What is the difference between denormalization and normalization in database management?

Database Normalisation Questions



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What is the difference between denormalization and normalization in database management?

Normalization and denormalization are two techniques used in database management to optimize the structure and performance of a database.

Normalization is the process of organizing data in a database to eliminate redundancy and improve data integrity. It involves breaking down a database into multiple tables and defining relationships between them. The main goal of normalization is to minimize data duplication and ensure that each piece of data is stored in only one place. This helps to reduce data anomalies, improve data consistency, and simplify data maintenance.

Denormalization, on the other hand, is the process of intentionally introducing redundancy into a database. It involves combining tables or duplicating data to improve query performance and simplify data retrieval. Denormalization is typically used in situations where read operations are more frequent than write operations, and the need for faster query execution outweighs the potential drawbacks of data redundancy. By denormalizing a database, it is possible to reduce the number of joins required in complex queries, resulting in faster response times.

In summary, normalization focuses on eliminating redundancy and improving data integrity, while denormalization aims to improve query performance by introducing redundancy. Both techniques have their own advantages and should be used judiciously based on the specific requirements of the database and the application.