Make (formerly Integromat) and Zapier are the two most popular no-code automation platforms. Both connect your apps and run trigger-action workflows without code. The real difference shows up when your workflows get complicated and when your usage scales: Zapier is the easiest tool with the biggest integration library, while Make is the more visual, more powerful, and usually cheaper option for complex work. This guide covers what actually matters.
If you are also weighing the developer-friendly option, read this alongside n8n vs. Make and Zapier vs. n8n.
Quick verdict
Choose Zapier if you want the largest integration library, the fastest setup, and simple, mostly linear automations, and your volume is low to moderate. Choose Make if your workflows are complex or high-volume and you want more power and a lower bill, thanks to visual multi-path scenarios and operation-based pricing. Zapier optimizes for ease and coverage; Make optimizes for power and cost.
The fundamental difference
Zapier: linear simplicity, maximum coverage
Zapier is built around simple, mostly linear "Zaps": a trigger followed by a series of actions. The interface is the cleanest in the category, setup takes minutes, and the integration library, 7,000+ apps, is the largest anywhere. The trade-off is that complex logic gets awkward, and per-task pricing adds up fast at volume.
Philosophy: automation should be as easy as connecting two apps, with a connector for everything.
Make: visual power, cheaper operations
Make is built around a visual canvas where you drag modules and connect them with routers (branching), iterators (loops), and aggregators (combining data). It handles multi-path, data-heavy scenarios that Zapier struggles with, and its operation-based pricing is generally cheaper. The trade-off is a steeper learning curve and a smaller integration library.
Philosophy: make complex automation visual and affordable, without requiring code.
Feature comparison
Integrations
Zapier's 7,000+ integrations are its defining moat, covering mainstream and niche apps alike; if a tool has an API, Zapier probably connects to it. Make offers 1,500+ well-built modules plus a generic HTTP module for the rest, strong on mainstream apps but far short of Zapier's breadth.
Winner: Zapier, clearly.
Workflow complexity
Zapier handles linear Zaps with paths, filters, and formatters, but has no true loops, limited error handling, and gets clumsy with complex conditional logic. Make's routers, iterators, and aggregators make multi-path, data-transforming scenarios native and readable on a visual canvas.
Winner: Make, significantly.
Pricing
Zapier is priced per task, where each action step consumes a task, so a frequently running workflow can burn thousands of tasks a month and high-volume teams can spend hundreds of dollars. Make is priced per operation, generally cheaper than Zapier tasks, with a more generous free tier (around 1,000 operations per month) and better economics at volume.
Winner: Make, especially as volume grows.
Ease of use
Zapier has best-in-class onboarding, fast app search, abundant templates, and a guided builder, so a non-technical user can ship a Zap in minutes. Make is more powerful but has a steeper start; the visual canvas is worth learning, but modules, routers, and data mapping take longer to grasp.
Winner: Zapier.
AI and ecosystem
Both add AI steps (Zapier's "AI by Zapier" and Make's AI modules) and connect to major model providers; they are roughly comparable for adding AI to a workflow, and neither is built for custom AI agents. Zapier has the larger community and template library.
Winner: Even on AI, Zapier on ecosystem depth.
Side-by-side
| Factor | Make | Zapier |
|---|---|---|
| Integrations | 1,500+ | 7,000+ |
| Workflow complexity | Advanced (routers, iterators) | Moderate (linear paths) |
| Pricing model | Per operation (cheaper) | Per task (pricier at scale) |
| Free tier | ~1,000 operations/month | Limited |
| Ease of use | Moderate learning curve | Very easy |
| Community | Large and growing | Massive |
| Best for | Complex, high-volume, budget-conscious | Non-technical, broad coverage, quick setup |
In practice: the same workflow, two tools
You want to take new leads from several sources, enrich them, branch by deal size, and route them to the right place.
With Make, the routers and iterators handle the branching and per-lead processing natively on one visual canvas, and operation-based pricing keeps a high-volume flow affordable.
With Zapier, you can build it, but the multi-path logic gets awkward and the per-task cost climbs as volume grows, though the initial setup is faster and the integrations are broader.
The pattern: Zapier wins on speed and coverage for simpler flows, Make wins on complex, high-volume automation at a lower cost.
Best use cases
Reach for Zapier when you are:
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Non-technical and want the fastest setup
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Dependent on a niche integration only Zapier supports
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Running low-to-moderate volume where convenience wins
Reach for Make when you are:
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Building multi-path, data-heavy scenarios
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Watching cost at higher volume
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Wanting serious visual power without code
Limitations to keep in mind
Neither is a true agent: both follow fixed rules and break when a task deviates from the design. Zapier gets expensive and awkward for complex logic; Make has a steeper learning curve and a smaller integration library. Both are cloud-only. Pricing and limits change, so verify current plans before committing.
What both share (and lack)
Make and Zapier are both workflow automation tools. They connect apps and execute sequences you configure. They are powerful plumbing, but plumbing, not personnel. Neither gives you AI employees with business roles, a shared brain that agents read from, or a workspace where AI and human work converge. Each workflow runs on its own, with no shared knowledge.
The alternative approach
If your goal is not "automate this workflow" but "get AI teammates that own a function," that is a different category: an AI employee platform. Agently provides AI employees for sales, operations, marketing, support, and research in a shared workspace, reading from one brain and acting across your tools, so they do not just run a flow, they handle the function. Make and Zapier automate workflows. Agently provides the workforce.
Bottom line
Choose Zapier for the largest integration library, the easiest setup, and quick automations.
Choose Make for visual complexity, cheaper operations at scale, and serious no-code power.
Look beyond both if you want AI that works as part of your team, with business roles, a shared brain, and one workspace where AI and human work come together.
Agently provides AI employees that work alongside your team in a shared workspace, not just automating workflows but handling sales, marketing, operations, support, and research. Try it free.
