Founder of Goodspeed
Make and n8n are often shortlisted together, and for good reason. Both use a visual, node-based canvas, both handle complex multi-step logic that would strain a linear tool, and both are far more capable than the simplest automation platforms. If you are choosing between them, you are already past the beginner tier and thinking seriously about how your automation will scale.
The differences that matter are underneath the surface. Make is a polished cloud product priced by operations. n8n is source-available, can be self-hosted, and prices very differently. One keeps your data in its cloud, the other lets you keep it on your own infrastructure. Those distinctions decide the comparison far more than the canvas you draw on.
We build on n8n, so we have a preference, but Make is a genuinely good tool and we will say where it is the better fit. This guide runs through them at a glance, on pricing, on flexibility and code, on self-hosting and data, when Make is plenty, and how to migrate if you move.
Make and n8n at a glance
On first impression the two feel similar. Both give you a visual canvas where you connect modules or nodes into a flow, both handle branching and complex logic comfortably, and both are aimed at people who have outgrown the most basic automation tools. If you have used Make's scenario builder, n8n's node editor will feel familiar rather than foreign.
The philosophies underneath differ, though. Make is a closed, hosted product, refined and commercial, that you use entirely in its cloud. n8n is source-available and can run on your own servers as well as in its cloud, with the ability to write custom code anywhere in a workflow. So while they look alike on the canvas, they represent different bets: Make on a managed, polished experience, n8n on openness and control.
Pricing: operations versus self-hosting
The pricing models are the heart of the comparison. Make charges by operations, where broadly each module action in each scenario run consumes one operation from your plan. Make's operations tend to stretch further than Zapier's tasks, so it is often cheaper for complex work, but the fundamental dynamic is the same: the more your automations run, the more operations you consume and the higher the bill climbs.
n8n breaks that link when self-hosted. You pay for the server it runs on, not per operation, so a workflow can execute enormous volumes without the cost moving. n8n's cloud prices by executions rather than per operation, which is already gentler for multi-step flows. For teams running high volumes, the self-hosted flat cost is frequently the deciding factor, because it turns an ever-growing usage bill into a predictable line item.
Flexibility and custom code
Both tools handle complex logic, but n8n goes further when you need to escape the built-in options. Make lets you transform data with functions and has a code-style module, but it remains a closed environment with defined boundaries. When you hit those boundaries, your room to manoeuvre is limited to what Make provides.
n8n treats code as a first-class citizen. Its Code node runs real JavaScript or Python, so you can manipulate data, call libraries, and implement logic that no visual module covers. Combined with the HTTP Request node reaching any API, this means there is rarely a point where n8n simply cannot do something. For teams whose automations get genuinely custom, this open-ended flexibility is a meaningful advantage over Make's more contained model.
Self-hosting and data control
This is where the two diverge most sharply. Make is cloud-only, so every scenario runs on Make's infrastructure and your data passes through it. That is fine for many teams, but there is no option to keep everything in-house, which rules Make out for organisations that require their data never to leave their own systems.
n8n's self-hosting is a fundamental difference, not a footnote. Run it on your own server and your data stays entirely under your control, in the region and under the retention rules you choose, integrating with internal systems no cloud tool can reach. For regulated industries, privacy-conscious teams, or anyone who simply prefers to own their stack, this capability is often the single strongest reason to choose n8n over Make.
Integrations compared
Make has a large, well-maintained library of app integrations, and its modules are typically polished and reliable. For mainstream SaaS tools you will usually find a ready-made Make module that just works, and that breadth and quality are a real strength of the platform.
n8n offers hundreds of built-in nodes plus a growing set of community nodes, and crucially the HTTP Request node connects to any REST API when no dedicated node exists. So while Make may edge ahead on the number of pre-polished modules, n8n's effective reach is close to unlimited for teams comfortable configuring an API call. The practical question is less about raw counts and more about whether you prefer everything pre-built or are happy to wire up the occasional custom connection to gain the openness.
Ease of use and the learning curve
Make has invested heavily in polish, and it shows. The interface is refined, the modules are consistent, and the overall experience is smooth, which makes it approachable for users who are past the basics but do not want rough edges. If a highly finished, managed experience is what you value, Make delivers it well.
n8n is very capable but a touch more technical, especially once you start using code and more advanced patterns. The two are closer than the Zapier comparison, since both use a similar visual model, but Make generally feels more buttoned-up out of the box while n8n rewards a little more hands-on comfort. The trade is familiar: Make optimises for a frictionless managed experience, n8n for openness and control that pays off as your needs deepen.
When Make is genuinely enough
Make is a strong tool, and there are plenty of teams for whom it is the right answer. If you want a polished, fully managed cloud platform, you are comfortable with your data running through Make's infrastructure, and your operation volume sits at a level where the pricing stays reasonable, Make gives you a lot without asking you to manage anything.
It is especially well suited to teams that value the finished experience and have no desire to self-host. If nobody on your team wants to think about servers, and your automations are complex but not enormous in volume, Make covers that ground comfortably. Choosing it in that situation is not settling, it is picking the tool whose managed, hands-off model matches how you want to work. The question is simply whether you will stay inside those bounds.
When n8n is the better call
n8n becomes the better choice as soon as you push against Make's limits. High operation volumes that make the bill uncomfortable, a need to self-host for data or compliance reasons, or automations that demand custom code and integrations beyond what modules provide all point toward n8n. Any one of those can justify the switch, and often teams feel more than one at once.
It is also the better long-term bet for teams whose automation is central and growing. Because you control where it runs, how it scales, and how deeply you customise it, n8n is a platform you build on rather than one you eventually outgrow. If you can see your needs heading toward serious volume, tight data control, or genuinely bespoke logic, n8n is where that road leads.
Reliability, error handling and monitoring
As automation becomes business-critical, how a tool handles failure matters as much as what it can build. Make provides error handling within its scenarios, and for a managed cloud product that is often enough, since the platform itself takes care of the underlying reliability and you do not manage any infrastructure.
n8n gives you finer control and more visibility. You get dedicated error workflows, per-node retry and timeout settings, continue-on-fail behaviour, and, when self-hosted, metrics you can graph and alert on through the N8N_METRICS option. The trade mirrors the wider comparison: Make hands you a dependable managed baseline, while n8n lets you engineer resilience and observability to exactly the level your most important automations demand.
Migrating from Make to n8n
Migrating from Make is smoother than from most tools, precisely because the visual, node-based model is so similar. A Make scenario maps naturally onto an n8n workflow, its trigger becomes a trigger node, and its modules become nodes on the canvas. Teams that know Make tend to find their footing in n8n quickly, which takes a lot of the fear out of the move.
Follow the same disciplined path as any migration. Audit your scenarios and prioritise them, rebuild each one cleanly rather than copying its quirks, and reconnect apps with fresh, least-privilege credentials. Test every workflow in isolation, run it in parallel with the live Make scenario to confirm the outputs match, then cut over in waves with the old scenario paused as a fallback. Approached this way, the switch is low-risk and reversible.
Two good tools, one honest recommendation
Make and n8n are both genuinely good, and this is not a comparison where one is obviously right for everyone. Make wins for teams that want a polished, managed, cloud-only experience and whose volume and data requirements sit comfortably inside its model. That is a real and common situation, and Make serves it well.
n8n wins for teams that need self-hosting, custom code, or predictable cost at scale, and who want to own their automation stack rather than rent it. If your needs are heading toward volume, control, or bespoke logic, that is the direction we would steer you, and it is the platform we build on every day for exactly those reasons. Match the tool to where you are going, not just where you are today.
Choose on cost and control, not features alone
Make and n8n look alike on the canvas but differ where it counts. Make is a polished, cloud-only product priced by operations, ideal for teams that want a managed experience and sit within its volume and data bounds. n8n adds self-hosting, first-class custom code, and a flat cost model when self-hosted, which is why it keeps making sense as automation grows in volume, sensitivity, and complexity.
If you value openness, data control, and predictable cost at scale, n8n is the stronger long-term bet, and migrating from Make is unusually smooth thanks to the shared visual model. If you want a team that builds automation you own, see our n8n case studies, including HubSync, or book a free call with our n8n team.
Written By
Founder of Goodspeed