Make Data Stores vs Airtable vs Google Sheets for Scenario Data

A practical field guide from Automation Ace.

The short answer

Use a Make data store for small, internal data that only scenarios use, such as checkpoints, deduplication keys, and simple lookups. Use Airtable when people also need to see, edit, or report on the data, or when records link to each other. Use Google Sheets for simple lists a team already maintains in a spreadsheet, and avoid it for high-volume or concurrent writes. All three work with Make; the right choice depends on who uses the data and how much of it there is.

Make data stores

A data store is a small database inside Make. You define a data structure, then add, update, search, and delete records with Data store modules.

• Good for: last-run timestamps and cursors, processed IDs for deduplication, small lookup tables, and short queues.
• Strengths: no extra app or connection, fast access from any scenario, and simple key-based lookups.
• Limits: storage size depends on your plan, the interface is basic, and it isn't built for people to browse, edit, or report on.

Airtable

Airtable is a relational database with an interface people actually use.

• Good for: operational records people review, queues with statuses, run logs, and anything with linked tables.
• Strengths: field types, views, filters, interfaces, and its own automations.
• Limits: API rate limits and plan record limits, plus one more app and connection to manage. See Airtable API rate limits.

See the Airtable operations database guide.

Google Sheets

Google Sheets is familiar and easy to share.

• Good for: small reference lists a team already maintains, simple exports, and reports people read in a spreadsheet.
• Strengths: everyone knows it, and it's quick to set up.
• Limits: no field types or validation, edits can break column mappings, and frequent or simultaneous writes can collide or hit API quotas. See Google Sheets automation cleanup and why a Sheets automation skips rows.

Side-by-side comparison

How to choose

1. Will people need to look at or edit the data? If yes, use Airtable, or Google Sheets for very simple lists.
2. Is it only for the scenario's own memory? Use a data store.
3. Do records link to other records? Use Airtable or a real database.
4. Will many runs write at once? Avoid Google Sheets.
5. Will it grow past a few thousand rows? Use Airtable or a database rather than a data store or sheet.

The same trade-offs apply in Zapier. See Zapier Storage vs Tables vs external databases and key-value storage vs database tables.

Example: using all three

A lead routing scenario keeps the last processed lead ID in a data store, so each run continues where the previous one stopped. It reads the sales territory list from a Google Sheet the sales manager maintains. It writes every routed lead, with its owner and status, to Airtable, where the team reviews and reports on them. Each tool does the job it is best at. See lead routing automation.

Frequently asked questions

What is a Make data store?

A data store is a small database inside Make. You define its structure and use Data store modules to add, update, search, and delete records from any scenario.

When should I use Airtable instead of a Make data store?

Use Airtable when people need to see, edit, filter, or report on the data, when records link to each other, or when the data will grow large.

Is Google Sheets a good database for Make?

It works for small lists a team already keeps in a spreadsheet. Avoid it for high-volume or simultaneous writes, because rows can collide and edits can break mappings.

Do data store operations count toward Make usage?

Yes. Each data store module run counts like other modules, so search for many records at once where you can instead of looking them up one by one.