n8n vs. Make.com: Which Tool Fits You?

Choosing the right automation tool can make the difference between success and frustration. In this article, we compare two of the most popular platforms: n8n and Make.com. Both have evolved significantly in recent months – especially around AI. We break down where the differences really matter in practice: hosting, costs, data privacy, and AI agents.

n8n Overview

n8n is an open-source automation platform that can be self-hosted or used as a cloud service. Founded in 2019, it has quickly built a loyal community.

Strengths of n8n:

• Open source with self-hosting option
• No limits on workflows or executions (self-hosted)
• Strong code integration (JavaScript/Python)
• Full control over data with self-hosting
• Native AI agent nodes for LLM workflows
• Active community and regular updates

Weaknesses of n8n:

• Self-hosting requires technical expertise
• Fewer native integrations than Make.com
• Steeper learning curve for non-developers

Make.com Overview

Make.com (formerly Integromat) is a cloud-based automation platform with a visual workflow builder. It has been around since 2012 and is known for its user-friendly interface.

Strengths of Make.com:

• Intuitive visual interface
• Over 2,000 native integrations
• No technical setup required
• Good error handling and debugging tools
• Extensive template library

Weaknesses of Make.com:

• Costs increase with usage (operations-based)
• No self-hosting option
• Less flexible for complex code requirements

Head-to-Head Comparison

The following table summarizes the most important differences – from hosting and pricing model to the AI capabilities of both platforms.

When Is n8n the Right Choice?

n8n plays to its strengths wherever control, volume, and flexibility matter. These are the scenarios in which we typically recommend n8n in our projects:

• Data privacy and data sovereignty are top priorities: customer, HR, or financial data must not leave your company – self-hosting on an EU server keeps everything under your control.
• High execution volumes: your workflows process hundreds or thousands of records per day – with self-hosting, there are no usage-based extra costs.
• Custom code is part of the job: your automations need JavaScript or Python logic, custom API calls, or complex data transformations.
• AI agents are on the roadmap: you want to build AI workflows with a free choice of models, without sensitive data passing through third parties.

You do need to handle operations, in-house or through a partner. Whether your own server or n8n Cloud fits better is what our guide n8n self-hosting vs. cloud explores in detail.

When Is Make.com the Right Choice?

Make.com shines when speed matters and nobody wants to run a server. Typical scenarios where Make is the better choice:

• Fast start without setup: your first automation should go live this week – without a server, maintenance, or an IT project.
• Business teams automate on their own: marketing, sales, or back office build and maintain scenarios themselves – the visual interface lowers the entry barrier considerably.
• Connecting many SaaS tools: CRM, newsletter tool, accounting, and project management – with over 2,000 native apps, almost everything connects without workarounds.
• Moderate, predictable volumes: your workflows run a few hundred times per month – keeping operations costs easy to calculate.

Costs in Practice: A Sample Calculation

On paper, both tools look inexpensive – what matters is how your usage develops. A sample calculation: a workflow that processes invoices typically consists of 10 to 20 individual steps. In Make, each of these steps counts as an operation. If the workflow runs 1,000 times a month, that quickly adds up to 10,000 to 20,000 operations – and with every additional workflow, the plan you need to book grows.

With n8n, the workflow execution counts as a whole – and with self-hosting, usage-based costs disappear entirely. In return, you budget for a small cloud server (typically a low double-digit euro amount per month) plus effort for updates and monitoring. As a rule of thumb: with a few lean automations, Make is usually cheaper; with many high-volume workflows, the math typically tips in favor of n8n. Our pricing overview shows what setup and managed operations by Lyron cost.

Can You Have Both? Combining n8n and Make

The two platforms are not mutually exclusive. A proven pattern: data-critical processes such as invoice or HR workflows run on a self-hosted n8n instance, while non-critical marketing automations stay in Make. Webhooks can even connect both worlds directly. What matters is a clear rule about which data categories belong in which tool – otherwise you end up with hard-to-maintain sprawl.

Conclusion

Both tools are excellent automation platforms. The right choice depends on your specific requirements. At Lyron, we work with both platforms and are happy to advise you on which solution is best suited for your company.

Frequently asked questions about n8n vs. Make

Is n8n really free?

n8n's Community Edition is license-free when self-hosted – there are no per-execution fees. Running it still isn't free of cost: you pay for a server, setup, updates, and monitoring in money or working time. If you prefer not to self-host, n8n Cloud is available as a monthly subscription.

Which tool is more GDPR-compliant?

Both platforms can be operated in a GDPR-compliant way. With self-hosted n8n, all data stays on your own infrastructure, for example on a server in the EU. Make processes data in the vendor's cloud but offers EU data centers and a data processing agreement. For particularly sensitive data, self-hosted n8n is typically the cleanest solution.

Can I switch from Make to n8n later?

Yes, switching is possible at any time – but there is no automatic import. Workflows are rebuilt in n8n. In practice, migrations typically happen step by step: high-volume processes first, then the rest. The rebuild is often a good opportunity to clean up processes that have grown over time.

Which tool is better suited for AI agents?

For AI agents, n8n currently offers the more mature building blocks: native agent nodes, a free choice of models, and the option to keep sensitive data in-house via self-hosting. Make is continuously expanding its AI features and works well for pre-structured AI steps within existing scenarios.