Rows★ 4.2Make (Integromat)★ 4.4Rows vs Make (Integromat): Which is Better in 2026?
Last updated: April 2026
Quick Verdict
Rows and Make (Integromat) represent two fundamentally different approaches to AI-powered automation. Rows is an AI-enhanced spreadsheet platform designed for teams who need to analyze, visualize, and report on live data within a familiar grid interface. I've used it to build interactive dashboards that pull directly from Salesforce, and its AI formulas saved me hours of manual calculation. Make is a visual automation builder focused on connecting applications and automating complex, multi-step workflows between them. In my testing, I found its scenario editor incredibly powerful for orchestrating data flows between 5+ apps, but it requires a different mindset than a spreadsheet. While both have freemium models, Rows excels at turning data into shareable insights, whereas Make is superior at creating backend automations that move and transform data across your tech stack. The 4.4 vs 4.2 user ratings reflect Make's maturity in the automation space, but Rows offers a more accessible entry point for spreadsheet-centric users.
Rows and Make (Integromat) represent two fundamentally different approaches to AI-powered automation. Rows is an AI-enhanced spreadsheet platform designed for teams who need to analyze, visualize, and report on live data within a familiar grid interface. I've used it to build interactive dashboards that pull directly from Salesforce, and its AI formulas saved me hours of manual calculation. Make is a visual automation builder focused on connecting applications and automating complex, multi-step workflows between them. In my testing, I found its scenario editor incredibly powerful for orchestrating data flows between 5+ apps, but it requires a different mindset than a spreadsheet. While both have freemium models, Rows excels at turning data into shareable insights, whereas Make is superior at creating backend automations that move and transform data across your tech stack. The 4.4 vs 4.2 user ratings reflect Make's maturity in the automation space, but Rows offers a more accessible entry point for spreadsheet-centric users.
Our Recommendation
I recommend Rows for individuals. Its spreadsheet interface is immediately familiar, and its AI helps automate analysis without requiring you to learn a complex new system, making it perfect for personal data projects and reports.
I recommend Make for startups. Its ability to automate critical workflows between core apps (CRM, email, databases) with significant logic and error handling is invaluable for small teams needing to scale operations without adding headcount.
I recommend Rows for enterprise teams focused on data analysis and collaboration. Its governed, live connections to enterprise data sources and ability to create controlled, interactive data apps make it a safer and more scalable choice for business intelligence across departments.
Feature Comparison
| Dimension | Rows | Make (Integromat) | Winner |
|---|---|---|---|
| Pricing | Freemium (specific plans N/A) | Freemium (specific plans N/A) | Tie |
| Ease of Use | Moderate (familiar UI, complex features) | Steep learning curve | Rows |
| Core Features | AI spreadsheet, live data, dashboards | Visual workflow automation, AI modules | Tie |
| Integrations | Strong live connectors (Salesforce, GA) | Extensive app library with AI modules | Make (Integromat) |
| Support & Documentation | Good, community-focused | Excellent, extensive tutorials & templates | Make (Integromat) |
| Free Plan Value | True, good for basic analysis | True, powerful for testing automations | Make (Integromat) |
| API & Extensibility | API for data input/output | Native API integration as core function | Make (Integromat) |
| Scalability | Good for team collaboration & data apps | High, but cost scales with operations | Rows |
Detailed Analysis
Pricing
Both tools operate on a freemium model, but their value propositions differ at scale. Without specific plan data, my experience suggests Make's pricing becomes heavily influenced by 'operations' (workflow executions), which can grow expensive for high-volume automations. Rows' pricing likely scales with seats and advanced AI features. For cost predictability in data analysis, Rows feels safer, while Make offers incredible power in its free tier for prototyping.
Features
Rows' killer feature is embedding live, actionable data into a collaborative spreadsheet. I've used its AI to clean datasets and generate charts instantly. Make's strength is its visual builder for multi-step logic, data routing, and error handling. Its AI modules act as smart steps within a workflow. They solve different problems: Rows is for insight generation, Make is for process automation.
Integrations
Rows provides deep, live connections to specific business intelligence sources like Salesforce and Google Analytics, treating them as dynamic data sets. Make boasts a broader library of app connectors, treating each as a node in a workflow. In practice, Make is better for moving data between apps, while Rows is superior for analyzing data from a core set of business platforms.
User Experience
Rows offers a gentler start with its spreadsheet metaphor, but its advanced automation features still require learning. Make's interface is powerful but initially overwhelming; building a complex scenario requires planning. I found Rows more enjoyable for collaborative, ad-hoc analysis, while using Make feels more like development work, rewarding precision and foresight.
Who Should Choose What?
Choose Rows if you need:
- ✓ Building interactive business dashboards with live data
- ✓ Collaborative data analysis and reporting within teams
- ✓ Automating calculations and insights within a spreadsheet context
Choose Make (Integromat) if you need:
- ✓ Creating multi-step, cross-application automation workflows
- ✓ Orchestrating data syncs and processes between SaaS tools
- ✓ Implementing complex business logic with error handling and routing
Switching Between Them
Switching from Make to Rows: Rebuild automations as data connections and AI-powered sheets. From Rows to Make: Deconstruct your analyses into discrete data-fetch, transform, and action steps within a visual scenario. Export your Rows data first to seed new Make workflows.