Make vs Zapier vs n8n

These three get compared constantly, which obscures that they aim at different buyers. Zapier sells to anyone in a company. Make sells to operations people who think in flowcharts. n8n sells to people comfortable with a terminal.

Pricing changes frequently on all three, so this page describes how each charges rather than quoting figures that will be stale by the time you read them. The billing model is the durable difference, and it determines your cost more than the sticker price does.

How each one charges

This is the single most consequential difference, and it's where most cost surprises come from.

Zapier counts a task as any successful action that runs. Triggers never consume tasks, including polling triggers that check an app repeatedly. Filters and paths don't consume tasks. Steps that error or get skipped don't. Every successful action step does. Exceed your plan allocation and the account moves to pay-per-task billing automatically, capped at three times the plan limit, after which workflows stop running.

Practical consequence: cost scales with workflow depth times frequency. Deep workflows on high-volume triggers are where Zapier gets expensive.

Make bills in credits. Each action a module performs consumes credits — most consume one, and some advanced features backed by Make's AI provider consume more. Because bundles from an earlier module multiply through the rest of the scenario, a trigger returning ten records means downstream modules each run ten times. Make offers a free tier with a monthly credit allowance.

Practical consequence: similar depth-times-volume shape to Zapier, but the multiplying effect of bundles is the thing that catches people out. Aggregating before processing matters.

n8n charges its cloud plans per workflow execution. A single run of an entire workflow is one execution regardless of how many steps it contains or how much data it moves. Self-hosted deployments of the Community Edition aren't metered by n8n at all — you pay for the infrastructure you run.

Practical consequence: complexity is free, frequency is what costs. This inverts the incentive: on n8n you consolidate logic into fewer, larger workflows; on Zapier and Make you strip steps out.

Head to head

Choose Zapier when

The connector catalog is the deciding factor, and it frequently is. If your stack includes a niche tool, Zapier is most likely to support it natively, and building against a maintained connector beats reverse-engineering an API.

Also choose it when the builders are non-technical and will remain so. Zapier's constraint — mostly linear workflows — is also its accessibility. Someone in marketing can build, understand and fix a Zap without training. That's worth more than most feature comparisons admit.

Where it stops fitting: high-volume, many-step processes, and processes whose real structure is a graph, not a line.

Choose Make when

Your processes have genuine branching — routes that diverge on conditions and rejoin, iteration over collections with per-item handling, aggregation before a downstream step, error handlers that differ by failure type. Make's canvas represents that structure directly, and seeing a process laid out visually is a real advantage when you're debugging something nobody has touched in months.

It suits operations people who think in flowcharts but don't want to write code or run servers.

Where it stops fitting: very high volume, where per-action metering still scales against you, and cases where you need to run inside your own environment.

Choose n8n when

Volume is high enough that per-action pricing hurts, or the processes are deep enough that execution-based billing is dramatically cheaper. Or you need workflows to run inside your own infrastructure for compliance or data residency. Or your team wants to drop into JavaScript or Python mid-workflow instead of assembling eleven modules to do a transformation.

Where it stops fitting: nobody on the team wants to operate infrastructure, or the builders are non-technical. Self-hosting isn't free — it's a subscription paid in someone's attention. And if you're building a product on top of n8n rather than running it internally, read the Sustainable Use License carefully first, because offering it as a service is not permitted under it.

The comparison that actually predicts success

None of the above is the strongest predictor of whether an automation program works. This is: who will maintain it in eighteen months, and can they read it?

An n8n workflow only the departed contractor understood is worse than a clumsy Zap the office manager can fix. A Make scenario with forty modules and no naming convention is worse than four small Zaps. Platform capability doesn't matter if the artifact is unmaintainable by whoever inherits it.

So pick the least powerful platform that can do the job, staffed by people who'll still be here. Revisit when you actually hit the ceiling.

Do you need to pick one?

Not necessarily. Running Zapier for the long tail of simple connections and n8n for the handful of high-volume or sensitive processes is a reasonable structure — you pay for connector breadth where you need it and avoid per-action metering where volume is concentrated. The cost is two systems to monitor. Worth it above a certain scale; overhead below it.

Before choosing any of them, check whether the process needs a third-party platform at all. Native automation inside software you already pay for is free and adds no vendor. And run the numbers on whether the automation earns its cost, including when the answer is no.

Frequently asked questions

What is the main difference between Make and Zapier?

Flow control and pricing unit. Zapier is fundamentally linear — a trigger followed by a sequence of actions, with filters and paths available but branching bolted onto a straight-line model. Make is built around a visual canvas with routers, iterators, aggregators and error handlers, so processes that genuinely branch and rejoin can be represented as they actually are. On billing, Zapier counts successful action steps while Make consumes credits per module action. Zapier's connector catalog is substantially larger — it states 9,000-plus integrations against Make's stated 3,000-plus.

Is n8n cheaper than Zapier?

For deep workflows, usually and often dramatically, because the billing units differ in kind. n8n's cloud plans count a single run of an entire workflow as one execution regardless of step count, while Zapier counts every successful action step. A twenty-step workflow costs the same as a two-step workflow on n8n and ten times as much on Zapier. Self-hosting the n8n Community Edition removes vendor metering entirely. The offset is operational cost: someone must run, patch, monitor and back up the infrastructure, and that time isn't free.

Is n8n really open source?

Not under the standard definition. n8n ships under the Sustainable Use License, which it describes as fair-code rather than open source. The license grants a royalty-free right to use, copy, distribute and modify the software for internal business purposes and for non-commercial or personal use, while prohibiting commercial use of the kind that involves offering it as a service, and prohibiting removal of licensing notices. For companies running it internally this distinction rarely matters in practice. For anyone building a product on top of it, it matters a great deal — read the license text before committing.

Can Make or Zapier be self-hosted?

No. Both are commercial software-as-a-service products that run on the vendor's infrastructure, and neither offers a self-hosted deployment. If your requirement is that workflow data never leaves your environment — for regulatory reasons, contractual data residency commitments, or internal security policy — that requirement rules both out. Among these three, n8n is the only option, via its Community Edition, and other self-hostable engines exist in the same category. Self-hosting solves data residency and metering, but transfers uptime, upgrades and backups to you.

Which automation platform is best for a small business?

Usually the one your team can maintain without help, which for most small businesses means Zapier or Make rather than n8n. Small businesses rarely have the volume where execution-based pricing wins, and rarely have someone who wants to operate a server. Start with whatever your existing software already automates natively, add a hosted platform for the connections that cross systems, and only consider self-hosting when volume makes the subscription genuinely painful. The platform that gets abandoned because nobody can debug it costs more than the expensive one that keeps working.

Should I use more than one automation platform?

Above a certain scale, yes. A common structure is a broad-catalog platform for the long tail of simple, low-volume connections, plus a self-hosted or execution-priced engine for the few workflows carrying most of the volume or handling sensitive data. That puts each workload on the pricing model that suits it. The cost is operational: two systems to monitor, two places to look during an incident, two sets of credentials. Below a few dozen workflows, that overhead usually outweighs the saving.