denormalizes

Denormalization is a database optimization technique that involves intentionally introducing redundancy into a database schema, which is normally designed to reduce redundancy. In a normalized database, data is split into multiple tables to avoid data duplication and ensure data integrity. Denormalization reverses this process by combining tables or adding duplicate data to improve read performance.

The primary motivation for denormalization is to speed up data retrieval. By reducing the number of joins required to fetch information, queries can execute more quickly. This is particularly beneficial in read-heavy applications where performance is critical. For example, instead of joining customer and order tables, an order table might include customer name and address directly, eliminating the need for a join.

However, denormalization comes with trade-offs. The increased redundancy can lead to data inconsistency if updates are not managed carefully. Maintaining data integrity becomes more complex as the same information may need to be updated in multiple locations. Storage space can also increase due to the duplicated data. Therefore, denormalization is typically applied selectively to specific tables or queries where performance gains outweigh the risks and complexities of data maintenance. It is a design choice made after careful consideration of an application's specific needs and performance bottlenecks.