Self-Hosted n8n vs Zapier vs Make: Which Automation Platform Fits You?

You want to stop copying data between systems by hand. Three names come up again and again: Zapier, Make and n8n. Each one connects your apps and runs workflows, and each one now has AI features. So which should you pick?

Choosing badly is expensive in a quiet way. A tool that is too simple leads to fragile workarounds. A tool that is too technical sits unused. A pricing model that does not match your volume grows into a large bill. This guide gives you a fair comparison, written by a team that builds on all three.

The short answer

• Choose Zapier if non-technical staff will build simple workflows themselves and want the widest range of ready-made app connections.
• Choose Make if you want a visual builder with more control over branching and data handling, still without running servers.
• Choose self-hosted n8n if your workflows touch sensitive data, need custom code, run at high volume, or must stay on your own infrastructure. You also need someone to maintain it.

Side-by-side comparison

Factor	Zapier	Make	Self-hosted n8n
Hosting	Vendor cloud	Vendor cloud	Your server or private cloud (a vendor cloud option also exists)
Pricing model	Plan plus usage, counted in tasks	Plan plus usage, counted in operations or credits	Your infrastructure and maintenance time; licence terms apply
Where data lives	Passes through the vendor	Passes through the vendor	Stays in your environment, except calls you choose to make
Ease for non-technical users	Easiest	Moderate	Moderate to technical
Custom code	Supported in code steps	More limited; check current options	Code nodes and custom nodes, very flexible
AI features	Built-in AI steps and agents	Built-in AI modules and agents	AI and agent nodes, plus any model you can reach, including private ones
Maintenance	Handled by vendor	Handled by vendor	Your responsibility: updates, backups, monitoring

Features and plans change often. Treat this table as a starting point and check each vendor's current pricing pages and documentation before you decide.

Pricing model: usage versus infrastructure

Zapier and Make charge a subscription that includes a set amount of usage. Zapier counts tasks. Make counts operations, and its units have changed over time. A workflow with many steps, or one that runs on every new record, uses more units. Costs grow with volume.

Self-hosted n8n works differently. You pay for the server, plus the time to run it, and you must follow its licence terms. Usage volume matters much less. That makes it attractive for high-volume workflows, but the maintenance time is a real cost. Count it honestly.

We are not quoting figures here because they change. Model your expected monthly runs against each vendor's current pricing page.

Data privacy and where your data lives

With Zapier and Make, your data passes through the vendor's cloud. Both publish security and compliance information, and for many businesses that is entirely acceptable. Review their data processing terms and hosting regions against your own obligations.

With self-hosted n8n, workflows run in your environment. Data only leaves when a step sends it somewhere, such as an AI model API. You can go further and use a private model, so even the AI step stays in-house. Our private on-device AI case study shows that approach for a regulated client. For regulated data, this control is often the deciding factor.

Flexibility and custom code

Zapier is designed for straightforward, mostly linear flows. It supports code steps, but complex logic gets awkward. Make's visual canvas handles branching, loops and data mapping well. For deeper custom logic, check Make's current options.

n8n is the most flexible of the three for engineers. Code nodes let you transform data freely, and you can build custom nodes for internal systems. It also handles long-running, multi-step processes well. See the approval flows in our article on AI agents with n8n, MCP and human approval.

AI features

All three platforms have added AI steps and agent features. For a simple job, such as summarising a form submission, any of them will do.

The differences appear with more serious AI work. You may need control over prompts, structured outputs, retries and confidence thresholds. You may need a private model, or retrieval over your own documents. n8n gives the most control here, because you can call any API and run code around the AI step.

Maintenance burden

This is where Zapier and Make shine. The vendor runs the platform, applies updates and keeps it available. You only maintain your workflows.

Self-hosting n8n means someone must apply updates, back up the database, monitor the server, secure access and handle failures. If nobody owns that, do not self-host. A managed n8n setup run by a partner, or n8n's own cloud offering, are middle-ground options.

A note on n8n's licence

n8n is "fair-code", not traditional open source. It uses the Sustainable Use License. Broadly, it allows internal business use and self-hosting, but restricts some commercial uses, such as offering n8n itself as a service. Licence terms can change and edge cases matter. Read the current licence and n8n's documentation, and check whether your use case is covered. Embedding it in a product you sell, or running it for clients, are the cases to check most carefully.

Who should pick which

Pick Zapier when

A marketing or operations team wants to connect common SaaS apps quickly. Workflows are simple, volume is modest and data is not sensitive.

Pick Make when

You need richer logic and data handling than Zapier makes comfortable. Someone on the team is happy with a more technical visual builder.

Pick self-hosted n8n when

Workflows handle customer, financial or health data, or need custom code. They may call private AI models or run at volumes where usage-based pricing hurts. You also need an owner for the server. Most of the automations in this series run on it, from lead follow-up with n8n and Telegram to automated KPI reports.

Mixing is fine too. Many companies keep simple Zapier flows and move sensitive or high-volume work to n8n.

Questions to ask before you choose

• Who will build and change the workflows, and how technical are they?
• What is the most sensitive data any workflow will touch?
• Roughly how many runs a month do you expect in a year's time?
• Who will be alerted, and who will fix it, when a workflow fails at night?
• Will you ever run these workflows for clients or inside a product you sell?

How UnlockLive can help

Through our AI Workflow Automation service we help you choose, then build and run the workflows. That includes a hardened self-hosted n8n setup with backups and monitoring where it fits. For agent-style workflows that take actions in your systems, see our AI agents development service. If you are still deciding whether to automate with off-the-shelf tools at all, read our build vs buy guide for AI automation.

Not sure which platform fits? Book a free 30-minute call and bring a list of the workflows you want to run.