Make vs n8n vs Zapier: Which Should You Use?

A decade ago, Zapier made automation accessible to anyone.

When we launched Friday Labs in 2023, we discovered that Make.com was far better at handling the complex, multi-branch workflows businesses rely on.

Now, n8n is quickly carving out its place, not as the easiest or most polished tool, but as the one that makes agentic, AI-heavy workflows and self-hosted automation possible.

The stakes are also a little bit different now. Automation isn’t just about moving a form submission into a spreadsheet. Teams expect multi-step logic, real-time AI integrations, error handling, and compliance-grade data flows.

The choice of platform determines whether you scale efficiently, or collapse under cost and complexity.

Different philosophies, different strengths

Zapier built its empire on simplicity. Its linear builder and massive integration catalog make it the obvious first choice for non-technical teams. But that simplicity is also the ceiling. As soon as loops, branches, or heavy data volumes enter the picture, Zapier starts to break, and gets really expensive. For many small businesses, it’s perfect. For scaling teams, it’s the wrong foundation.

Make takes a different approach with its canvas-style editor, offering significantly more freedom than Zapier. This allows for the design of workflows that truly reflect real-life operations. At Friday Labs, Make has become our backbone due to its ability to process thousands of records, handle errors gracefully, and remain accessible to non-engineers after some training. While it may not be as quick to learn as Zapier, mastering it proves beneficial in terms of scalability and cost efficiency.

n8n pushes further into the realm of development tools. It offers a node-based editor similiar to Make, but with the ability to drop in custom JavaScript or Python, and, crucially, the option to self-host. This makes it very appealing for enterprises that need data control, or for builders experimenting with AI agent logic.

The hidden edge: writing and mapping formulas

One of the most overlooked aspects of automation isn't the integrations, the interface, or the AI capabilities. It's how you transform and map data once it's in motion. Every platform eventually requires you to work with formulas, and this is where the real differences become apparent.

Zapier maintains simplicity, likely by design. It offers a Formatter tool and a few basic formula steps, but for tasks beyond simple string splitting, date reformatting, or basic math, you may encounter multiple steps that other platforms might handle more efficiently.

Make offers advanced capabilities, including built-in functions for parsing JSON, manipulating arrays, running regex extractions, and constructing complex conditional logic. At Friday Labs, this functionality consistently proves its value. Rather than routing everything through multiple steps or external scripts, we can often manage transformations directly within the modules using Make’s formula editor. It resembles writing formulas in Excel or Google Sheets, but with direct access to the data flowing through your automation.

n8n is similar to make, but takes a more developer-first view. If you know JavaScript or Python, you can do anything. You can actually embed code nodes, where you transform payloads however you want, pull in npm packages, or calculate values dynamically. This makes n8n unmatched for advanced use cases like AI pipelines, heavy API integrations, or logic that would otherwise require a separate backend. But even then, there is a limit that can be reached so we typically move large n8n flows to custom code when the time is right.

The Real Question: Cost

The cost of these platforms can vary significantly, and if you're not using the right software, you might be overpaying. Many of our projects involve transitioning clients from Zapier to Make, which ultimately saves them money, even after accounting for our labor costs.

• Zapier charges per task, which seems straightforward, but it can become costly when dealing with loops and bulk processing.

• Make charges per operation, which is more efficient for multi-step scenarios.

• n8n charges per execution if you use their cloud service. However, the real advantage lies in self-hosting, where you only incur server costs, regardless of workflow complexity. 

This is why we recommend Zapier for small automations that the team frequently changes, Make for heavier operational pipelines, and n8n for massive, custom, or compliance-sensitive workflows.

What We’ve Learned

Zapier still has its place. If we need an obscure connector tomorrow, it’s often the fastest path. But for serious client delivery, Make is where we build. Its combination of visual debugging, branching logic, and cost structure simply makes sense for business operations. And when the project is experimental, AI-heavy, or requires on-premises deployment, we move to n8n. In practice, we often touch all three, but with very different expectations of what each can deliver.

Rethinking automation choices

The lesson from our own work is simple: the “best” tool doesn’t exist in a vacuum. Zapier, Make, and n8n each reflect different philosophies of automation. Zapier optimizes for ease, Make balances power and usability, and n8n maximizes flexibility and control. The right choice depends less on brand and more on workload pattern, team skill set, and compliance needs.

As AI reshapes automation, these distinctions will only grow sharper. The operators who win won’t be the ones who pick the flashiest platform, but the ones who understand where each tool bends, and where it breaks.