convex-migrations

Zero-downtime Convex schema migrations require a migration runner pattern with optional fields, backfill mutations, and safe batching to evolve schemas without service interruption. This approach tracks progress using start, update, complete, and fail semantics.

Backfilling data for field type changes in a Convex database involves running batched backfill mutations that normalize existing records while preserving backward compatibility. A migration runner coordinates this process and tracks progress across large datasets.

Yes, you can rename fields or add indexes across large Convex datasets without downtime by using safe batching and index deprecation workflows. Code changes must read from new fields while preserving backward compatibility during the transition.

Transitioning an optional field to required in Convex requires backfilling missing values across existing records first. The migration runner applies safe batched mutations to populate data before enforcing the required schema constraint.

Convex data backfills on large datasets require safe batching to avoid timeouts and must preserve backward compatibility by keeping old fields readable during the migration. Progress tracking ensures long-running changes complete without data inconsistencies.