Normalization vs. Denormalization (original) (raw)

Last Updated : 31 Jan, 2026

Normalisation and denormalisation are used to alter the structure of a database. The key difference is that normalisation reduces redundancy by organising data into smaller, well-structured tables, while denormalisation intentionally introduces redundancy by merging tables to speed up query performance.

Normalisation

Normalisation is the method used in a database to reduce data redundancy and data inconsistency in the table. It is the technique in which non-redundant and consistent data are stored in a set schema. By using normalisation, the number of tables is increased instead of decreased.

Benefits

• Data is reduced in the table.
• Optimized memory.
• Maintain data integrity.

Drawbacks

• The number of tables is increased.
• Consume more resources when using expensive operations.
• Query performance may decrease due to multiple table joins.

Example of Normalization

Denormalization

Denormalization is also the method which is used in a database. It is used to add the redundancy to execute the query quickly. It is a technique in which data are combined to execute the query quickly. By using denormalization the number of tables is decreased which oppose to the normalization.

Benefits

• Execute the query quickly.
• Fewer joins are needed, so queries execute faster.
• Improves read performance for complex queries.

Drawbacks

• Wastage of memory because store the duplicate data.
• Complex data maintenance occurs because INSERT, UPDATE, and DELETE operations become harder due to data redundancy.
• Does not maintain data integrity.

Example of Denormalization

**Normalization and Denormalization