How should a JPA application manage database schema changes in production?

Uses versioned migrations and staged compatibility instead of letting Hibernate mutate a production schema automatically.

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I use versioned migrations through a tool such as Flyway or Liquibase and keep them in source control with the application. Hibernate schema generation is useful for disposable development or tests, and schema validation can check that mappings match an existing schema. I do not use automatic ddl-auto=update as the production migration strategy because its changes are not a complete, reviewed rollout plan.

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ddl-auto modes, Flyway or Liquibase, backward compatibility, expand-contract changes, validation, and rollback planning.

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Core answer
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Overview
Entity mappings describe application expectations; production schema evolution needs an explicit, reviewable deployment process.
I use versioned migrations through a tool such as Flyway or Liquibase and keep them in source control with the application. Hibernate schema generation is useful for disposable development or tests, and schema validation can check that mappings match an existing schema. I do not use automatic ddl-auto=update as the production migration strategy because its changes are not a complete, reviewed rollout plan.
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A safe rollout often uses expand and contract: add a nullable column or compatible table first, deploy code that can work with both shapes, backfill in bounded batches, enforce the new constraint later, and remove old fields only after all application versions stop using them. Large index builds, table rewrites, and backfills need database-specific planning. Editing an already applied migration destroys auditability; a new corrective migration records what actually happened.

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Using ddl-auto update in production.
Changing an already applied migration.
Adding a non-null column with an unsafe full-table rewrite.

How should a JPA application manage database schema changes in production?

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