n8n vs Zapier vs Make: Which to Build Your Automation On

The short answer

If you want a light automation running today and the monthly bill will not exceed a modest task volume, choose Zapier. If you want visibly more sophisticated workflows — branching, iteration, data transformation — at a lower price, choose Make. If your workflows are genuinely complex, call APIs that have no pre-built connector, run at high volume, or process data that must not leave your infrastructure, choose n8n.

The mistake we see most often is choosing by familiarity and then hitting the ceiling eighteen months later: a Zapier bill that has crept past the cost of a custom build, or a Make scenario so dense nobody dares edit it. Choosing correctly at the start is mostly a matter of being honest about volume and complexity now, not at launch.

Zapier: breadth and simplicity

Zapier's real product is its connector library — thousands of apps, more than either competitor, with the long tail of niche SaaS tools covered. If your automation touches an obscure CRM or a regional accounting package, Zapier is the platform most likely to have a ready-made connector. The editor is linear and friendly, and a non-technical operations person can genuinely maintain simple Zaps.

The trade-offs: per-task pricing punishes volume, and the linear model strains under complex logic. Multi-path branching, loops and error handling are all possible but increasingly awkward, and a workflow that processes thousands of items a day can cost more per month than the tool it automates. Zapier is the right answer for breadth and speed to first value, not for heavy lifting.

Make: visual density and value

Make (formerly Integromat) gives you a visual canvas where scenarios branch, loop and merge, with fine control over how data is transformed between steps. Operations pricing is markedly cheaper than Zapier's at comparable volume, and the platform handles moderately complex logic — routers, iterators, aggregators — natively rather than as workarounds.

The cost is cognitive. The canvas that makes Make powerful also makes it easy to build scenarios that only their author understands, and the learning curve is real for non-technical users. Its connector library is large but thinner than Zapier's in the long tail. Make is the value pick for teams with someone technical enough to own it.

n8n: self-hosting and complex logic

n8n is open-source and self-hostable, which changes two things fundamentally. First, cost: a self-hosted instance runs unlimited workflows for the price of a small server, so high-volume automation that would cost hundreds a month elsewhere costs almost nothing to execute. Second, data control: payloads never leave your infrastructure, which matters for anyone handling customer data under strict policies or contractual data-residency terms.

It is also the strongest of the three for engineering-grade logic: JavaScript code nodes, custom HTTP calls to any API, error workflows, queues and version control integration. The trade-off is that someone has to host, update and monitor it — n8n is closer to software you run than a service you subscribe to. The hosted n8n cloud option softens this at a subscription price.

n8n vs Zapier vs Make side by side

Pricing models change frequently, so treat the table as a structural comparison rather than a current price list — the shape of each platform's pricing has been stable for years even as the numbers move.

Choose Zapier when, Make when, n8n when

Choose Zapier when task volume is low, the apps you use are niche, and the person maintaining automations is non-technical. Choose Make when you want more logic per dollar and someone on the team enjoys building. Choose n8n when volume is high, logic is complex, an API you need has no connector anywhere, or your data is not allowed to transit a third party's servers.

Volume deserves the most honesty. At tens of tasks a day, platform choice barely matters financially. At thousands, per-task pricing becomes a meaningful line item, and self-hosted n8n usually wins the three-year arithmetic by a wide margin — provided someone competent operates it.

Whichever you pick, the workflow is the product

The platform is maybe a fifth of the outcome. The rest is the design of the workflow itself: what triggers it, how errors are caught and retried, how edge cases are handled, and whether anyone can understand it in a year. A mediocre workflow on the best platform still loses data quietly on the day an API changes.

We build production workflows on all three platforms — scoped, fixed price between $500 and $1,500, delivered in 4–10 days, running in your account so there is no dependency on us afterwards. The workflow automation use case shows typical scopes, or book a free 30-minute call and bring the process you want to stop doing by hand.