What is Denormalization?
Praveen Moosad
Denormalization is opposite to the normalization.Actually it is a process of attempting to optimize the read performance of a by adding redundant data or by grouping data. It is used for fast searching the data in a table.
Denormalization is the process of attempting to optimize the read performance of a database by adding redundant data or by grouping data.In some cases, denormalization is a means of addressing performance or scalability in relational database software.
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Denormalization is just opposite approach of normalization . Denor. we add some redundant data to increase performance........
In computing, denormalization is the process of attempting to optimize the read performance of a database by adding redundant data or by grouping data. In some cases, denormalization is a means of addressing performance or scalability in relational database software.
De-Normalization is the process which increase dependency and redundancy in data.
In a relational database, denormalization is an approach to optimizing performance in which the administrator selectively adds back specific instances of duplicate data after the data structure has been normalized.
Normalize the database until it hurts you. Denormalized the database until you achieve your goal.
Denormalization is the process of attempting to optimize the read performance of a database by adding redundant data or by grouping data.[1][2] In some cases, denormalization helps cover up the inefficiencies inherent in relational database software. A relational normalized database imposes a heavy access load over physical storage of data even if it is well tuned for high performance.
Denormalization is the reverse process of the normalization process. Denormalization works by adding redundant data or grouping data to optimize the performance. Even though, adding redundant data sounds counter-productive, sometimes denormalization is a very important process to overcome some of the shortcomings in the relational database software that may incur heavy performance penalties with normalized databases (even tuned for higher performance). This is because joining several relations (which are results of normalizing) to produce a result to a query can sometimes be slow depending on the actual physical implementation of the database systems.