convex-migrations

Zero-downtime Convex schema migrations are achieved by evolving tables with optional fields, running backfills, and updating indexes before removing deprecated fields. This enforces a stepwise workflow where code paths switch safely without deployment interruptions.

Backfilling large Convex datasets requires orchestrated batch mutations and progress tracking to safely update existing records. This approach ensures data migrations complete iteratively without overloading the database or causing downtime during the schema transition.

Renaming or removing fields in a Convex schema requires introducing the new field, backfilling data, and switching code paths before deletion. The deprecated field must only be removed after all application code successfully transitions to the new schema.

Yes, Convex index migrations and table schema changes can be applied without downtime by following stepwise patterns. You introduce index changes alongside optional fields, ensuring existing queries remain functional while the new schema is deployed.

You should use a stepwise Convex migration pattern when adding, removing, or renaming fields and performing data migrations across large datasets. It prevents downtime by separating code deployments from schema changes and backfill operations.