Database Denormalization
Database denormalization is a database optimization technique that involves intentionally adding redundant data to one or more tables to improve read performance at the expense of write performance and data consistency. It reduces the need for complex joins by storing related data together, which can speed up query execution in read-heavy systems. This approach contrasts with normalization, which minimizes redundancy to ensure data integrity.
Developers should use denormalization in scenarios where read performance is critical, such as in data warehousing, reporting systems, or high-traffic web applications where frequent joins slow down queries. It is particularly useful for analytical queries that aggregate large datasets, as it reduces computational overhead by pre-combining data. However, it should be applied judiciously, as it can lead to data anomalies and increased storage costs.