Make + Spreadsheet Database

Airtable when the data matters: typed fields, linked records and filtered views mean it behaves like a database, its forms and views give non-technical teammates a proper interface, and it holds up as the record count grows. Sheets when the data is simple and the team already lives in Google Workspace: there is no new tool to learn, and whoever maintains the rows by hand works in the most familiar grid there is. The practical test is volume and editing load. Past a few thousand rows, or with several people reshaping the structure, Sheets stops behaving like a store; a handful of simple lists updated occasionally is fine on it. Swapping later means re-mapping the Make modules to the other backend rather than migrating a schema, so starting on Sheets and graduating to Airtable is a low-risk path.

Three different walls, one per tool. Make's free plan allows 1,000 credits a month across 2 active scenarios (for standard modules one credit equals one operation), which a single busy scenario can exhaust within days; the Core plan at $9 a month lifts the allowance to 10,000 credits, with higher volume bought in credit packs rather than a higher tier. Airtable's free plan caps a base at 1,000 records and 5 editors, so a working dataset outgrows it quickly; the Team plan at $24 per user per month ($20 billed annually) raises the base to 50,000 records and 25,000 automation runs a month. Google Sheets is the easy one: full functionality is free with a personal account, so the Sheets path often stays at $0.

Same pattern, different engine. Zapier is the simpler tool: linear Zaps, a much larger app catalog (6,000+ integrations versus Make's roughly 2,000), and less to learn. Make answers with depth: routers, iterators, and aggregators let a single scenario branch, loop, and merge data, and its per-credit pricing stays cheaper than Zapier's per-task billing as volume grows, because one pass over many records costs a task per record per step on Zapier. The tradeoff is a steeper learning curve and more time spent building each scenario. Pick Zapier when every workflow is genuinely linear and time to a first working automation matters more than cost; pick Make when scenarios need branching logic or the volume is high enough that per-task bills bite.

The data is safe; the logic is not. Everything Make knows about the workflows lives in its own visual scenario definitions, which do not transfer: moving to Zapier or to self-hosted n8n means rebuilding each scenario module by module. What moves cleanly is the backend, because Airtable and Google Sheets hold the records independently of the automation tool, and a new engine only needs its triggers and actions re-authored against the same fields. If the concern is cost rather than features, self-hosted n8n is the exit that removes usage-based billing entirely, at the price of running the automation tool yourself. Budget the rebuild while the scenario count is still small; the Make scenario library itself becomes the real switching cost once the business depends on dozens of them.

Because every module that runs counts, not every record. Make bills one credit per module execution, and for standard modules one credit equals one operation, so a ten-module scenario processing 100 rows consumes roughly 1,000 credits before filters and error branches, and a router fanning out to three paths multiplies it again. Scheduled scenarios that re-scan a whole table on every run drain the allowance fastest, which is why the habit worth building is to filter early (narrow the trigger to changed rows where the module supports it) and to read the scenario's usage history after its first production run. Make's per-credit model is still cheaper than Zapier's per-task pricing at volume, but only when the scenario is not wasting credits re-reading unchanged data.