Denormalisierte

Denormalisierte (denormalization) refers to a database design technique used to improve data retrieval performance by intentionally introducing redundancy into a database table. Unlike normalization, which organizes data to reduce duplication and dependency, denormalization involves combining tables or adding redundant data to decrease the number of joins required for queries.

The primary goal of denormalisierung is to optimize read operations, especially in systems where quick data access is critical, such as data warehouses, reporting tools, or real-time applications. By storing redundancy, denormalization minimizes the need for complex joins, thereby reducing query response times.

However, denormalization comes with trade-offs. Increased redundancy can lead to challenges in maintaining data consistency, as updates must be propagated across multiple locations. It can complicate data management and increase storage requirements. Therefore, its implementation is typically guided by specific performance needs and carefully balanced against the potential drawbacks.

In practice, denormalization might involve duplicating fields, combining multiple normalized tables into a single table, or creating summary tables with aggregated data. It is often used after the normalization process has been initially applied, especially when read performance takes precedence over storage efficiency and data integrity.

Overall, denormalized structures are useful in scenarios where read performance is paramount, but they require diligent management to ensure data accuracy and consistency across the database.