DeNormalization in SQL Server

De-normalization in SQL Server is the process of combining data from multiple tables into a single table to improve read performance. This is often done in scenarios where complex queries need to be executed quickly, such as in Online Analytical Processing (OLAP) systems.

1. Purpose: The main goal is to enhance query performance by reducing the number of joins needed to retrieve data[1].
2. Data Redundancy: De-normalization introduces redundancy by storing the same data in multiple places. This can lead to increased storage requirements and potential data inconsistency[1].
3. Use Cases: It is commonly used in data warehousing and reporting systems where read operations are more frequent than write operations[1].
4. Trade-offs: While it improves read performance, it can make write operations more complex and slower due to the need to update redundant data[1].

Thanks

Denormalization in SQL means simplifying the database by combining tables or adding extra data. This makes it faster to get the data you need, but it can also mean storing the same data in more than one place, which might make updates more complicated. It's like keeping copies of the same information to avoid looking it up every time, making it quicker to access but harder to keep everything in sync.