A relational database handles schema changes through a structured process known as schema migration, which allows developers to modify the database structure without losing existing data. Schema changes can include adding or removing tables, altering columns, changing data types, or adding constraints. These changes can be performed using Data Definition Language (DDL) commands, such as CREATE, ALTER, and DROP. When a schema change is made, it’s important to ensure that the alteration is backward compatible to avoid disrupting application functionality.
For example, if a developer wants to add a new column to an existing table, they would typically use an ALTER TABLE statement. This command allows them to specify the table and the new column to be added. The database will then update the schema while preserving the current data in the table. During this process, it's critical to consider how this change affects existing queries, stored procedures, and application logic that interacts with the database. Proper planning, such as testing the changes in a development environment before applying them to production, can help mitigate issues.
Moreover, many development teams use schema migration tools or frameworks that help automate this process. These tools track schema changes in a version control system, enabling teams to apply and rollback changes systematically. For instance, tools like Liquibase or Flyway allow developers to define their schema changes in files, which can then be executed on the target database. This not only ensures a structured approach to schema changes but also helps maintain the integrity of the database while allowing for seamless transitions as applications evolve.