convex-migrations

A migration runner pattern handles long-running data transformations in batches, providing a trackable system for schema evolution. It ensures zero-downtime deployments by safely processing field additions, removals, and type conversions.

Yes, you can perform type conversions and index creation on a live Convex database by using batch processing and migration tracking strategies. This facilitates zero-downtime deployments and ensures consistent data integrity in reactive backend environments.

The best way to handle data backfilling during field removals or additions in Convex is to implement patterns for backfilling data and handling optional fields. This ensures application stability and prevents data corruption during schema updates.

Changing a schema constraint requires a migration strategy because existing records must be backfilled with default values to satisfy new constraints. Without this, reactive backend environments face data corruption and application downtime during schema updates.

Without batch processing, evolving a reactive database schema risks application instability and downtime during long-running data transformations. A trackable migration runner pattern is required to safely handle large-scale field additions and type conversions.