Which technique improves read performance in databases at the cost of…

Denormalization is the technique that improves read performance in databases by intentionally introducing redundancy into the data structure. While normalization organizes data to minimize duplication and ensure integrity, it often requires complex joins across multiple tables, which can slow down read operations. Denormalization reverses some of these processes by combining tables or duplicating data, allowing queries to retrieve information from fewer sources without extensive joins. This trade-off sacrifices storage efficiency and update consistency for significantly faster read speeds, making it ideal for read-heavy applications like data warehouses. Indexing (Option A) also improves performance but does not inherently create redundancy; it merely provides a lookup path. Normalization (Option B) is the opposite approach, focusing on reducing redundancy to prevent anomalies rather than speeding up reads. Partitioning (Option D) splits data for manageability but does not directly address read performance through redundancy.