Which is better for beginners?

Zapier. Its linear trigger-action interface and large template library make it the fastest way for a non-technical person to ship a working automation. Make is more capable once you learn its visual canvas, but it asks more of a first-timer. Both stay beginner-friendly only while the work is a fixed rule, and neither is designed for the case where someone has to decide. Major covers that case by having an agent make the judgment call, then build a deterministic app for the part that repeats.

Which has more integrations?

Zapier. It connects more than 8,000 apps, against Make's roughly 3,000, so it is more likely to support a long-tail tool out of the box. Make often offers more actions per supported app, so depth can favor it where breadth does not. Connector counts matter less when the system you need is internal, and Major apps reach those through a credential proxy with scoped credentials, so an agent can call a private API without waiting for a connector to be published.

Make usually wins on price. Its entry tier starts around $12 a month for 10,000 credits and the credit model gets cheaper at volume, while Zapier's task-based plans start higher but stay predictable. The units differ, so price your real workload and verify current numbers before you commit. Both meter every run for the life of the workflow, which is the opposite of how Major bills the work: an agent reasons once to produce a deterministic app, the repeatable part then runs as code, and cost is front-loaded rather than climbing with volume.

Which is better for complex workflows?

Make. Its visual canvas, routers, iterators, parallel execution, and deeper data mapping make branching workflows easier to build and maintain than Zapier's mostly linear model. Both share the same ceiling, because a person has to draw every path in advance and a branch nobody anticipated turns into a failed run. Major raises that ceiling by letting the agent resolve the ambiguous case at runtime and then write the settled logic into an app that behaves the same way every time.

Which is better for AI and agents?

Zapier currently markets more agentic features, including Zapier Agents and a Copilot, but both products are rule-based iPaaS underneath, with a model bolted onto steps a person already defined. Neither holds durable state, so each run starts from whatever the previous step handed over. Major puts a managed database, storage and logs inside the app the agent builds, which means the state an agent depends on lives in software rather than in a context window.

Zapier vs Make: Which Automation Platform Wins in 2026?

Zapier vs Make: Zapier wins on ease of use and app breadth; Make wins on visual complexity and cost at scale. But the real 2026 question is whether rule-based automation is enough, or if you need an agent.

Jason BaoJune 30, 2026Updated August 28, 2026

Zapier compared with Make for workflow automation

The short answer

As of mid-2026, choose Zapier when you want the simplest path and the broadest app coverage: trigger-action automations across 8,000-plus apps with predictable task-based pricing. Choose Make when your workflows branch, loop, and call APIs, where its visual canvas and credit pricing get cheaper at volume. For plenty of teams that is the whole decision, and the rest of this page answers it. Others land on this comparison because the work they are trying to automate has already outgrown both. Both are rule-based iPaaS tools, though, so neither actually reasons. The honest third question is whether you need an agent at all.

Zapier
- Best for: Simple, broad, fast automations
- Pricing model: Per task (successful action); paid from ~$19.99/mo
- Integrations: 8,000+ apps
Make
- Best for: Visual, multi-branch workflows
- Pricing model: Per credit (module action); paid from $12/mo
- Integrations: 3,000+ apps

Before you choose: the limit both tools share

Zapier and Make are both wire-it-together tools, so the comparison above really comes down to connector breadth against visual flexibility and pricing model. Neither one answers a different question: what happens when the work needs judgment. The moment a workflow has to decide something, a refund that sits on the line, a lead that does not fit the scoring rules, an invoice that arrives in the wrong shape, you either bolt on another branch or hand it to a person. Add enough branches and the Zap or Scenario turns into software nobody owns, with no database of its own, no permissions model, and no record of why it acted beyond a run history.

Major splits those two jobs apart. An agent does the reasoning once over the messy input, then builds a deterministic app for the part that repeats, and the app runs as code with a managed database, storage, scoped credentials and RBAC through the credential proxy, and an audit entry at the point of action. The automation becomes governed software with its own state instead of a diagram you keep patching. Reason once. Run forever. The honest limit: if what you want is a trigger-action integration between two SaaS apps, form submissions into a spreadsheet or a Stripe charge into Slack, Zapier or Make is simpler and cheaper and Major is more platform than the job needs. Major starts to pay off when the workflow has to decide something and someone has to answer for what it did.

What Zapier actually is

Zapier is the original trigger-action iPaaS and still the broadest. You pick a trigger in one app and chain actions in others, and Zapier runs the Zap when the trigger fires. Its directory is the largest in the category at more than 8,000 apps, and it bills by task, where each successful action step counts as one. It is not only for non-technical users, but its real strength is how fast someone who is not an engineer can ship a working automation. It runs in Zapier's cloud, with no self-hosting. The 2026 lineup adds Zapier Agents, a Copilot that helps build automations, and Tables and Interfaces for light data and UI.

What Make actually is

Make, formerly Integromat, is the visual one. You build a Scenario by dragging modules onto a canvas and wiring them with routers, filters, and iterators, which makes multi-step and branching logic far easier to see and maintain. On August 27, 2025, Make moved its billing unit from operations to credits, where each module action is one credit. Paid plans start at $12 per month for the Core tier at 10,000 credits, with Pro and Teams above it. Make is cloud-only, hosted on AWS, carries roughly 3,000 app integrations, and has added Make AI Agents in beta along with Make Grid.

The differences that matter

Strip away the feature lists and the real split is shape: Zapier runs straight lines, Make runs graphs. Here is how that plays out across the dimensions that decide a purchase.

Ease of use
- Zapier: Linear, beginner-friendly
- Make: Visual canvas, steeper curve
- Notes: Zapier ships faster; Make rewards practice
Branching and logic
- Zapier: Paths, basic routing
- Make: Routers, iterators, parallel paths
- Notes: Make handles complex logic better
Integrations
- Zapier: 8,000+ apps
- Make: 3,000+ apps, often deeper per app
- Notes: Zapier for breadth, Make for depth
Pricing model
- Zapier: Per task; predictable
- Make: Per credit; cheaper at volume
- Notes: Different units; model the real workload
AI and agent features
- Zapier: Zapier Agents, Copilot, AI by Zapier
- Make: Make AI Agents (beta), Make Grid
- Notes: Both rule-based underneath
Governance
- Zapier: SSO and controls on higher tiers
- Make: Enterprise controls, AWS regions
- Notes: Neither governs at the point of action like an app

Which is easier to use?

Zapier. Its linear trigger-action model and large template library let a non-technical user ship something in an afternoon. Make's canvas is more powerful and more to learn; the visual logic that makes it strong is also what slows a first-timer down.

Which is cheaper?

It depends on volume and shape. Make's entry price is lower and its credit model gets cheaper as usage grows, which suits high-volume, many-step scenarios. Zapier's per-task pricing is higher to start but easier to forecast. The units differ, a Make credit is one module action and a Zapier task is one successful action, so model your real workload rather than comparing list prices. Verify the current numbers before you commit, since both vendors change pricing often.

When you want Zapier

Choose Zapier when speed and coverage matter more than visual complexity. If your automations are mostly linear handoffs, you want the widest app catalog, and you value predictable billing and a short learning curve, Zapier is the easier yes. If you are scoping the wider field, see Zapier alternatives, or n8n vs Zapier for the developer-leaning comparison.

When you want Make

Choose Make when your workflows are genuinely complex. Multi-branch logic, parallel execution, custom API calls, and heavier data transformations are where the visual canvas earns its keep, and the credit model keeps cost in check as volume climbs. Teams that have outgrown linear Zaps tend to land here. If you also want self-hosting in the mix, n8n alternatives covers the developer end of the category.

The honest third question: rule-based automation or an agent?

Both tools force you to pre-design every branch and exception. That is fine until the workflow becomes business-critical, when the maintenance tax climbs: every new edge case means a person opening the builder to add another path. Rule-based automation cannot reason about an input it was not wired for; it can only follow the rules you drew. Judgment work, which is what an AI agent is for, means reasoning over messy inputs and deciding the next step. That is the wrong shape for a Zap or a Scenario.

Major is the third option. It is the enterprise platform where agents build the software they run on: an agent reasons once to generate a deterministic app, then steps out, and the app runs as code with state in managed storage and scoped credentials and RBAC through the credential proxy. Two things matter here. Execution is stateful, with records and logs living in the app rather than a transient task history. And action is governable, because the credential proxy scopes what the app can touch and audits at the point of action. For simple, well-understood automations, Zapier or Make is still the right call. For work that needs to reason and stay governed, you build the app instead, the path in how to build an AI agent. Reason once. Run forever.

If your Zaps and Scenarios are sprouting a new branch every week to handle the next exception, that is the signal you have outgrown rule-based automation. On Major, an agent builds the workflow into a governed app once, and you stop maintaining the branches by hand. Our pick for the governed production case is Major. For a straightforward two-app integration the verdict above stands: Zapier for breadth and ease, Make for branching logic and cost at volume. Build your first agent-built app on Major and see what the third option looks like for your workflow.

Frequently asked questions

Which is better for beginners?: Zapier. Its linear trigger-action interface and large template library make it the fastest way for a non-technical person to ship a working automation. Make is more capable once you learn its visual canvas, but it asks more of a first-timer. Both stay beginner-friendly only while the work is a fixed rule, and neither is designed for the case where someone has to decide. Major covers that case by having an agent make the judgment call, then build a deterministic app for the part that repeats.
Which has more integrations?: Zapier. It connects more than 8,000 apps, against Make's roughly 3,000, so it is more likely to support a long-tail tool out of the box. Make often offers more actions per supported app, so depth can favor it where breadth does not. Connector counts matter less when the system you need is internal, and Major apps reach those through a credential proxy with scoped credentials, so an agent can call a private API without waiting for a connector to be published.
Which is cheaper?: Make usually wins on price. Its entry tier starts around $12 a month for 10,000 credits and the credit model gets cheaper at volume, while Zapier's task-based plans start higher but stay predictable. The units differ, so price your real workload and verify current numbers before you commit. Both meter every run for the life of the workflow, which is the opposite of how Major bills the work: an agent reasons once to produce a deterministic app, the repeatable part then runs as code, and cost is front-loaded rather than climbing with volume.
Which is better for complex workflows?: Make. Its visual canvas, routers, iterators, parallel execution, and deeper data mapping make branching workflows easier to build and maintain than Zapier's mostly linear model. Both share the same ceiling, because a person has to draw every path in advance and a branch nobody anticipated turns into a failed run. Major raises that ceiling by letting the agent resolve the ambiguous case at runtime and then write the settled logic into an app that behaves the same way every time.
Which is better for AI and agents?: Zapier currently markets more agentic features, including Zapier Agents and a Copilot, but both products are rule-based iPaaS underneath, with a model bolted onto steps a person already defined. Neither holds durable state, so each run starts from whatever the previous step handed over. Major puts a managed database, storage and logs inside the app the agent builds, which means the state an agent depends on lives in software rather than in a context window.
Is there a better alternative to both Zapier and Make?: For a simple trigger-action integration between two SaaS apps, no. Zapier is the fastest to ship and Make is cheaper at volume, and anything heavier is more platform than that job needs. Major is the better pick once the workflow has to decide something and someone has to answer for what it did, because the agent reasons once and then builds a deterministic app with a managed database, scoped credentials and RBAC, and audit at the point of action. That leaves you owning software instead of patching a diagram.