De-Normalization:
De-normalization is the process of attempting to optimize the performance of a database by adding redundant data. It is sometimes necessary because current DBMSs implement the relational model poorly.
A true relational DBMS would allow for a fully normalized database at the logical level, while providing physical storage of data that is tuned for high performance. De-normalization is a technique to move from higher to lower normal forms of database modeling in order to speed up database access.
* Many critical queries and reports exist which rely upon data from more than one table. Often times these requests need to be processed in an on-line environment.
* Repeating groups exist which need to be processed in a group instead of individually.
* Many calculations need to be applied to one or many columns before queries can be successfully answered.
* Tables need to be accessed in different ways by different users during the same timeframe.
* Many large primary keys exist which are clumsy to query and consume a large amount of DASD when carried as foreign key columns in related tables.
* Certain columns are queried a large percentage of the time. Consider 60% or greater to be a cautionary number flagging de-normalization as an option.
De-normalization is the process of attempting to optimize the performance of a database by adding redundant data. It is sometimes necessary because current DBMSs implement the relational model poorly.
A true relational DBMS would allow for a fully normalized database at the logical level, while providing physical storage of data that is tuned for high performance. De-normalization is a technique to move from higher to lower normal forms of database modeling in order to speed up database access.
* Many critical queries and reports exist which rely upon data from more than one table. Often times these requests need to be processed in an on-line environment.
* Repeating groups exist which need to be processed in a group instead of individually.
* Many calculations need to be applied to one or many columns before queries can be successfully answered.
* Tables need to be accessed in different ways by different users during the same timeframe.
* Many large primary keys exist which are clumsy to query and consume a large amount of DASD when carried as foreign key columns in related tables.
* Certain columns are queried a large percentage of the time. Consider 60% or greater to be a cautionary number flagging de-normalization as an option.
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