Comparison
Make (formerly Integromat) vs Zapier
The two biggest automation platforms compared — which one saves you more time in 2026?
Our verdict
Make wins on power, pricing, and visual clarity. Zapier wins on ease of use, app library, and getting started in minutes.
Make (formerly Integromat) offers a visual canvas-based workflow builder with significantly more powerful logic — branches, iterators, aggregators, and error handling — at a lower price point than Zapier. Zapier has 6,000+ app integrations (vs Make's ~1,500), simpler setup, and the most recognizable brand in automation. Make is the choice for power users; Zapier is the choice for non-technical teams who need automation in minutes.
Overview
Make and Zapier are the two dominant workflow automation platforms. This comparison covers pricing, app support, complexity ceiling, and which is better for marketing, ops, and AI workflows.
Head-to-head comparison
| Category | Make (formerly Integromat) | Zapier |
|---|---|---|
| App Integrations | ~1,500 apps and services | 6,000+ app integrations |
| Pricing | Free tier; paid from $9/month — significantly cheaper | Free tier; paid from $19.99/month |
| Workflow Logic | Powerful — branches, iterators, aggregators, routers, error handlers | Simpler logic — good for linear workflows, limited branching |
| AI Features | AI modules for OpenAI, Anthropic, and data transformation | Zapier AI actions and OpenAI integration |
| Learning Curve | Steeper — visual canvas can be overwhelming initially | Low — wizard-driven setup, very beginner-friendly |
| Execution Speed | Faster execution and more operations per run | Slower on complex, multi-step workflows |
| Data Handling | Excellent data manipulation, JSON handling, and transformations | Basic data transformation; Formatter app helps but limited |
| Support & Community | Strong community, growing documentation | Extensive documentation, larger community, more tutorials |
| Score | 4 wins | 3 wins |
Who should choose what?
Choose Make (formerly Integromat) if…
- Power users who need complex, branching workflows with advanced data handling
- Teams on a budget who need a lot of automation operations for less money
- Developers or technical ops teams comfortable with a learning curve for more control
- Teams processing large data sets or needing custom iterators and aggregators
Choose Zapier if…
- Non-technical teams who need automation running in minutes without a learning curve
- Teams whose critical apps are only on Zapier (many niche SaaS tools support Zapier first)
- Businesses already invested in the Zapier ecosystem with existing zaps
- Teams that prioritize app library breadth over workflow complexity
Frequently asked questions
Is Make better than Zapier?
Make is better for power users who need complex logic, lower cost, and more operations per dollar. Zapier is better for simplicity and has a much larger app library. For most professional automation use cases in 2026, Make offers more value — but Zapier wins on ease of initial setup.
How much cheaper is Make than Zapier?
Make's paid plans start at $9/month vs Zapier's $19.99/month. At comparable operation volumes, Make is typically 3-5x cheaper than Zapier. For high-volume automation, this difference becomes significant quickly.
Can Make replace Zapier?
For most use cases, yes. The main exception is if you rely on Zapier-exclusive integrations — some niche SaaS tools only offer official Zapier support. Before switching, check that all your critical apps have Make modules.
Do Make and Zapier support AI automations?
Both do. Make has native modules for OpenAI, Anthropic (Claude), and Perplexity. Zapier has Zapier AI Actions and OpenAI integration. Both can be extended via HTTP modules to call any AI API. n8n is increasingly preferred over both for serious AI automation workflows.
Which is better for marketing automation — Make or Zapier?
For marketing automation connecting tools like HubSpot, Mailchimp, Slack, and Google Sheets, both work well. Zapier is usually faster to set up for standard marketing workflows. Make is better when you need complex data transformation, enrichment pipelines, or AI-augmented marketing workflows.
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