Side-by-side

Baserow vs Make

BaserowMake

Bottom line: Baserow for teams needing self-hosted databases; Make for operations and marketing teams automating multi-step, cross-app processes.

	Baserow Open-source no-code database and Airtable alternative Visit	Make Make is a visual workflow automation platform that connects over 3,000 apps and services, enabling users to build automated workflows without extensive coding Visit
Votes	0	0
Pricing	Freemium	Freemium
Category	Automation	Automation
Tags	open-sourceno-codedatabaseairtable-alternativeself-hosted	automate-workflows
Best for	Teams needing self-hosted databases Privacy- and cost-conscious organizations Developers wanting an API-backed database	Operations and marketing teams automating multi-step, cross-app processes No-code and low-code builders who want visual control over complex logic Businesses running high-volume workflows sensitive to per-operation cost
Pros	Open source with free self-hosting Self-hosted usage is effectively unlimited REST API for every database Strong fit for data-sovereignty needs Familiar Airtable-style interface	The visual scenario builder makes complex, multi-branch automations far easier to design and audit than linear step-based tools, with data flow and logic represented clearly on a single canvas. A library of 3 000+ pre-built app connectors, backed by generic HTTP, webhook, and custom app modules, means nearly any API can be reached even when a native integration is missing. Make is genuinely AI-native, offering agentic automation, ready-made AI agents, and an MCP server that lets AI assistants trigger real actions across connected apps rather than just generating text. The pricing is competitive for high-volume workflows, with an operations-heavy allowance at entry-level tiers and a no-time-limit free plan for experimentation.
Cons	Self-hosting requires technical setup and maintenance AI and polish trail Airtable in places No native mobile app Cloud free plan caps rows and storage Some features gated to premium/enterprise	The visual canvas is powerful but has a real learning curve; newcomers to automation often find its data mapping, iterators, and error handling harder to grasp than simpler competitors. The recently introduced credit-based billing model can make costs harder to predict, since advanced and AI-powered actions may consume more credits than a standard operation. Complex scenarios can become difficult to maintain and debug at scale, and heavy reliance on the platform creates a degree of workflow lock-in. There is no self-hosted or offline option, so teams with strict on-premise or air-gapped requirements will need an alternative.

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