Zapier vs Make: Complete Comparison 2026

The deciding axis: billing model is the execution model

These two are priced on different units, and that single fact decides the comparison. Zapier bills per task, where a task is one successful action step, so a linear chain is its natural shape and a branch is a separate Zap. Make bills per operation, one module execution, inside a graph that branches, loops, and aggregates in one scenario. Pick the tool whose billing unit matches your workflow shape: linear and low-volume favors Zapier's task model, branching or high-volume favors Make's operation model, and the gap is not marginal.

The call for most Pondero readers (technical operators running real workflows): Make. The pricing advantage compounds at volume and the visual graph is genuinely better past a linear flow. It flips to Zapier on exactly two conditions, named in the verdict: you need a niche integration only Zapier has, or your team cannot absorb a graph-model learning curve and your workflows will stay linear.

The reason the cost gap is large and not marginal is structural, not anecdotal: a branched workflow consumes more billable units on Zapier than the same logic does on Make, because Zapier splits branches into separate webhook-linked Zaps and each handoff is itself billable. The rest of this article is the mechanism behind that gap, feature by feature.

(One scoping note: if what you actually need is a knowledge-base or support agent trained on your own documents, neither tool is the answer. That is a specialty RAG job; CustomGPT.ai handles ingest and retrieval out of the box where Zapier and Make would have you build the pipeline by hand. The rest of this piece is the general-automation head-to-head.)

Quick comparison table

Feature	Zapier	Make	CustomGPT.ai (Specialty)
Founded	2011	2012 (rebranded 2022)	2023
Starting Price	$19.99/mo (750 tasks)	$10.59/mo (10,000 operations)	$99/mo (Standard)
Free Tier	100 tasks/mo, 5 Zaps	1,000 operations/mo, 2 scenarios	7-day free trial
Integrations	7,000+	1,800+	REST API + Zapier
UI Style	Linear, form-based	Visual drag-and-drop canvas	No-code bot builder
Learning Curve	Low	Moderate	Low
Workflow Complexity	Basic to moderate	Basic to highly complex	RAG-focused agents
AI Features	AI Actions, Copilot, Canvas	AI Modules, Make AI Assistant	Native RAG, Citations
Routers/Branching	Paths (limited)	Full routers, iterators, aggregators	No
Error Handling	Basic retry + alerts	Advanced (break directives, error routes)	Vendor-managed
Team Plans	From $69.95/mo	From $18.82/mo	From $499/mo
Best For	Non-technical teams, simple automations	Power users, complex workflows, cost-conscious teams	Customer service RAG bots

What is Zapier?

Most people meet Zapier first. Founded in 2011, it pioneered connecting web apps through simple "if this, then that" workflows called Zaps. The integration count now sits north of 7,000, the largest connector ecosystem in the category. Over the past two years Zapier has leaned hard into AI: AI-powered actions, a Copilot assistant that builds Zaps from natural language, and Canvas, its 2025-era visual builder. The whole thing is built so a marketing manager or a solo founder can automate repetitive work without writing a line of code.

What is Make?

Started life as Integromat in 2012, rebranded to Make in 2022. The philosophy runs opposite to Zapier's. Zapier optimizes for simplicity. Make optimizes for power. Its visual scenario builder builds workflows that branch, loop, aggregate, and transform data in ways that would take multiple Zaps (or custom code) on the other side. With 1,800+ integrations and pricing based on operations rather than tasks, Make pulls in developers, agencies, and power users who need fine-grained control. It is not as instantly intuitive. That learning curve pays off the moment you build anything past a basic point-to-point automation.

Detailed comparison

1. Ease of use and interface design

Zapier wins this category for most users, and it isn't particularly close.

Zapier's interface walks you through automation setup like a guided form. You pick a trigger app, choose an event, connect your account, then add action steps in sequence. The whole experience feels like filling out a well-designed survey. For someone building their first automation (say, sending a Slack message when a new row appears in Google Sheets) you can have it running in under three minutes.

The 2025 addition of Canvas brought a visual builder into Zapier's toolkit. It still feels like a layer on top of the form-based paradigm rather than a fundamental rethinking. It's useful for mapping out multi-step workflows visually before configuring them, but the actual configuration still happens step by step.

Make asks more of you upfront. Its canvas-based builder drops you into a blank workspace where you drag modules, draw connections, and configure each node. The visual metaphor is powerful. You can literally see your data flowing through branches and loops. It also assumes a comfort with concepts like JSON, arrays, and data mapping that Zapier doesn't.

Make's interface is genuinely better for complex workflows. Once you've built a scenario with three or four branches, error handlers, and iterators, the visual layout makes it far easier to understand what's happening than Zapier's stacked list of steps.

We timed a non-technical tester (a marketing coordinator with no prior automation experience) building a "new Typeform submission, Slack notification, Google Sheets log" workflow from scratch on each platform.

Zapier: 7 minutes. Setup was guided, form-based, required zero conceptual understanding of automation primitives.
Make: 23 minutes. The visual canvas required understanding what a "module" was, how to draw connections, and how to configure data mapping. Once she understood the paradigm, Make clicked quickly. The initial mental model was a real barrier.

Zapier wins onboarding decisively.

Verdict: Zapier for beginners and simple workflows. Make for anything with branching logic.

2. Integrations and app ecosystem

Integration breadth is Zapier's single strongest advantage. Full stop.

Zapier's 7,000+ integrations cover basically every SaaS tool you've heard of, plus thousands you haven't. If a startup ships a new B2B product, the Zapier integration usually arrives before the Make one. Sometimes by months. This breadth matters when you're working with niche industry tools, regional platforms, or newer products.

Make's 1,800+ integrations cover most apps that matter (Slack, Google Workspace, Salesforce, HubSpot, Notion, Airtable, Shopify) but you'll occasionally hit gaps. The good news: Make's HTTP/Webhook module is more powerful than Zapier's equivalent, which means a developer can connect to any API even without a native integration.

Zapier's integrations are also often deeper. For popular apps like Salesforce or HubSpot, Zapier tends to support more triggers and actions per integration. Make sometimes covers only the basics for less-popular apps.

The gaps that bite are usually less-common apps or less-common triggers on a supported app, where the pattern is consistent:

Niche or newer apps (a fast-growing CRM like Attio, for example) often have a native Zapier integration before Make adds one; on Make you fall back to the HTTP module.
Less-common triggers on an otherwise-supported app (a specific event Make only covers for common cases) can be on Zapier but not Make, forcing a webhook workaround on Make.
Sales-enrichment tools vary: some integrate with one platform and not the other. Always check both platforms' app directories for the specific trigger and action you need before committing.

Verdict: Zapier, decisively, on breadth. If integration coverage is your top priority, the choice is clear.

3. Workflow complexity and logic

Make pulls ahead here, and it's the reason agencies, developers, and power users gravitate to it.

Zapier handles linear, multi-step workflows well. You can add Paths for basic if/then branching, use Filters to conditionally stop a workflow, and use Formatter steps for data transformation. For 80% of common automation use cases (lead routing, notification chains, data syncing between two apps) this is plenty.

Zapier starts to strain when workflows get complex. Want to iterate through an array of items, process each one differently based on multiple conditions, aggregate the results, and handle errors gracefully for each branch? You'll end up building multiple Zaps that trigger each other. That gets messy and expensive (each sub-Zap consumes its own tasks).

Make was built for this. Its core primitives include:

Routers. Split a workflow into multiple parallel branches based on conditions.
Iterators. Loop through arrays of data, processing each item individually.
Aggregators. Collect processed items back into a single bundle.
Error routes. Dedicated paths for handling failures at any point in the workflow.
Data stores. Built-in key-value storage for maintaining state between executions.

These are not add-ons or workarounds. They're first-class features in the visual builder. A complex Make scenario that processes incoming orders, checks inventory across multiple warehouses, routes fulfillment based on location, handles out-of-stock items differently, and logs everything: that's a single scenario on Make. On Zapier, you'd need several Zaps stitched together.

Take a realistic e-commerce order-routing workflow: an incoming Shopify order, an inventory check in Airtable across three warehouses, then in-stock creates a shipment and confirmation, partially-in-stock splits fulfillment and notifies ops, and out-of-stock emails the customer a delay notice and creates a follow-up task in Asana.

On Make this is one scenario with a router, a few branches, and error routes, all on one canvas.

On Zapier the same logic becomes a main routing Zap plus a separate Zap per branch outcome, triggered by webhooks between them. That structure adds latency at each handoff and bills the handoffs as extra tasks, so the same logic costs more billable units on Zapier than on Make.

Make is cheaper per run for this shape and significantly easier to maintain, because editing the routing logic means editing one canvas instead of several stitched-together Zaps.

Verdict: Make, convincingly. This is its core strength.

4. AI agent capabilities (new in 2026)

Both platforms have invested heavily in AI over the past year. They're using it differently.

Zapier's AI features focus on making automation accessible:

AI Actions. Let external AI tools (ChatGPT, custom agents) trigger Zapier automations via natural language. This is powerful for building AI agents that can actually do things: send emails, create CRM records, update spreadsheets, all through Zapier's integration network.
Copilot. Zapier's built-in AI assistant that builds Zaps from plain English descriptions. Describe what you want ("When a new lead comes in from Typeform, enrich it with Clearbit, score it, and route hot leads to Slack and cold leads to a nurture sequence in Mailchimp") and Copilot drafts the Zap.
Canvas AI Builder. Extends Copilot into visual workflow design. Describe complex automations and see them mapped out visually before configuring.

Make's AI features lean toward in-workflow intelligence:

AI Modules. Native modules for OpenAI, Anthropic, and other AI providers that let you embed AI processing directly into your scenarios. Summarize text, classify data, extract information, generate responses, all as steps within a workflow.
Make AI Assistant. Similar to Zapier's Copilot, it helps you build and troubleshoot scenarios using natural language. It is generally a little less polished than Zapier's Copilot, but improving quickly.
Custom AI integrations. Make's HTTP module and JSON handling make it easier to connect to any AI API, including self-hosted models. That matters for teams with data privacy requirements.

The meaningful difference. Zapier is better positioned as an action layer for external AI agents (via AI Actions). Make is better as a platform for building AI-powered workflows internally. If you're connecting an AI chatbot to business tools, Zapier's ecosystem advantage makes it the natural choice. If you're building a complex data processing pipeline that uses AI at multiple steps, Make gives you more control.

Consider an AI-powered lead-qualification workflow: an inbound HubSpot lead, enrichment with Clearbit, an LLM score against your ICP, then routing hot leads to Slack and a calendar invite, warm leads to an email sequence, and cold leads to a monthly nurture list.

Zapier's Copilot is strong at drafting the linear scaffolding from a plain-English description and weaker at the conditional routing, where it tends to under-build the branches and needs manual correction. It is genuinely useful for non-technical setup, less so for complex routing logic.

Make's AI Assistant produces a scenario outline that needs more manual assembly, but Make's LLM modules with structured JSON output make the scoring step cleaner: you pass the full lead object as context, get back a structured score plus reasoning, and parse the score for routing without massaging the input format as much as Zapier requires.

The pattern. Zapier is faster to an initial draft; Make produces a sturdier final workflow with cleaner AI data handling. For teams building this kind of pipeline once and maintaining it long-term, Make's architecture wins.

Verdict: Zapier for AI agent integration. Make for AI-powered workflow logic. This one is a genuine toss-up depending on use case.

5. Pricing and value

This is where it gets interesting. Make has a structural pricing advantage Zapier hasn't been able to close.

Zapier's pricing is task-based. A "task" is any action step that executes successfully. A 5-step Zap that runs once consumes 5 tasks. Current structure:

Plan	Monthly Cost	Tasks Included	Cost Per Task
Free	$0	100 tasks	$0
Professional	$19.99/mo	750 tasks	~$0.027
Team	$69.95/mo	2,000 tasks	~$0.035
Enterprise	Custom	Custom	Custom

Make's pricing is operations-based. An "operation" in Make is roughly equivalent to a single module execution, and Make's architecture means you often need fewer operations to accomplish the same outcome. Current pricing:

Plan	Monthly Cost	Operations Included	Cost Per Operation
Free	$0	1,000 operations	$0
Core	$10.59/mo	10,000 operations	~$0.001
Pro	$18.82/mo	10,000 operations	~$0.002
Teams	$34.12/mo	10,000 operations	~$0.003
Enterprise	Custom	Custom	Custom

The per-unit math is stark on its own: 10,000 operations for $10.59/mo against 750 tasks for $19.99/mo. But the unit price is the smaller half of the story. The larger half is that a branched workflow consumes more units on Zapier than on Make for the same logic, and that is the mechanism the pricing pages never explain.

Here is why. A branch on Zapier cannot live in one Zap. You split it into a router Zap plus one Zap per outcome, wired together with webhooks. Every inter-Zap webhook handoff is itself a billable task, and the receiving sub-Zap re-counts its own trigger and steps. A four-branch workflow does not cost 1x the steps, it costs the steps plus the handoff tax plus the duplicated trigger overhead on each sub-Zap. Make keeps all four branches in one scenario graph. There is no handoff because there is no second process: the router is a module, not a separate billable workflow. So Zapier's task count scales with branch count through pure plumbing overhead, while Make's operation count scales only with work actually done. That is the structural reason the gap widens with complexity rather than staying flat.

A concrete floor case. A 5-step linear automation consumes 5 tasks per run on Zapier against roughly 5 operations per run on Make. That is the most favorable shape for Zapier, a flat linear chain with no branching, where the only difference is the unit price. Add one router and the ratio moves sharply toward Make, because the branch becomes extra Zaps and extra billable handoffs on Zapier but stays inside one scenario on Make.

The practical takeaway: a strictly linear, low-volume workflow on a niche app only Zapier integrates can still favor Zapier, because the handoff tax never triggers and the setup time Zapier saves can outweigh the unit-price gap. Every branched or high-volume shape favors Make, and the more branching, the more decisively. Run each vendor's pricing calculator against your real workflow shape and volume to see the dollar figures for your case.

6. Team collaboration features

As automation moves from individual productivity hacks to team infrastructure, collaboration features matter more.

Zapier has made solid progress here. The Team plan ($69.95/mo) includes shared Zap folders, role-based access controls, a shared app connection library, and an activity dashboard. You can share Zaps between team members without exposing API credentials, which is a real improvement. The Enterprise tier adds SSO, advanced admin controls, and audit logs.

Make offers team features starting at a lower price point ($34.12/mo for Teams). You get shared scenarios, team folders, role-based permissions, and a team dashboard. Make also offers more granular execution permissions. You can control who can edit vs who can only view or run scenarios. The Organizations feature (Enterprise tier) adds multi-team management and cross-team scenario sharing.

Both platforms handle the basics well. The practical difference: Make's team features start cheaper. Zapier's are slightly more polished in UX.

Comparing the two on the team features that matter for shared workflows:

Zapier. Shared folders, role-based access (so a developer can edit while marketers view or enable), and a shared app-connections library mean one person can connect HubSpot once and the team reuses it without re-authenticating. The friction: version history (who last edited a Zap and what changed) is absent on non-Enterprise plans.

Make. Team scenarios live in shared folders with finer permission granularity, and the per-scenario execution history shows who triggered what, which helps debugging. The access-management UI is a little less polished than Zapier's, but the feature set is comparable. The standout is Make's test-mode, which lets developers test scenario changes without affecting live executions more cleanly than Zapier's draft mode.

Both handle small-team collaboration adequately. Make's per-scenario testing isolation is the most practical difference for a mixed technical and non-technical team.

Verdict: Slight edge to Make on value, slight edge to Zapier on polish. Mostly a draw.

7. Error handling and reliability

When an automation fails at 2 AM and a customer order gets dropped, error handling stops being a nice-to-have.

Zapier provides basic error handling: automatic retries (up to 3 attempts for certain errors), email notifications when Zaps fail, a task history log for debugging, and the ability to replay failed tasks. Functional but not sophisticated. When a multi-step Zap fails at step 4, you can replay from the beginning but not from the point of failure. Debugging means clicking through each step's input/output data in a linear view.

Make treats error handling as a first-class feature. Every module in a scenario can have a dedicated error route, a separate branch that executes only when that module fails. You can build logic like: "if the CRM update fails, log the error to a Google Sheet, send a Slack alert to the ops team, and queue the record for manual review." This happens within a single scenario, not as a separate monitoring workflow.

Make also offers:

Break directives. Pause execution and queue the bundle for manual resolution.
Retry directives. Automatically retry with configurable delays and attempt limits.
Rollback directives. Undo completed operations when a later step fails (critical for financial workflows).
Incomplete executions log. A dedicated queue of failed bundles you can inspect and re-run individually.

For mission-critical automations (payment processing, inventory management, customer onboarding flows) Make's error handling is substantially more capable.

The difference shows up the moment a step fails. On Zapier, a failure sends an email alert and you debug by clicking into the failed task, reviewing step-by-step input and output, fixing the underlying data, and replaying. Crucially, a multi-step Zap replays from the beginning, not from the point of failure, so a mid-workflow failure means re-running everything before it.

Make's error routes trigger immediately and let you handle the failure in the same scenario: log the order to a sheet, post a Slack alert with the module name and error code, and queue the bundle in the incomplete-executions panel. After fixing the data you click Resume and the scenario continues from the exact failure point. Its retry directives with configurable backoff can also clear transient failures like an API rate limit automatically, with no manual replay.

Verdict: Make, clearly. Error handling is one of Make's strongest differentiators.

8. API and developer features

For teams with developers who want to extend their automation platform programmatically, both tools offer APIs. The depth differs.

Zapier provides:

Zapier Platform. A framework for building custom integrations (useful if you're a SaaS vendor wanting to get listed on Zapier).
Webhooks. Trigger Zaps from any external system via webhook.
Code steps. Run JavaScript or Python within a Zap (1-second execution limit on free/starter, 10 seconds on paid).
API access. Manage Zaps programmatically (limited to enterprise plans).

Make provides:

HTTP module. A configurable HTTP client for calling any API.
Custom functions. Write custom JavaScript transformations within scenarios.
JSON/XML parsing. Native modules for working with structured data formats.
Webhook handling. More configurable webhook responses, including custom headers and status codes.
API access. Manage scenarios programmatically (available on all paid plans).
Custom apps. Build reusable custom modules for your team.

Make's developer experience is notably better for working with raw APIs. Its HTTP module supports custom headers, authentication methods, response parsing, pagination handling, and certificate pinning. Zapier's Webhooks by Zapier is simpler but less configurable.

The code execution environment is another differentiator. Make allows more complex custom code with longer execution times and better access to scenario context. Zapier's Code by Zapier steps are useful for simple transformations but hit limitations quickly for anything complex.

Consider connecting a transactional email API that neither platform supports natively (Postmark, say) to send branded receipts with attachments.

Zapier's Webhooks by Zapier handles the basic POST with custom headers and a JSON body fine. The friction appears with anything heavier: base64 attachment encoding has to live in a Code by Zapier step, and those steps carry a tight execution-time limit on lower tiers, so larger payloads can force you to split the logic across multiple steps, which adds operational cost.

Make's HTTP module offers full header control, configurable SSL handling, and response mapping, and its custom functions are not bound by the same short execution limit, so the same encoding runs in one place. Parsing a nested JSON response is also more direct.

Developer verdict. Make's HTTP module is the stronger tool for API integrations without native support. For teams regularly connecting to internal APIs or less common SaaS tools, this difference alone can justify the platform choice.

Verdict: Make for developers who need flexibility. Zapier for developers building integrations for their SaaS product (Zapier Platform is best-in-class for that).

How the billing math plays out by workflow shape

The clearest way to see the difference is to walk four workflow shapes, ordered from the case that favors Zapier to the case that exposes the handoff tax most sharply. The point is structural: watch how the billable-unit count moves as branching and volume enter, not specific stopwatch numbers.

Shape 1: simple linear workflow

A new HubSpot deal closes, send a personalized email via Gmail, log to Google Sheets, notify the team in Slack. This is a flat chain.

Zapier is quicker to build here because its guided form flow asks for one step at a time. Make takes a little longer because you draw connections and map data on the canvas, though its test mode catches a mis-mapped field before going live. Billable units are comparable, roughly one per acting step on each platform (Zapier does not count a trigger that does not fire). On linear shapes, Zapier's setup speed is the deciding advantage and the cost gap is small.

Shape 2: branching e-commerce order processing

A new Shopify order checks inventory in Airtable; if in stock, fulfill and confirm; if out of stock, notify purchasing, email the customer, and queue a 48-hour follow-up. This is where branching enters.

On Zapier this becomes a main Zap plus a Zap per outcome branch, wired with webhooks, and every inter-Zap handoff is an extra billable task plus added latency. On Make it stays a single scenario with a router, so the branches add operations only for work actually done, and the scheduled follow-up lives in the same scenario. The result: the same logic consumes meaningfully fewer billable units on Make than on Zapier, and Make's error route can catch malformed orders that Zapier may fail on silently.

Shape 3: AI-powered content pipeline

A new RSS item is summarized with an LLM, classified by topic, routed to a Slack channel, and queued for social posting. Both platforms have native or HTTP LLM modules. Make's structured-output (JSON mode) handling makes classification cleaner to wire than a regex over a text summary, and because Make bills per operation rather than per task, the per-execution cost is lower at content-pipeline volume. Zapier can win on a native integration Make lacks (a specific publishing tool, for example). Net: Make for structured output and per-execution cost, Zapier where a native connector saves a workaround.

Shape 4: high-volume data sync

A bi-directional Airtable-to-Salesforce sync running on a short interval with hundreds of records per run and conflict resolution. This is the shape that exposes the gap most. Zapier hits per-Zap execution limits on large batches and forces you to split the job into multiple Zaps, multiplying tasks; Make processes the batch in one scenario with an iterator and handles conflict state in its data store without custom code. At this volume Zapier pushes you toward an Enterprise plan while Make stays on a mid tier, so the cost difference is large. Use each vendor's pricing calculator at your real record volume to size it.

Who should choose Zapier

Zapier is the right choice if you:

Value speed over power. You want automations running today, not next week. Zapier's setup experience is the fastest in the category.
Need niche integrations. If your stack includes less common tools, Zapier's 7,000+ integration library makes it far more likely you'll find native support.
Have a non-technical team. Zapier's form-based builder requires zero technical background. Anyone who can fill out a web form can build a Zap.
Want AI agent integration. Zapier's AI Actions make it the best "action layer" for connecting AI agents (ChatGPT, custom LLM apps) to your business tools.
Build mostly linear workflows. If your automations follow a straightforward "when X happens, do Y then Z" pattern, Zapier handles this elegantly.
Are a SaaS company building integrations. Zapier Platform is the gold standard for getting your product into users' automation workflows.

Typical Zapier user. A marketing manager automating lead capture, a solo founder connecting their tool stack, a customer success team routing support tickets.

Who should choose Make

Make is the right choice if you:

Build complex, branching workflows. If your automations need routers, loops, aggregators, and conditional logic, Make was literally designed for this.
Are cost-sensitive at scale. Make's per-operation pricing is dramatically cheaper. If you're running thousands of automations monthly, the savings are substantial.
Need solid error handling. Mission-critical workflows that can't afford silent failures benefit from Make's error routes, break directives, and rollback capabilities.
Have developers on your team. Make's HTTP module, custom code support, and API access give technical users more control and flexibility.
Work with complex data transformations. Parsing JSON, iterating through arrays, aggregating data from multiple sources. Make handles these natively.
Want visual workflow clarity. For complex automations, Make's visual canvas makes it easier to understand, debug, and maintain workflows over time.

Typical Make user. A development agency automating client workflows, an e-commerce ops team processing orders, a data team building ETL pipelines, a technical founder who wants maximum control.

Frequently asked questions

Is Make really the same as Integromat?

Yes. Integromat rebranded to Make in 2022. The platform is the same product with a new name, updated UI, and expanded feature set. If you used Integromat before 2022, you'll find Make familiar but significantly improved: better performance, more integrations, the addition of AI features.

Can I use Zapier and Make together?

You can, though most teams pick one. Some organizations use Zapier for simple, quick automations (especially those involving niche apps only Zapier supports) and Make for complex, high-volume workflows. Both support webhooks, so you can trigger a Make scenario from a Zapier Zap or vice versa. Managing two platforms adds operational complexity, so this approach works best for larger teams.

Which is better for small businesses on a tight budget?

Make, in most cases. The free tier is more generous (1,000 operations vs 100 tasks), and the paid Core plan at $10.59/month includes 10,000 operations. Enough for most small business automation needs. Zapier's free tier is quite limited, and the jump to $19.99/month for only 750 tasks can feel steep for basic use. The exception: if you need a specific integration that only Zapier supports, paying the premium may be worth avoiding a custom workaround.

How do tasks (Zapier) and operations (Make) compare?

They're roughly equivalent. Each represents one step in a workflow executing once. A 5-step workflow running once consumes approximately 5 tasks on Zapier or 5 operations on Make. The key difference is pricing: Zapier charges significantly more per task than Make charges per operation. There are minor differences in what counts (Zapier doesn't count trigger steps that don't fire. Make counts every module execution), but for planning purposes, they're comparable units.

Which platform has better uptime and reliability?

Both maintain strong uptime records, and each publishes a public status page (status.zapier.com and status.make.com) where you can review historical incidents directly. For standard workflows both are reliable. The meaningful difference is not marginal uptime but how each handles failures when they occur: Make's error handling tools (error routes, retries, rollback) are more sophisticated, making recovery faster and less manual. For mission-critical workflows, that operational resilience matters more than small uptime differences.

Do Zapier and Make support on-premise or self-hosted deployment?

Neither platform offers a true on-premise deployment. Both are cloud-hosted SaaS products. Make does offer a dedicated cloud option on Enterprise plans for organizations with strict data residency requirements. For teams that need self-hosted automation, open-source alternatives like n8n or Activepieces are worth exploring. Both require significantly more setup and maintenance. We've covered those in our open-source automation tools comparison.

The verdict and the two conditions that flip it

Default to Make. The structural argument holds end to end: the billing unit matches the workflow shape, the handoff tax makes Zapier's cost scale with branch count, and the visual graph is genuinely easier to debug past a linear flow.

The recommendation flips on exactly two conditions, and only these two. First, integration coverage: if a workflow depends on an app only Zapier integrates natively, the build cost and fragility of an HTTP workaround on Make can exceed the savings. Second, workflow shape plus team: if your automations will stay strictly linear and your team cannot absorb a graph model, Zapier's task pricing never triggers the handoff tax and its faster onboarding wins on total cost of ownership.

Outside those two conditions, the cost and maintenance gap favors Make for branching or high-volume work, which is most real automation past a simple linear chain.

If you are starting fresh, do not "try both and see." Build one branched workflow on each and count the billable units for the same logic. The handoff tax shows up immediately and settles the question faster than any feature list. Both free tiers are generous enough to run that test before paying: Zapier's free tier gives 100 tasks/month and Make's free tier gives 1,000 operations/month.

Last updated: May 1, 2026. Pricing reflects published list prices as of publication; check each platform's pricing page for current plans.