In the n8n vs Make vs Zapier comparison there is no universal winner. Zapier is the easiest to get started with and has a very large catalogue of apps, Make offers a powerful visual editor for scenarios with many branches, and n8n can be hosted on your own server and gives the most technical control. The right choice depends on who builds the workflows, what data passes through them and how complex they are.
All three essentially do the same thing: they connect the apps you already use (CRM, email, forms, online store, invoicing, spreadsheets) and move information between them automatically, following rules you set. The differences lie in details that matter a great deal after the first few months: how cost is calculated, where data is processed, how easily you can spot an error and who can maintain the workflows when the person who built them is no longer available.
In short
Zapier: the most accessible for non-technical teams and simple workflows. Make: a rich visual editor, good for scenarios with many conditions and data transformations. n8n: a self-hosting option, code where needed and control over data, at the price of greater technical responsibility. Test your real workflow on the chosen option before moving all your processes.
What n8n, Make and Zapier are, in brief
They are workflow automation platforms, sometimes called “no-code” or “low-code” platforms, meaning tools in which you build automations from visual blocks, with little or no code. A workflow starts with a trigger (for example, “a new form has arrived”) and continues with a series of actions (create the contact in the CRM, send an email, notify the team in chat).
- Zapier calls its workflows “Zaps”. It is a cloud service, designed to be used quickly by people without technical training.
- Make, formerly known as Integromat, calls its workflows “scenarios”. It is also a cloud service, with a visual editor in which you see the workflow as a map of connected modules.
- n8n calls them “workflows”. It can be used as a cloud service offered by n8n or installed on your own server, managed by you or by a provider.
Hosting: cloud or your own server?
This is the biggest structural difference. Make and Zapier are SaaS (software as a service) products: the platform runs on the provider's infrastructure, and you simply log in and build. There is nothing to install or update, but you also do not control where and how it runs.
n8n can be used both ways. The version hosted by n8n is similar in experience to the other two. The self-hosted version means you install n8n on a server of your choice, including in a data centre in the European Union or on your business's own infrastructure. n8n's licence is “fair-code”, called the Sustainable Use License: the source code is available and you can use the platform for your business's internal needs, but there are restrictions if you want to offer it to others as a commercial service. Some advanced features are available only with an enterprise licence.
Self-hosting is not free in terms of effort, though. Someone has to look after server security, updates, backups and monitoring. If you have no one to take on these tasks, the cloud version is usually safer than an unmaintained server.
How cost is calculated on n8n, Make and Zapier
We do not give figures, because these platforms' plans and prices change often. Always check the official pricing page. What is worth understanding is the unit of measurement, because it decides how much a workflow costs you as volume grows.
- Zapier charges, in principle, by the number of “tasks”, meaning successful actions performed by workflows. A workflow with five actions uses more than one with a single action.
- Make measures usage by the steps executed in scenarios (operations or credits, depending on the plan). Every module that runs uses up allowance, and scenarios that frequently check for new data can use it even when they find nothing.
- n8n Cloud charges by the number of workflow executions, regardless of how many steps a workflow has. In the self-hosted version, the main cost is the server and administration time, not execution volume.
In practice, short and infrequent workflows cost little anywhere. The differences become significant when you have long workflows with many steps that run hundreds or thousands of times. For an accurate estimate, count how many times the workflow is triggered per month and how many steps each run has, then calculate using each platform's model. Also factor in the time to build and maintain the workflows, which often exceeds the subscription.
Where data goes and what it means for GDPR
Personal data often passes through automations: names, emails, phone numbers, orders, sometimes documents. From a GDPR point of view, the automation platform usually becomes a processor (a provider that processes data on your behalf), so you need a data processing agreement and clarity about where data is processed and stored.
- Check the hosting region. Some providers let you choose an EU region; others process data mainly outside the European Economic Area, in which case the transfer mechanisms set out in the contract matter.
- Read the list of sub-processors and the data processing agreement published by the provider.
- Execution history often keeps the data that passed through the workflow. Decide how long it is kept and who can see it.
- Minimise data: send only the fields you need through the workflow, not the whole CRM record.
- With self-hosted n8n, data stays on the server you choose, but responsibility for protecting it rests entirely with your business.
Important limitation
This guide is for information only and does not constitute legal advice. Data protection rules and their interpretation can change. For your business's specific situation, consult the text of the Regulation on EUR-Lex, the guidance from ANSPDCP (the Romanian data protection authority) and, where appropriate, a data protection specialist. Information about providers is valid at the time of writing (October 2026) and must be checked against their official documents.
Complexity: how easy it is to build and maintain workflows
Zapier has the gentlest learning curve. You build step by step, in a vertical list, and most people used to web apps manage to create their first workflow without help. As you add conditions and branches, however, workflows can become hard to follow.
Make shows the workflow as a diagram, with modules, routes, filters and tools for processing lists of data. It is very well suited to scenarios with many branches and transformations, but takes a bit longer to learn, especially when working with lists and data structures.
n8n also has a visual editor, but it is designed for people comfortable with technical concepts: data in JSON format, API calls, expressions. It lets you add code (JavaScript and, in some configurations, Python) directly in the workflow, which solves the cases where other platforms get stuck. On the other hand, a non-technical team will find it harder to manage on its own.
AI steps in automations
At the time of writing, all three platforms let you integrate large language models (LLMs) into workflows: classifying an email, extracting data from text, summarising a request or drafting a suggested reply. The specific features evolve quickly, so check each one's current documentation.
- Zapier and Make offer modules for popular AI providers and their own AI features, easy to add to an existing workflow.
- n8n has dedicated nodes for AI agents, memory, tools and vector databases, useful when you build more elaborate AI workflows.
- Whatever the platform, the AI step can get things wrong. For actions with consequences (an email sent to a customer, a change in invoicing), add a human approval step.
- Data sent to an AI model reaches yet another provider. Include that provider in your GDPR analysis too.
Error handling: what happens when a step fails
Every automation will fail at some point: an app is unavailable, a field comes through empty, a password expires. The difference between a toy workflow and a reliable one is what happens then.
- Zapier flags failed runs, sends notifications and lets you replay them; higher-tier plans have additional automatic replay options.
- Make has dedicated error-handling routes on each module, with options such as ignoring, retrying or stopping the scenario, plus storing incomplete executions for later resolution.
- n8n lets you define a separate workflow that starts when another workflow fails, for example to alert the team, plus configurable retries on nodes.
Practical tip
For every important workflow, decide from the start who receives the alert when something goes wrong and what that person does. A workflow that fails silently is more dangerous than having no automation at all, because everyone believes the job has been done.
n8n vs Make vs Zapier compared, criterion by criterion
- Hosting: Zapier and Make cloud only; n8n in the cloud or on your own server.
- Licence: Zapier and Make are closed commercial services; n8n has a fair-code licence, with source code available and restrictions on resale.
- Cost unit: Zapier by successful actions; Make by steps executed; n8n Cloud by executions, and self-hosted by server and administration.
- Ease of use for non-technical people: Zapier easiest, Make medium, n8n the most technical.
- Complex workflows and data transformations: Make and n8n are better suited than Zapier.
- Custom code: possible in all of them, but most natural in n8n.
- Control over where data lives: greatest with self-hosted n8n; with Make and Zapier it depends on the provider's options.
- Catalogue of ready-made integrations: Zapier has the widest catalogue; for apps without an integration, all of them offer HTTP calls to APIs.
Which platform to choose: n8n, Make or Zapier?
- Choose Zapier if your team is non-technical, your workflows are relatively simple and you want to get started quickly with popular apps. It is not the best choice for long, high-volume workflows, where the cost per action rises quickly.
- Choose Make if you have processes with many conditions, or lists of products or orders to process, and you want to see the whole workflow on a single diagram. It is less suitable if you strictly need the platform to run on your own infrastructure.
- Choose n8n if you have strict requirements about where data lives, want to combine automation with code and AI, or already have someone who can manage a server. It is not suitable if no one in the business or among your providers can take on the technical maintenance.
You do not have to choose a single platform forever, but it is not advisable to have workflows scattered across three places either. Start with one clear process, document it, test it on the chosen platform and only then expand.
We work with n8n and Make, and we also build custom integrations where no-code platforms fall short. We start from your process, not from the tool: we look at what data passes through the workflow, its volume and who will maintain it, then recommend the right option and document it. If you would like a second opinion before you choose, an initial conversation is a good starting point.
Next steps