When do you normalize your database design?

1 What is normalization?

Normalization is the process of applying a series of rules or normal forms to a database design to ensure that each table has a clear purpose and that the data is not duplicated or inconsistent. The most common normal forms are the first, second, and third normal forms (1NF, 2NF, and 3NF), which require that each table has a primary key, that each column depends on the whole primary key, and that each column depends only on the primary key, respectively. There are also higher normal forms, such as the Boyce-Codd normal form (BCNF), the fourth normal form (4NF), and the fifth normal form (5NF), which address more complex scenarios involving functional dependencies, multivalued dependencies, and join dependencies.

2 What are the benefits of normalization?

Normalization can have several benefits for database design, such as reducing data redundancy and storage space, improving data integrity and consistency, and simplifying queries and data manipulation. By eliminating duplicate or unnecessary data, normalization can save disk space and avoid data anomalies. Furthermore, by enforcing constraints and relationships, it can ensure that the data is valid and accurate. Additionally, having a clear and logical structure makes it easier to write and execute queries, as well as to perform operations such as joins, aggregations, and indexing.

3 What are the drawbacks of normalization?

Normalization can have some drawbacks for database design, such as increasing complexity and overhead. With more tables and columns, the design can be more complex and difficult to understand, particularly for higher normal forms. It can also increase the overhead of maintaining and querying the database, as it may require more joins, foreign keys, and transactions. Furthermore, normalization can affect the performance and efficiency of the database, necessitating more disk accesses, memory usage, and network traffic. Additionally, it can reduce the flexibility and scalability of the database by limiting options for data modeling, partitioning, and caching.

4 What is denormalization?

Denormalization is the process of reversing or relaxing some of the rules or normal forms applied to a database design to improve performance or functionality. Denormalization can involve adding redundant or derived data, combining or splitting tables, or changing the primary keys or foreign keys. Denormalization can help optimize the database for specific queries, operations, or applications.

5 What are the benefits of denormalization?

Denormalization can have several benefits for database design, such as improving performance and efficiency by reducing the number of tables and columns. This may reduce disk accesses, memory usage, and network traffic, as well as enhance the flexibility and scalability of the database. Additionally, denormalization can simplify complexity and overhead by creating fewer tables and columns, which makes the database design easier to understand. It may also decrease the overhead of maintaining and querying the database by requiring fewer joins, foreign keys, and transactions.

6 What are the drawbacks of denormalization?

Denormalization can have some drawbacks for database design, such as increasing data redundancy and storage space, reducing data integrity and consistency, and complicating queries and data manipulation. By adding duplicate or unnecessary data, denormalization can waste disk space and create data anomalies. It can also violate constraints and relationships, compromising the validity and accuracy of the data. Furthermore, denormalization can make it harder to write and execute queries, as well as to perform operations such as joins, aggregations, and indexing.

7 Here’s what else to consider

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