What is the Difference Between Normalization and Denormalization?

The main difference between normalization and denormalization lies in their approaches to data organization and performance optimization in a database. Here are the key differences between the two:

1. Data Integrity: Normalization maintains data integrity, meaning that any addition or deletion of data from the table will not create any mismatch in the relationship of the data. In contrast, denormalization does not maintain data integrity.
2. Redundancy: Normalization reduces data redundancy and inconsistency by storing non-redundant and consistent data in a set schema. Denormalization, on the other hand, combines data to execute queries quickly, adding redundancy for performance gains.
3. Number of Tables: Normalization increases the number of tables and joins, as it divides the data into multiple tables to remove redundancy. Denormalization decreases the number of tables and joins by combining multiple table data into one.
4. Performance: Normalization optimizes the use of disk space and is faster in performance. Denormalization, while optimizing query performance, introduces some memory wastage.
5. Use Cases: Normalization is generally used when a large number of insert, update, and delete operations are performed, and data consistency is required. Denormalization is used when faster search and analysis are more important, and to optimize read performance, especially for read-heavy workloads or reporting databases.

In conclusion, the choice between normalization and denormalization depends on the specific requirements and constraints of your database and application. By understanding the nuances of these approaches and carefully evaluating your application's needs, you can craft a database that strikes the perfect equilibrium between data integrity and performance.

Comparative Table: Normalization vs Denormalization

Here is a table comparing normalization and denormalization:

In conclusion, normalization is used when faster insertion, deletion, and update operations are required, while denormalization is used when faster query execution is more important and to optimize the read.