Zapier vs Make vs n8n: The 80/20 Comparison

If you’re looking into workflow automation, you’ve probably seen these three names everywhere: Zapier, Make, and n8n.

They all do the same thing on paper. Connect your apps. Automate repetitive tasks. Stop copy-pasting data between systems.

But picking the wrong one can cost you months of frustration or thousands in unnecessary fees.

Here’s the thing nobody tells you upfront: there’s a trade-off triangle at play.

• Ease of use (learning curve)
• Price (especially at scale)
• Capabilities (what you can actually build)

You can optimize for two. Not all three. Let me break down which platform wins where.

The Quick Overview

Zapier: The Gateway Drug

Zapier built its entire business on being easy. The interface is a linear, fill-in-the-blanks wizard. Pick a trigger, pick an action, done.

It’s where most people start. If you’ve never built an automation before, Zapier will get you from zero to working workflow in 15 minutes. The learning curve is basically flat.

Its real strength is the ecosystem. Nearly 8,500 app integrations. If a SaaS tool exists, Zapier probably connects to it. This matters when you’re dealing with niche industry software that smaller platforms don’t support.

The downside? Pricing gets brutal as you scale. Every action in your workflow counts as a “task,” and tasks add up fast. More on that below.

Make: The Sweet Spot

Make (formerly Integromat) takes a different approach. Instead of a linear list, you get a visual canvas where you drag and drop modules and literally see data flowing between them.

This makes complex workflows much easier to build and debug. Branching logic, error handling, multiple paths. It’s all visible on the canvas.

Make sits at an inflection point. Technical enough to handle real complexity. Visual enough that non-developers can learn it. They’ve also added JavaScript and Python code modules recently, plus an HTTP module for connecting to any API. If you’re willing to learn it, you can build almost anything—and you don’t need to be a developer.

The main trade-off is fewer pre-built integrations than Zapier (around 2,000 vs 8,500). But for mainstream apps, it covers most of what you need.

n8n: The Developer’s Choice

n8n is open-source and can be self-hosted. That’s the headline feature.

It uses a node-based editor similar to tools in game development or visual effects. Each step is a node. You connect them however you want. You can write JavaScript or Python directly in the workflow and have full control over the execution.

The learning curve is real. n8n is more reserved for people with some programming background or at least comfort with technical concepts. If you’ve never touched code, you’ll struggle.

But if you’re willing to climb that curve, the payoff is significant. You get maximum flexibility, the ability to self-host (meaning your data never leaves your infrastructure), and dramatically lower costs at scale.

n8n has also become the go-to platform for building AI agents. If you’re doing anything with autonomous AI workflows, the community and tooling around n8n for this use case is ahead of the others.

The Pricing Reality

This is where the differences really show up. And the gaps are larger than most people realize.

Zapier: Pay Per Task

Every action in your workflow costs you. The trigger is free, but every subsequent step counts as a “task.”

A simple 3-step automation (receive email → process with AI → send response) uses 2 tasks per run. A 10-step workflow uses 9 tasks per run.

For 10,000 operations, you’re looking at around $170/month on Zapier.

Make: Pay Per Operation

Similar concept, but dramatically cheaper. For the same 10,000 operations, Make charges around $10/month. That’s not a typo. The price difference is roughly 17x.

Make also has a free tier up to 1,000 operations, which is enough to test and build before committing.

n8n: Pay Per Execution

Here’s where n8n does something fundamentally different. On n8n Cloud, you pay per workflow execution, not per operation.

A workflow with 3 nodes that runs 5,000 times costs the same as a workflow with 50 nodes that runs 5,000 times. Their starter plan runs around $24/month for 2,500 executions and 5 active workflows.

This changes the economics completely. You can build detailed, complex workflows without watching your bill multiply with every added step.

Self-host n8n and the software cost is zero. Your only expense is the server, which can be as low as $5-10/month for a VPS. The same workflow volume that costs $170/month on Zapier costs you the price of a coffee.

The Comparison Table

When to Use What

Choose Zapier if:

• You’ve never built an automation before
• You need to connect niche apps that only Zapier supports
• Your workflows are simple (under 5 steps)
• Volume is low (under 1,000 runs/month)
• You need something working in the next 15 minutes
• Budget isn’t a constraint

Choose Make if:

• Your workflows involve branching logic or multiple paths
• You want visual debugging and error handling
• You’ve outgrown Zapier’s pricing but aren’t ready to self-host
• You need some code capability but aren’t a developer
• You want the best balance of power and accessibility

Choose n8n if:

• You’re willing to invest time in the learning curve
• Volume is high and cost optimization matters
• Code execution is a priority in your workflows
• Data privacy matters (you can self-host)
• You’re building AI agents or autonomous workflows
• You have technical team members who can maintain it

The AI Agents Angle

Worth mentioning: n8n has become the de facto platform for building AI agents. Six months ago, almost nobody was talking about it. Everyone was focused on Zapier or Make. Now n8n is the first recommendation in most AI automation communities.

The reason is flexibility. When you’re building agents that need to make decisions, call APIs, execute code, and handle unpredictable inputs, n8n’s node-based approach and code execution capabilities fit naturally.

There’s a fundamental difference between an automation and an AI agent. An automation has predefined configurations—you tell it exactly what to do in advance. An AI agent executes tasks autonomously based on context and what you’re asking in the moment. That shift requires a platform that can handle unpredictability, and n8n was built for it.

Make has recently added AI agent features too, with sub-scenarios that can execute autonomously. It’s catching up. But if AI agents are your primary use case today, n8n has the stronger ecosystem.

The Hidden Use Case: Rapid Prototyping

Here’s something developers don’t always admit: many of them use these platforms to prototype ideas before writing code.

Instead of spending hours building an integration properly, you can connect nodes in 20 minutes and test whether the concept even works. If it doesn’t, you’ve lost nothing. If it does, you can either keep the automation running or rebuild it properly.

These platforms make it easy to build a minimum viable product just by connecting modules. Test fast, learn fast, decide whether to invest more.

The Real Question

The platform choice isn’t really about features. It’s about your constraints.

If time is your constraint and you need something working today, Zapier wins.

If budget is your constraint and you’re running high volume, n8n wins.

If you want the middle ground with visual building, reasonable cost, and growing code capabilities, Make wins.

Pick based on what’s actually limiting you. Not what sounds impressive.

And sometimes, if your needs are basic enough, you might not need an automation platform at all—a well-structured database and some scripts will do.

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One more thing: you can always start with one and migrate later. Many teams start on Zapier for speed, then move to Make or n8n when the bills get painful. The workflows don’t transfer automatically, but the logic translates. Rebuilding isn’t fun, but it’s not the end of the world either.