Best Automation Tools 2026 — Zapier vs Make vs n8n

Workflow automation platforms connect the apps a business already uses so that an event in one, such as a new form submission, a payment or a support ticket, triggers actions in others without anyone copying data by hand. Three platforms dominate discussions of general-purpose, low-code automation: Zapier, Make (formerly Integromat) and n8n. They overlap heavily, but they make different design choices about who builds workflows, how usage is counted, how much logic and code you can use, and where your data is processed.

This comparison is built from each vendor's own documentation, not from marketing claims or affiliate deals. We describe what each tool does, its documented limits, and the kinds of teams it tends to suit. We do not list prices: all three change their plans regularly, and the only reliable figure is the one on the vendor's pricing page on the day you check. What we can compare reliably is the billing unit, because that determines how costs scale.

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The Short Answer

• Zapier suits non-technical teams that need to connect many SaaS apps quickly with mostly linear workflows. It has the largest integration directory of the three.
• Make suits people who think visually and need branching, iteration over lists and explicit error handling, and who are willing to learn its concepts.
• n8n suits technical teams who want to write code inside workflows or keep data on their own infrastructure by self-hosting, and who can operate a server.

If you are new to automation, it is worth mapping the process on paper first; see how to map a business process before automating it. The right tool depends far more on the shape of the workflow than on any feature list.

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How we compared the tools

Each claim below is drawn from the vendor's public help centre or documentation, checked in October 2026:

• Integrations: the number each vendor states on its own directory page. Counts are self-reported and define "integration" differently, so treat them as orders of magnitude.
• Billing unit: how the vendor's documentation says usage is counted.
• Logic: documented branching, looping and error-handling features.
• Code: which languages can run inside a workflow and with what restrictions.
• Hosting: whether the software can run on your own servers, and under what licence.

We did not run load tests or measure uptime, so we make no claims about relative reliability or speed.

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Zapier

Zapier, founded in 2011, organises automations as Zaps: a trigger in one app followed by one or more action steps.

Integrations

Zapier's app directory states that it connects 10,304+ apps, according to zapier.com/apps as of October 2026. That breadth is Zapier's most distinctive feature, and it makes Zapier a common first stop when you need a connector for a niche SaaS product.

How usage is counted

Zapier bills by tasks. According to its help article on how task usage is measured, a task is any successful action that runs in a Zap. Several things do not use tasks:

• Triggers never use tasks, including polling checks for new data.
• Filter and Paths steps do not use tasks.
• Actions that error or halt do not count.

Search actions are an exception: they use a task when set to continue even if nothing is found. Zapier's own example: a Zap with two action steps that runs ten times uses 20 tasks.

The practical consequence is that Zapier's cost scales with the number of action steps multiplied by the number of runs. A long Zap that runs thousands of times a day can use a large number of tasks, while a filter that stops most runs early costs nothing for the stopped runs.

Logic

Zapier supports conditional branching through Paths. The help centre states that each path group can contain up to 10 branches, Paths can be nested up to three levels deep, and a Zap is limited to 100 steps in total, including steps inside paths. That is enough for most business rules, such as routing leads by region or deal size. Workflows that need to iterate over arbitrary lists or handle deeply nested conditions become awkward compared with canvas-based tools.

Code

Zapier is not code-free if you need it to be otherwise. Code by Zapier runs small snippets of JavaScript (Node.js 22) or Python inside a Zap. Its documentation says code runs in a sandbox with limited time and memory, has a 6 MB limit on the combined size of code and data, and allows public npm packages on paid plans. It is meant for small transformations, not for long-running jobs.

Where Zapier fits

Zapier fits teams where the people closest to a process (marketing, sales operations, support) build their own automations. Its step-by-step editor shows sample data from your connected accounts at each step, which lowers the barrier for non-developers.

Documented limits to weigh

• Usage scales with action steps, so long, high-volume Zaps use many tasks.
• Branching is capped by Paths limits; complex iteration needs workarounds.
• It is a hosted service only; data passes through Zapier's cloud.

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Make (formerly Integromat)

Make, originally launched as Integromat in Prague and renamed in 2022, builds automations as scenarios on a visual canvas. Each app action is a module, and modules are connected like a flowchart.

Integrations

Make's integrations directory states a library of 3,500+ applications, according to make.com/en/integrations as of October 2026. That is about a third of Zapier's stated count. For apps without a ready-made module, Make provides generic HTTP and webhook modules that can call any web API, which requires some understanding of how APIs work; our explainer on API basics for no-code automation covers the essentials.

How usage is counted

Make bills by operations, and the counting rule is different from Zapier's. According to Make's help page on operations:

• Each module run that processes or checks data is one operation.
• A module runs once per bundle (data item) it receives.
• Trigger modules count as a single operation per check, regardless of how many bundles they return.

Make's own example: a trigger that returns 10 bundles causes each later module to run 10 times, so a single scenario run can consume 31 operations. The same page notes that operations are also displayed as credits in the scenario editor; check Make's current pricing page for how credits map to plans.

This makes direct price comparisons with Zapier misleading. Make counts the trigger and every module run, including filters and routers in many cases, while Zapier counts only successful actions. Whether one is cheaper depends on how many steps your workflow has and how many items flow through each.

Logic

Make's canvas is designed for non-linear flows:

• A router splits a scenario into several routes, each with its own filter conditions, and supports a fallback route for data that matches no other route, according to Make's router documentation.
• Iterators split an array into separate bundles, and aggregators combine bundles back into one, which makes "for each item in this list" workflows natural.
• Error handlers attach to a module and decide what happens when it fails. Make's documentation lists handlers that skip the failing bundle, save the run for retry, substitute a replacement value and continue, commit work already done and stop, or roll back changes and stop.

Explicit error handling matters more than many beginners expect. An automation that fails silently can corrupt data for weeks before anyone notices; see why automation needs error queues.

Code and data handling

Make provides built-in functions for text, numbers, dates and arrays that can be used inside any field, which covers many transformations without a separate code step. It handles arrays and nested JSON structures natively through bundles and mapping, which is a common reason teams move to Make from simpler tools. For a hands-on walkthrough, see our Make.com automation tutorial.

Where Make fits

Make suits operations people, agencies and analysts who handle data-heavy workflows: processing spreadsheet rows, syncing records between systems with transformations, or running multi-branch approval flows.

Documented limits to weigh

• More concepts to learn (modules, bundles, operations, routers, iterators) before the first useful scenario.
• Smaller integration directory than Zapier, offset by generic HTTP modules.
• Hosted service only; scenarios run in Make's cloud.

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n8n

n8n (pronounced "n-eight-n") was founded in Berlin in 2019. It uses a node-based canvas similar in spirit to Make's, but it is distributed as software you can run yourself as well as a hosted cloud service.

Licence: fair-code, not open source

n8n is often called open source, but its repository describes it as fair-code. According to the n8n GitHub repository, the code is distributed under the Sustainable Use License plus a separate n8n Enterprise License for enterprise features. The source is available and self-hosting is permitted, but the licence restricts some commercial uses, so it does not meet the Open Source Initiative definition. Organisations that plan to embed n8n in a product they sell, or offer it as a hosted service to others, should read the licence text before building on it.

Integrations

n8n's repository README claims 1,500+ integrations, as of October 2026, although the same GitHub page's description line says 400+, so the two figures use different counting rules. Like Make, it offers an HTTP Request node for any API, and it allows developers to write custom nodes.

Self-hosting

n8n's hosting documentation lists several ways to run it: a one-line setup script on Linux or macOS, Docker Compose for production deployments with a database, npm, and guides for major cloud providers. The docs note that npm installation is deprecated from n8n 3.0 and recommend Docker Compose or the setup script instead. Without a licence key, n8n runs as the free Community edition; Business and Enterprise features require a key.

Self-hosting removes per-execution platform fees and keeps workflow data on your own infrastructure, but it moves responsibility to you: TLS certificates, database backups, upgrades, monitoring, credential security and uptime. Our n8n self-hosted guide walks through a Docker setup and the operational trade-offs.

Code

The Code node is n8n's strongest differentiator for technical teams. According to n8n's Code node documentation:

• It runs JavaScript (Node.js) and Python. Native Python became stable in n8n 2, replacing an older Pyodide-based option.
• On self-hosted n8n, you can import built-in and external npm modules once enabled.
• On n8n Cloud, external npm modules cannot be imported; only the crypto module and the moment package are available, and the Python option cannot import libraries.

That difference matters: the "write any code you like" flexibility often cited for n8n applies fully only to self-hosted installations.

A typical Code node step looks like this (illustrative):

// n8n Code node: normalise incoming leads
return $input.all().map(item => ({
  json: {
    name: item.json.name.trim(),
    email: item.json.email.toLowerCase(),
    priority: item.json.company_size > 100 ? 'high' : 'normal'
  }
}));

Where n8n fits

n8n suits developer-led teams, internal tools groups, and organisations with data-residency requirements who already run servers. It is also widely used for orchestrating calls to language models and AI agents, because code nodes make it easy to handle structured model output. Our beginner's guide to n8n workflows covers the editor itself.

Documented limits to weigh

• Self-hosting requires server administration skills and ongoing maintenance.
• The licence is not OSI open source; check it for commercial redistribution.
• Code flexibility is reduced on n8n Cloud.

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Head-to-Head Comparison

Dimension	Zapier	Make	n8n
Stated integrations (vendor page, Oct 2026)	10,304+	3,500+	1,500+ (README)
Billing unit	Task = successful action step	Operation = each module run per bundle	Executions on cloud plans; self-hosted has no platform fee
Do triggers count?	No	Yes, once per check	Not applicable when self-hosted
Editor style	Linear step list	Visual canvas	Visual node canvas
Branching	Paths: up to 10 branches per group, 3 nesting levels	Routers with filters and fallback route	IF / Switch nodes, merges
Lists and loops	Limited	Iterators and aggregators	Item-based processing, loops
Error handling	Errored steps don't use tasks; replay options	Dedicated error-handler modules	Error workflows and retry settings
Custom code	JavaScript or Python, sandboxed, 6 MB I/O	Built-in functions in fields	JavaScript and Python Code node; npm on self-hosted
Self-hosting	No	No	Yes
Licence	Proprietary SaaS	Proprietary SaaS	Sustainable Use License (fair-code)

Sources: vendor documentation linked in each section above, checked October 2026. The n8n error-handling and branching entries reflect its standard nodes; check n8n's docs for current details. Integration counts are self-reported and not directly comparable.

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Why usage units matter more than headline prices

Because the three tools count usage differently, the same workflow can cost very different amounts on each, and the ranking can flip depending on the workflow's shape.

Consider a workflow that runs once for each new order and has five steps: a trigger, a filter, and three actions (create a CRM record, send an email, log a row).

Platform	Counting rule	Usage per run
Zapier	Successful actions only; triggers and filters are free	3 tasks if it passes the filter, 0 if filtered out
Make	Trigger counts once per check; every subsequent module run counts	Trigger check plus each module run per order
n8n self-hosted	No platform usage meter	No platform charge; server cost instead

Now change the workflow so the trigger returns a batch of 50 new rows each time it checks. On Make, every downstream module runs 50 times. On Zapier, each row usually starts its own Zap run, so usage is 3 tasks per row that passes the filter. The way each platform batches data, and whether your filter removes most items early, determine the bill. The only reliable way to compare is to model your real workflow against each vendor's current pricing page, and to read the automation ROI calculator for estimating whether the time saved justifies any of them.

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Reliability practices that apply to every tool

Feature lists rarely mention it, but most automation failures come from design, not the platform:

• Duplicate events. Webhooks can be delivered more than once. Make actions safe to repeat with idempotency keys or "find before create" logic.
• Silent failures. A webhook that stops arriving produces no error at all. Monitor for missing events, not just failed ones; see why webhooks fail silently.
• Human checkpoints. For actions that send money, delete records or email customers, add an approval step; see how approval workflows prevent automation mistakes.
• Ownership. Every automation should have a named owner and a short note explaining what it does, so it can be maintained after the person who built it leaves.

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Other tools worth knowing

The three platforms above are general-purpose, but they are not the only options.

• Microsoft Power Automate is part of Microsoft's Power Platform. According to Microsoft's documentation, it offers cloud flows between apps and services, desktop flows for automating applications on a Windows PC, approvals, and process mining. It is a natural fit for organisations already standardised on Microsoft 365, where it is often licensed alongside other products.
• IFTTT focuses on personal and smart-home automations with simple applet-style triggers. It is not designed for multi-step business processes.
• Scripts and schedulers. For developers, a short script on a scheduler can replace a platform entirely; see Python automation scripts for beginners and how cron jobs differ from workflow automation.
• Browser automation. When an app has no API, tools such as Playwright drive a real browser, at the cost of fragility when the page changes; see browser automation in 2026.

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Decision Framework

Zapier is likely to suit you if:

• The people building automations are not developers.
• You rely on niche SaaS apps and need ready-made integrations.
• Your workflows are mostly linear, with a handful of conditions.
• Usage is moderate, or most runs are filtered out early.

Make is likely to suit you if:

• Your workflows branch heavily or loop over lists of items.
• You want explicit control over what happens when a step fails.
• You are comfortable learning a visual, flowchart-style tool.
• You can model your operation usage and confirm it fits your budget.

n8n is likely to suit you if:

• Your team writes JavaScript or Python and wants code inside workflows.
• Data must stay on your own infrastructure for policy or regulatory reasons.
• You already operate servers and can handle backups, upgrades and security.
• You have checked that the Sustainable Use License fits how you plan to use it.

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Questions to answer before you choose

Before signing up for any trial, write down short answers to these questions. They usually settle the choice faster than a feature checklist.

1. Who will build and maintain the workflows? Business users favour Zapier; developers are often more productive in n8n.
2. How many steps and items per run? Count them, then apply each vendor's billing unit described above.
3. Must data stay on your servers? If yes, only self-hosted n8n of these three qualifies.
4. Which apps are non-negotiable? Search each vendor's directory for them before anything else.
5. What happens when a step fails? Decide whether you need retries, rollbacks or a human alert.

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Migrating Between Tools

There is no standard export format between Zapier, Make and n8n, so migration means rebuilding.

1. Inventory every workflow: trigger, steps, conditions, connected accounts and owner.
2. Rebuild in the new tool, using the migration to simplify. Old workflows often contain steps nobody needs.
3. Run both in parallel for a short period on non-destructive actions, and compare outputs.
4. Switch off the old workflow only after the new one has handled real data correctly, and keep notes of what changed.

Pay special attention to anything that writes data: running two copies of a "create invoice" workflow at once creates duplicates.

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FAQ

Q: Which is easiest for beginners, Zapier, Make or n8n? A: Zapier is generally the most approachable because its editor is a linear list of steps with sample data shown at each stage. Make and n8n use canvases with more concepts to learn, which pays off mainly for complex workflows.

Q: How do Zapier tasks differ from Make operations? A: Zapier counts only successful action steps; triggers, filters and Paths are free. Make counts each module run for each bundle of data, and counts the trigger once per check. The same workflow can therefore use very different amounts on each platform.

Q: Is n8n open source? A: Not by the Open Source Initiative definition. n8n describes itself as fair-code and is released under the Sustainable Use License, which allows self-hosting and source access but restricts some commercial uses.

Q: Can I write code in these tools? A: Yes, to different degrees. Zapier runs sandboxed JavaScript or Python snippets. Make relies mainly on built-in functions inside fields. n8n's Code node runs JavaScript and Python, and self-hosted installations can import npm modules.

Q: Which tool is best for data privacy? A: Self-hosted n8n is the only one of the three that can run entirely on your own infrastructure. Zapier and Make are cloud services, so check their security and data-processing documentation against your requirements.

Q: Can I use more than one tool? A: Yes. Some teams let business users build simple Zaps while engineers run complex workflows in n8n. The cost is split monitoring and ownership, so document which tool owns which process.

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Related Articles

• How to Integrate Tools Without Coding
• How Event-Driven Automation Works

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Bottom Line

Zapier, Make and n8n are all capable platforms; the differences that matter are structural. Zapier offers the broadest integration catalogue and the gentlest learning curve, billing by successful actions. Make provides a visual canvas with routers, iterators and explicit error handlers, billing by every module run. n8n gives technical teams code nodes and the option to self-host under a fair-code licence, in exchange for running the infrastructure themselves. Choose by mapping your actual workflow, modelling its usage under each billing unit on the vendors' current pricing pages, and deciding who on your team will build and maintain it.

Sources

• Zapier app directory
• Zapier: How is task usage measured
• Zapier: Use JavaScript code in Zaps
• Make: Operations
• Make: Router
• Make: Error handlers
• n8n GitHub repository
• n8n: Hosting documentation
• n8n: Code node
• Microsoft Learn: Power Automate

Last verified: October 2026