Denormalization
Data denormalization is the process of restructuring a relational database by adding redundant data to one or more tables. The aim is to improve query performance by reducing the need for joins. The term refers to removing one or more normalization forms to achieve this goal. Normalization is a database design technique focused on minimizing data redundancy and inconsistency
The idea behind data denormalization is that it is faster to fetch data from a single table than to join data from multiple tables. When dealing with large datasets, the performance boost can be significant. By denormalizing data, a company can optimize query performance and, as a result, enable faster data processing and analytics.
References
-
Learn about denormalization in databases: its pros and cons, techniques, and when to use it. Discover how it can improve your database performance.🔗blog.invgate.com -
Sometimes a properly normalized database isn’t high-performing enough, so developers use a reverse method − they denormalize it. If you don’t have a clear understanding of when and how you should denormalize a database, read our article and find out everything you need to know about database denormalization.🔗rubygarage.org -
Data Denormalization is the process of optimizing data models for easier processing and analytics, by reducing the number of normalized tables and increasing redundancy.🔗dremio.com -
A Computer Science portal for geeks. It contains well written, well thought and well explained computer science and programming articles, quizzes and practice/competitive programming/company interview Questions.🔗GeeksforGeeks