Schema change
A schema change alters database structure, such as tables, columns, data types or constraints on permitted data.
Evolve the data structure
A schema change alters the structure of a database. This includes adding or removing columns, changing data types and adding constraints. In a fictional example, a job gains a required field for its responsible service region.
This raises questions about existing records and older application versions that do not yet provide the field. Plan data transition, checks and rollout order together. Removing a column can lose stored information. Whether a change locks access, takes a long time or can happen without interruption depends on the system, dataset and specific change. A successful structural change alone does not confirm that every affected workflow still works.
Sources
Related terms
- Data validationData validation checks data against defined requirements such as format, required fields or permitted value ranges.
- Unique keyA unique key constrains values or combinations so they cannot occur more than once within the defined data scope.
- Foreign keyA foreign key protects a defined reference between records through matching key values.
- Legacy systemAn existing system still in use, with technical and business dependencies accumulated over time.
- Multi-tenancyMulti-tenancy supports separate customer or group scopes in one solution. A tenant is not automatically one person or one database.
- Browser cacheThe browser cache stores suitable HTTP responses for later use. Reuse and revalidation follow the applicable rules.
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