n8n vs Make
Ask who fixes this at 9am on a Monday when it breaks. That answer decides more than any feature on either website.
The verdict
Choose Make when an operations person owns the automation and every system involved is a cloud app. Choose n8n when the workflow must run inside your own network, or when engineers maintain it and need real code in the middle.
Make is the better product for the person it is built for. The canvas is easier to read, the branching is visual, and an operations manager can build something useful on their own. That beats most technical advantages. An automation nobody in the business can change becomes an engineering ticket every time it needs a tweak.
One constraint overrides that. Make runs in Make's cloud, and there is no version you host yourself. If the data cannot leave your infrastructure, the comparison stops there.
Where the two differ in practice
Checked against both vendors' own pages on 11 August 2026. App counts move quickly; the hosting model and the billing unit move slowly.
| Dimension | n8n | Make |
|---|---|---|
| Who it is built for | Technical teams. n8n's docs point non-technical users to its managed cloud. | Operations staff. The canvas is the product. |
| Self-hosting | Yes. n8n names full control of the environment as the reason to choose it. | No. Make runs on its own cloud infrastructure. |
| Reaching a private system | Direct, because n8n runs inside your network. | Only via the on-prem agent, which Make lists on its Enterprise plan. |
| App catalogue | Over 500 integrations, per n8n's homepage. | 3,000+ standard apps, per Make's pricing page. |
| Billing unit | One execution covers a whole workflow run, whatever the step count. | Credits. Make says every time a module performs an action, it consumes credits. |
| Where data is processed | Wherever you install it. | Make's own cloud, on AWS in the EU or North America. |
| Custom code | A code node in JavaScript or Python, with more freedom when self-hosted. | Available, but the canvas is the intended way to build. |
n8n
Strong at
- Self-hosting keeps data and credentials on infrastructure you control, which is the answer to a residency question.
- It sits inside your network, so an internal database needs no public exposure.
- The code node handles the logic a canvas cannot express.
- Workflows are JSON, so they can be reviewed and rolled back like other code.
- One execution covers a whole run, which suits long workflows that fire often.
Weak at
- Self-hosting is a service somebody has to operate, patch and back up.
- The catalogue is far smaller, so more connectors become your problem to build.
- A non-technical owner will need help sooner than they would on Make.
- Tracing a failure deep inside a long run takes patience.
Make
Strong at
- A non-technical operator can build and repair workflows without an engineer, which is the whole point of it.
- The catalogue is around six times larger, so the connector usually exists already.
- Nothing to host, patch or monitor.
- Complex branching is easier to follow on the visual canvas than in most competing tools.
Weak at
- No self-hosting at all, so data residency has one answer: Make's cloud.
- Reaching an internal system needs the on-prem agent, which sits on the Enterprise plan.
- Credit billing counts each module action, so a busy many-step scenario costs more than a simple one.
- Heavy logic has to be bent into the canvas, and complicated scenarios get hard to read.
- Version control and code review are not how the product works.
Which one fits your team?
Three questions about your situation, not about features.
Who will maintain this in six months?
Where is the data allowed to be processed?
What does a failed halfway run cost?
Every outcome
- Make
- An operations person owns this and every system is a cloud app. They can build it, fix it on a Monday morning, and never file a ticket.
- Self-hosted n8n
- The workflow touches something private, or compliance will ask where the data was processed. Running it inside your own network answers both, and engineers get real code where they need it.
- Neither. Build a service.
- A half-finished run leaves money moved or an order half-placed. That needs durable execution and provable recovery, which is a job queue rather than a canvas.
- TriggerIdentical on both.
- LocationMake: its cloud. n8n: yours.
- Private dataThe line neither crosses freely.
- LogicCanvas, or canvas plus code.
- OwnerOperations, or engineering.
Stations two and five decide almost every real case. The connector count decides far fewer than the marketing suggests.
Rules that settle it
Decide on who owns it and where the data may sit. Both are known before you build anything, and neither changes cheaply afterwards.
- 01Choose Make if the person who understands the process is the person who should be editing it.
- 02Choose Make if every system involved is a cloud app and the connector already exists.
- 03Choose n8n if the automation reads a database you would not put on the public internet.
- 04Choose n8n if an auditor will ask which country processed the data.
- 05Choose neither if a partial run leaves somebody out of pocket. That is a queue with retries, not a canvas.
An automation running unattended
Common questions
01Which is easier for someone who cannot code?
Make, and it is not close. The canvas is designed for operations staff rather than engineers. n8n's own documentation points people without technical expertise toward its managed cloud instead of self-hosting. If nobody technical is available to help, that difference decides the tool.
02Can Make connect to a system on our internal network?
Only through its on-prem agent, which Make lists as an Enterprise plan feature for securely accessing local networks. Make itself still runs in its own cloud, so the platform is not self-hosted. Check that the agent covers your specific system before planning around it.
03Can you use n8n and Make together?
Yes, and splitting by ownership works better than splitting by feature. Let operations run their own scenarios in Make, and keep the workflows touching internal systems in n8n where engineers maintain them. Write down which team owns which process, or nobody knows where to look when something stops.
04What does moving from Make to n8n involve?
Rebuilding each scenario, because triggers, modules and credentials are vendor-specific. What carries over is the process knowledge, which took longer to work out than the wiring did. Move the scenario that touches private data first, since that is the one with a reason to move.
05Which one costs less to run?
The billing shapes differ, so it depends on how many steps your automations have and how often they run. Make consumes credits per module action. n8n Cloud counts a whole workflow run as one execution, and self-hosting removes the meter in exchange for running a server. Price your busiest workflow on both before deciding.
