catalogue of native integrations. If you work with lots of well-known SaaS apps, they are probably all available with complete modules.

n8n has fewer native connectors, though it covers the common tools, and its HTTP node plus the option to write code make connecting any API straightforward for someone technical.

Maintenance and governance

This is the most underestimated difference. An automation platform ends up running dozens of critical flows. You need to know which ones exist, who maintains them, what they do when they fail and how changes are versioned.

Make handles the infrastructure for you: there are no servers to maintain. Self-hosted n8n gives you full control, and full responsibility. Either way, the flow inventory, error alerts and documentation are your team's job.

When each one fits

Make usually fits better when:

• Flows will be built and maintained by business or operations staff.
• Operation volume is moderate and predictable.
• You mostly work with popular SaaS apps.
• There are no special restrictions on where data is processed.

n8n usually fits better when:

• Volumes are high or flows have many steps.
• Data must stay within your own infrastructure.
• You need custom logic, complex transformations or APIs without connectors.
• There is a technical person, in-house or external, who owns the server.

It is not unusual for a company to run both: Make for the light flows the team maintains itself, and n8n for critical, high-volume processes.

Five questions to decide

Before comparing plans, answer these in writing. They often tip the balance on their own:

1. Who will maintain the flows in a year? If nobody is technical, your own server is a burden, not an advantage.
2. Can the data pass through a third party's servers? If internal policy or a contract rules it out, self-hosted n8n is close to mandatory.
3. How many records will a flow process per day, and how many steps does it have? Estimate volume before looking at any price list.
4. Are there connectors for every app involved? If one is missing, can someone solve it with an API call?
5. What happens if the platform changes its terms? Keep the flows documented so you can rebuild them in another tool.

An illustrative example: a services firm wants website leads created in the CRM and the salesperson notified. It is a few steps, low volume, popular apps, and someone in operations will run it. Make fits without much debate. Another company has to process hundreds of orders a day with its own validation rules and cannot move the data off its servers. There the decision points to self-hosted n8n, with someone accountable for the server.

Signs you should review your current platform

• Monthly usage is growing faster than the value the flows deliver.
• Some flows nobody can explain break whenever an app changes.
• You need logic the platform only allows through workarounds.
• A security or data protection review questions where information is processed.

If any of these sounds familiar, do not switch tools straight away: first inventory your flows and decide which are worth migrating.

A practical way to run that inventory is a simple table with one row per flow: what triggers it, which systems it touches, who owns it, what happens when it fails and how often it runs. Flows that nobody owns are the first candidates to retire or document. Flows that run constantly and touch sensitive data are the ones that decide whether you need to rethink where the platform is hosted.

What matters more than the tool

The choice between Make and n8n matters less than the groundwork. Automation fails for the same reasons on any platform: a poorly defined process, dirty data, nobody receiving the error alerts. So before choosing, follow the steps in our business process automation guide: fix the process, decide which system owns each piece of data and name an owner.

And if you do not yet know which processes to automate, start with an operational audit.

In QuO Forge we work with both platforms and choose based on your data, your volume and who will maintain the flows once we have stepped back.

Frequently asked questions

Which is cheaper, Make or n8n?

It depends on volume and deployment. With a few flows at moderate volume, Make is usually inexpensive and needs no servers. At high volume, n8n, especially self-hosted, tends to cost less, as long as you account for the cost of technical upkeep.

Can you migrate flows from Make to n8n?

There is no reliable automatic converter, but the logic of a flow (triggers, steps, transformations) carries over well. Migration means rebuilding each flow and testing it with real data before switching the original off.

Is self-hosted n8n GDPR compliant?

Hosting n8n on your own servers inside the EU makes compliance easier because data stays in your environment, but GDPR depends on how data is processed, not only where it sits: you still need to document the processing, restrict access and secure the server.