Data archiving and tiering service for Airtable and no-code databases

The moment an ops team notices their base slowing down is almost never the moment they do anything about it — because the obvious fix, archiving old records, requires someone to decide what 'old' means, build the archiving logic, figure out where the archived data lives, and make sure nothing breaks when records disappear from the live base. That's a half-day project that gets deprioritized forever, which is why complaints like 'a base with a large number of records tends to slow the platform down dramatically' and 'the base does become slow as clients progress towards a larger system' persist for months or years.

This gap persists because the people who feel the pain — the ops coordinators and project managers doing daily work in the tool — don't have the access or confidence to restructure the base, and the people who do have access (the admin who set it up) don't feel the slowness because they're not in the tool all day. Nobody owns the problem clearly enough to fix it, so it stays broken.

What's missing is an automated, rule-based archiving layer that runs on a schedule: records older than 90 days that match a status condition get moved to a cold storage table or an external store, a link back is preserved so nothing breaks in automations, and the live base stays under a record count that keeps it fast. The user sets the rules once; the system enforces them continuously. This is fundamentally different from a manual export — it's ambient maintenance that the base would otherwise never get.

The cost of not having this is compounding: every week the base gets heavier, every new collaborator makes it slower, and eventually the team either pays for a migration to a more expensive tool or just lives with the slowness and loses adoption from mobile users (one complaint specifically called out mobile degradation). Recurring archiving is a service teams pay for monthly because the underlying problem is not a one-time event — it's entropy.

What to build

Build a scheduled archiving service that connects to Airtable bases via API, evaluates records against user-defined age and status rules on a nightly basis, moves qualifying records to a designated archive table or external datastore, inserts a lookup reference back into the live table, and sends a weekly digest showing how many records were moved and current base size versus the configured threshold.

Where to start

Start with agencies using Airtable for client project tracking, where a 'project closed' status is a clean, low-risk archiving trigger and the record volume is predictable — this gives you a repeatable onboarding playbook before tackling messier use cases.

The hard part

Airtable doesn't have a native 'move record' operation, so archiving requires a create-then-delete pattern that can break linked records and automations in ways that are hard to predict without deeply understanding the customer's specific base schema — making onboarding slow and support-heavy for the first dozen customers.

How it makes money

Monthly subscription at $39/month per workspace, priced below the cost of a single hour of ops time spent manually managing record bloat, with higher tiers for multiple bases or external datastore integrations.