denormalitzades

Denormalitzades is a term that describes a database design approach where data redundancy is intentionally introduced into a relational database. This is in contrast to normalization, which aims to reduce redundancy by organizing data into multiple tables with relationships. Denormalization is typically employed to improve read performance by reducing the need for complex joins.

In a denormalized database, data that would normally be spread across several tables is consolidated into fewer, larger tables. For example, customer order information that might be in separate customer, order, and product tables in a normalized schema could be combined into a single table for faster retrieval of complete order details. This reduces the processing overhead associated with executing multiple queries and joining their results.

However, denormalization comes with trade-offs. The increased data redundancy can lead to several issues. Data integrity can be compromised as updates to redundant data need to be made in multiple locations, increasing the risk of inconsistencies. Storage space requirements also increase due to the duplication of data. Furthermore, write operations become more complex and slower because multiple records may need to be updated simultaneously.

The decision to denormalize is usually driven by performance requirements, particularly in scenarios where read operations significantly outweigh write operations, such as in data warehousing or reporting systems. It is a technique that requires careful consideration of the balance between read performance gains and the potential drawbacks in terms of storage and data integrity.