n8n vs Zapier vs Make - Which Automation Tool Is Best in 2026?

Key Takeaways

• Pick Make if your ops team is not technical but your workflows branch, loop and need error handling.
• Pick n8n if you have an engineer, high volume, or a reason to keep data on your own servers.
• Pick Zapier if it needs to work before lunch and nobody wants to learn a new tool.
• Compare billing models, not feature lists. Zapier charges per step, Make per module, n8n per workflow run.
• None of the three reads a PDF invoice properly on its own. That is a separate job, and it is the one Parseur does.
• Every price, plan and app count below was checked in August 2026, with a source on each number.

Choosing an automation platform looks small in month one and expensive in month twelve. You pick it in an afternoon. Finance asks you about it for the next three years. Pick wrong and you outgrow it, overpay for it, or find out your supplier invoices have been sitting on a cloud your compliance team never approved.

The upside is not in doubt. Gitnux found that 67% of business leaders say workflow automation is essential to their digital transformation, and PS Global Consulting reports that automation can cut repetitive tasks by up to 95% and give teams back as much as 77% of their time. Every vendor in this category will quote you numbers like those. None of them will quote you the downside, which is just as real and simply arrives later, on an invoice.

So this comparison skips the connector-count contest. What decides the answer is how you get billed, where your data is allowed to sit, how much logic the tool can hold, and who on your team is actually going to build the thing. Plus the part most comparisons leave out, which is what happens when the work you want to automate arrives as a PDF stuck to an email.

Who each tool is actually for

If your operations team owns automation and nobody on it writes code, choose Make. It holds real branching logic on a canvas a non-engineer can read, and it bills per module, so building the logic properly does not multiply the bill. For most mid-sized companies, this is the default.

If an engineer owns automation, choose n8n. Execution-based billing, self-hosting, custom code and native AI nodes make it the most capable platform of the three. The condition attached to that is not negotiable. The question is not whether you have an engineer, it is whether you have a few hours of one every month for as long as the workflows keep running.

If business teams own automation and speed matters more than spend, choose Zapier. Nothing gets a non-technical person from idea to working workflow faster, and 9,000+ connectors mean the app you need is almost certainly already there. You pay for that speed in month twelve rather than in month one.

Most companies end up running two of them. Zapier or Make where business teams self-serve, n8n where volume, cost or compliance says otherwise. That is not indecision, it is what happens when three tools price the same work three different ways.

One thing to know before you pick for this quarter instead of next year. Workflows do not port. There is no export from Zapier that Make or n8n will read, so outgrowing a platform means rebuilding on the new one, not migrating to it. Budget a rebuild into the decision, or pick the tool you will still be on in two years.

n8n vs Zapier vs Make at a glance

Figures checked August 2026, from each vendor's own pricing and integration pages. n8n prices in euros because that is how n8n publishes them, so convert before you compare the columns.

Sources: Zapier pricing, Make pricing, n8n pricing, n8n integrations.

Two rows in that table decide more evaluations than all the others combined. Billing unit is why a twenty-step workflow costs the same as a one-step workflow on n8n, and twenty times as much on Zapier. Hosting is why some companies never get to have the conversation at all.

Which tool wins in which scenario

That last row is not filler. It is the one most teams find out about after they have already signed something, and it gets a full section further down.

Zapier

Zapier is the right choice when the person building the automation is not technical and the workflow is mostly linear. It connects more than 9,000 apps through a trigger-and-action model, and it is still the fastest path from an idea to a working automation. If you want the full picture of Zapier's revenue and company scale, we keep a sourced breakdown of the numbers.

A trigger is an event in one app, like a new email in Gmail. An action is what happens next, like creating a task in Trello. String them together and you have a Zap.

Where Zapier wins

Breadth, first. Nine thousand connectors means the obscure tool your sales team refuses to give up is probably already supported, and you will not be writing an HTTP request to find out. Zapier also has the best documentation and the largest template library in the category, and that library matters, because most business users start from a template rather than a blank canvas.

Second, nobody needs training. The editor makes sense on first contact. For a company where automation lives in marketing, sales and support rather than in engineering, that is worth paying for.

Where Zapier gets expensive

Every step in every Zap is a billable task, including the filters and formatters that do nothing visible. Branch or loop, and the counter runs faster than anyone budgeted for. The bill scales with complexity rather than with value, which is the single most common reason teams migrate off Zapier.

Cloud-only hosting is the other blocker. There is no self-hosted option, so every payload runs through Zapier's infrastructure. If your compliance team has a view about where invoice data can live, that view will end the evaluation.

And complexity has a ceiling. Zapier can branch, but a workflow with several conditional paths gets hard to read and harder to debug next to what Make or n8n show you on a canvas.

Make

Make is the right choice when your workflows are complicated but your team is not technical. If you have been searching Make.com vs Zapier, this is the section that answers it. Formerly Integromat, Make replaces the linear step list with a visual canvas where each step is a module and each workflow is a scenario, and it charges per module rather than per step.

Make users automated the equivalent of 331 years of manual work in 2021 alone, back when the catalog held around 629 apps. It has since passed 3,000 apps, plus 350+ AI apps.

Where Make wins

The canvas. Seeing a workflow laid out in space, with branches that fork and rejoin, changes what a non-engineer can build. Routers, filters, iterators, error handlers, and not one of them needs code.

Array handling is the underrated part. When a workflow has to loop over the line items on an invoice or the rows in a report, Make does it natively and legibly. Zapier makes you fight for the same result.

Then price. At $12 a month for 10,000 credits, a complex Make scenario costs a fraction of the same logic on Zapier. For a growing company running real business processes rather than Slack notifications, this is usually where the money argument lands.

Where Make asks more of you

It is not beginner software. Powerful, yes, but the first scenario takes longer to build than the first Zap, and mapping data between modules is where new users get stuck.

It is also cloud-only, with the same consequence as Zapier. No self-hosting, and no data residency choice beyond EU servers.

And the connector library, large as it is, is a third the size of Zapier's. For mainstream business tools this never bites. For niche or regional software, check before you commit.

Make vs n8n usually comes down to one question, and it is not a technical one: do you have an engineer with time to spare? If yes, n8n does more for less. If no, Make is as far up the complexity ladder as you can safely go.

n8n

n8n is the right choice when somebody technical owns automation, or when the data cannot leave your building. It is a fair-code platform built around a node-based editor, and unlike Zapier and Make it can run entirely on your own infrastructure.

The company behind it has grown fast. n8n reports over 230,000 active users and more than 3,000 enterprise customers, and in May 2026 SAP took a strategic investment that doubled n8n's valuation to $5.2 billion, with plans to embed the platform inside SAP's Joule Studio. Whatever else that signals, it means you would not be betting your operations on a side project.

Where n8n wins

Billing, first. n8n charges per workflow execution, not per step, so a twenty-node workflow costs what a one-node workflow costs. Once your automations get complicated, that is the difference between a bill that grows with usage and one that grows with ambition.

Self-hosting, second. The Community Edition is free and runs on your own server, which means document contents, credentials and execution logs stay inside your network. For finance, healthcare, legal and anyone with a data residency clause, this is not a nice-to-have.

Third, it is the most AI-native of the three, with built-in nodes for LangChain, the major model providers and agent orchestration rather than one prompt step bolted on the side.

And a small detail that settles a surprising number of arguments. Every n8n plan includes unlimited users. Zapier's Team plan stops at 25. If you are shopping n8n alternatives because of that ceiling, you are shopping the wrong way round.

What n8n asks in return

A learning curve, for a start. n8n assumes you are comfortable with JSON, APIs and the occasional line of JavaScript. Hand it to a marketing coordinator and it will not go well.

Self-hosting is free the way a puppy is free. Upgrades, backups, monitoring, scaling and incident response all land on somebody's calendar, and "we saved on the subscription" stops being true the moment that person's time is priced in.

Governance sits high on the plan ladder. SSO, version control through Git and multiple environments start on the Business plan at 667 euros a month, a steep step up from Pro at 50 euros.

Zapier vs n8n is the comparison most teams run twice: once when they pick Zapier, and again eighteen months later when the bill arrives. Running it once, properly, is cheaper.

And it is source-available, not open source. n8n ships under the Sustainable Use License, so you can read, modify and self-host the code for your own business, but you cannot resell it as a competing service. Useful transparency. Not the freedom the words "open source" imply.

The differences you notice in month twelve

Connector counts are not what you are choosing between. You are choosing how workflows get built, how they behave under load, and who is allowed to touch them. Deloitte found that 79% of CEOs are chasing efficiency gains through automation and that more than half are after the data those workflows generate, which is a polite way of saying the workflows you stand up this quarter become a reporting dependency next year. That is why the details below matter more than the connector count above.

Building workflows

Zapier gives you a linear chain of triggers and actions, which is easy to read and limited when the logic branches. Make gives you a canvas with forks, merges and error routes, the sweet spot for business processes. n8n gives you a node graph plus the ability to drop into code whenever the visual layer runs out of road.

Triggers and latency

All three fire instantly on webhooks. The difference shows on polling triggers, where the platform has to check an app for changes. Zapier's polling interval shortens as you move up plans. Make's free tier is capped at a 15-minute minimum interval and drops to one minute on paid plans. Self-hosted n8n runs on whatever schedule you configure, which is the only option here that tunes latency to the workload rather than to the invoice.

Governance and compliance

Zapier and Make are cloud-only. That removes infrastructure work, and it removes your control over where data lives. Of the two, Zapier holds the more established compliance certifications, including SOC 2, and publishes them openly.

n8n self-hosted inverts the model: no vendor certification to lean on, and no vendor in the data path either. Which of those your auditor prefers is worth establishing early, because it is not a question you can answer after you have built forty workflows.

What happens when it breaks, and when it grows

The question nobody asks in a demo is who you call at 11pm when a workflow stops silently. Zapier answers it with the deepest documentation in the category and staffed support on paid plans. Make sits in the middle, with strong tutorials and an active community forum. On self-hosted n8n the answer is you, backed by a GitHub and Discord community that will help generously provided you can already read a stack trace.

Growth splits the same way. Zapier scales in capability and charges you for the privilege. Make holds up on both counts right until a workflow needs something the canvas cannot express. n8n scales as far as your infrastructure does, which is either liberating or alarming depending on whether anyone is watching it.

Pricing and value for money

Three platforms, three billing units, and that is the whole story. Prices below are from each vendor's pricing page and were checked in August 2026. Automation vendors reprice often, so verify before you sign anything.

Zapier pricing

Zapier bills per task, where every action in a workflow counts as one, including filters and formatting steps.

• Free: $0/month, 100 tasks, two-step workflows, unlimited Zaps
• Professional: from $19.99/month, multi-step Zaps, premium apps, webhooks
• Team: from $69/month, 25 users, shared folders and connections, SAML SSO
• Enterprise: custom, unlimited users, advanced permissions, observability, technical account manager

Note the word "from" on those tiers. Each one is the entry rung of a volume ladder, and the price climbs with the task allowance you pick. Zapier also prices its AI agents separately, at $33.33/month for 1,500 agent activities. Source: zapier.com/pricing.

Make pricing

Make bills per credit, where each module action, trigger or function consumes one.

• Free: $0/month, 1,000 credits, 3,000+ apps, 15-minute minimum run interval
• Core: $12/month for 10,000 credits, unlimited active scenarios, Make API
• Pro: $21/month for 10,000 credits, priority execution, custom variables, log search
• Teams: $38/month for 10,000 credits, team roles, shared scenario templates
• Enterprise: custom, enterprise apps, custom functions, 24/7 support, overage protection

Core, Pro and Teams all start at the same 10,000 credits, so what you buy by moving up the ladder is capability, not volume. Credits are chosen separately and priced on top. Source: make.com/en/pricing.

n8n pricing

n8n bills per workflow execution, with unlimited steps inside each one, and every plan includes unlimited users.

• Community Edition: free, self-hosted, you pay only for the server
• Starter: 20 euros/month, 2,500 executions, 5 concurrent, 2,300 AI credits
• Pro: 50 euros/month, 10,000 executions, 20 concurrent, admin roles, workflow history
• Business: 667 euros/month, 40,000 executions, self-hosted option, SSO and SAML, Git version control, multiple environments
• Enterprise: custom, 200+ concurrent executions, external secret store, log streaming, dedicated SLA

There is also a startup plan at 50% off Business for companies under 20 employees. Source: n8n.io/pricing.

Note the shape of that ladder. n8n is the cheapest way to run a lot of complexity and the most expensive way to buy SSO. Budget for the tier you will need next year, not the one that covers this quarter.

The number to put in front of your CFO

Not the monthly price. Cost per thousand finished jobs, at the workflow length you actually run.

Take one real workflow, count its steps, and multiply by the volume you expect a month. On Zapier that multiplication is the bill, because every step is a task. On Make it is roughly the module count, which is usually smaller and always cheaper per unit. On n8n the step count drops out of the sum entirely, because the run is what gets counted. Do that arithmetic once, on a workflow you already have, and the winner usually stops being a matter of opinion.

Two things fall out of it. Short workflows make Zapier look reasonable. Long ones make it look like a subscription to your own inefficiency.

What all three get right

They dominate this category for reasons that have nothing to do with their differences. A non-developer can build something useful on any of them on day one, whether the model is trigger-and-action, a visual canvas or a node graph. All three connect Gmail, Slack, HubSpot, Salesforce and Sheets natively, and speak webhooks and HTTP where a native connector is missing. Free tiers are generous enough to prove the concept and tight enough to make you pay once it works, and every one of them leaves a door open for a developer to add custom code or a custom integration.

None of that is a tiebreaker. It is the floor, and it is why the rest of this page is about billing, hosting and who owns the thing instead.

When to use each, by team

Marketing and sales teams, choose Zapier

Leads from Facebook Ads into a CRM. Webinar signups into Mailchimp. A Slack alert when a deal closes. The app library and the templates mean these ship in an afternoon, with no IT ticket in the way.

Growing SMBs and ops teams, choose Make

Multi-step order processing, routing support tickets by category, syncing inventory across CRM and accounting. The canvas holds the branching, the error handlers catch what breaks, and the bill stays sane.

Engineering, IT and regulated industries, choose n8n

Internal systems under compliance constraints, mission-critical workflows with custom logic, and volumes where per-task pricing would be absurd. Self-hosting keeps healthcare, finance and government workloads where the auditor expects to find them.

The part every comparison skips, getting your documents in

Ask any of these platforms to connect two APIs and they will do it beautifully. Ask them to read a supplier invoice that arrived as a scanned PDF stuck to an email, and you meet the gap.

Zapier, Make and n8n are orchestrators, not extractors. They decide what happens next. They were never built to read a document whose layout changed last quarter. People try anyway, with regex on email bodies, brittle text-splitting, or a prompt bolted onto an AI step. Those workarounds hold up right until a vendor redesigns their invoice template, which is usually a Tuesday.

The architecture that holds up puts extraction in its own layer:

Email or PDF arrives
        ↓
Document parser extracts the fields
        ↓
Validation and confidence check
        ↓
Zapier / Make / n8n routes the data
        ↓
ERP, accounting system, CRM, database

The automation platform orchestrates. The parser reads. Keeping those jobs apart is what stops a new invoice format from becoming a workflow rebuild.

What you should be extracting

For invoices, the fields worth pulling are consistent across almost every finance stack:

vendor name, vendor address, vendor tax ID, invoice number, invoice date, due date, currency, subtotal, tax, shipping and fees, total, purchase order number, payment terms, remittance details, and the line items, each with description, item code, quantity, unit price, tax and line total.

Normalize vendor names, dates, currencies and PO numbers before anything reaches your accounting system, and route anything below your confidence threshold to a human queue rather than into the ledger.

What this changes about the platform decision

It simplifies it. Once extraction lives upstream, your workflows get shorter, which directly lowers what Zapier and Make charge you, since both bill by the step. And the tool choice stops hinging on which platform has the least-bad PDF handling, because none of them is doing that job any more.

How Parseur works with Zapier, Make and n8n

Parseur is the extraction layer in that diagram. It takes emails, PDFs and scanned documents, pulls out the fields you define, and hands your automation platform clean structured JSON. There is a native Parseur app in Zapier, a native module in Make and a native node in n8n, so connecting them is configuration rather than a project.

The setup effort that remains is teaching the parser what your documents look like. That is where the hours go, and it is the right place for them, because it is the one part of this pipeline none of the three platforms will do for you.

Parseur and Zapier

Parseur extracts the data, sends it to Zapier, and Zapier routes it across its 9,000+ connectors. Teams use this to update spreadsheets from email alerts, push new leads into a CRM from form notifications, send invoice details straight to accounting tools, and stop copy-pasting between tabs.

Step-by-step setup: Extract text from emails and PDFs in Zapier.

Parseur and Make

Parsed data lands in Make as a trigger, and from there filters, routers and conditional logic take over across 3,000+ apps. Real estate teams run lead capture this way, recruiters run candidate pipelines, and e-commerce teams run order processing, which is the same shape as an invoice on its way to accounting. And yes, one customer runs their book club on it, with a Google Alert for "Harry Potter" filing itself into Notion while they get on with the actual reading.

Step-by-step setup: Send data extracted from emails and PDFs to Make.

Parseur and n8n

Parseur delivers structured JSON to n8n through the native node, or by webhook for self-hosted instances. That last detail is the point. On a self-hosted setup, the document contents and the extracted data stay inside your own infrastructure end to end.

The common build is invoice processing. Parseur pulls vendor, date, totals and line items out of incoming PDFs, and n8n pushes them into Google Sheets or an ERP, with branching, custom logic and a human approval step where the amounts justify one.

Step-by-step setup: Send data extracted from emails and PDFs to n8n.

Where these platforms are heading

All three are chasing the same thing, which is agents that decide rather than workflows that execute. Zapier sells agent activities as a separate line item. Make has folded AI apps into its catalog. n8n has gone furthest, with native LangChain and model-provider nodes, and now SAP's backing to push it into enterprise stacks.

None of that changes the input. An agent reasoning over your accounts payable still needs the invoice as structured data before it can reason about anything at all, which is why feeding agents clean structured data sits underneath all of these platforms rather than inside any one of them.

If Microsoft is already in your stack, the fourth option is worth a look too. We compare Zapier, Make and Power Automate separately.

So, which automation tool is best for you?

Make for most mid-sized companies, because it holds real complexity without demanding an engineer and without Zapier's bill. n8n when you have technical ownership, high volume, or data you cannot hand to a vendor, which is also where the category's momentum currently sits. Zapier when time-to-first-automation is the metric that matters and budget is not the constraint.

Pick by who is building, not by feature count. That one question settles most of these evaluations in about a minute.

And whichever you choose, sort out the documents first. Emails, PDFs and scans are where most manual data entry still hides, and no amount of workflow logic saves a workflow that starts with somebody retyping an invoice.

Last updated on August 6th, 2026