Database Normalisation Questions Medium
The process of denormalizing a database involves intentionally introducing redundancy into the database design by combining or duplicating data from multiple tables. This is done to improve the performance of certain queries or to simplify complex joins between tables.
Denormalization is typically done in situations where the database is heavily read-oriented and there is a need for faster query execution. By denormalizing the database, the number of joins required to retrieve data can be reduced, resulting in improved query performance.
There are several techniques for denormalizing a database, including:
1. Combining tables: This involves merging two or more tables into a single table. For example, if there is a one-to-one relationship between two tables, they can be combined into a single table to eliminate the need for a join.
2. Duplicating data: This involves duplicating data from one table into another table. For example, if there is a frequently accessed column in a table, it can be duplicated into another table to avoid the need for a join.
3. Adding derived columns: This involves adding additional columns to a table that can be derived from existing columns. These derived columns can store pre-calculated values, reducing the need for complex calculations during query execution.
4. Creating summary tables: This involves creating additional tables that store aggregated or summarized data from multiple tables. These summary tables can be used to quickly retrieve aggregated information without the need for complex joins and calculations.
It is important to note that denormalization should be used judiciously and only in specific cases where the benefits outweigh the potential drawbacks. Denormalization can lead to data redundancy, increased storage requirements, and potential data inconsistencies if not carefully managed. Therefore, it is crucial to carefully analyze the database requirements and performance needs before deciding to denormalize a database.