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Database normalization is the process of structuring a relational database in accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity. It was first proposed by British computer scientist Edgar F. Codd as part of his relational model .
Denormalization is a strategy used on a previously-normalized database to increase performance. In computing , denormalization is the process of trying to improve the read performance of a database , at the expense of losing some write performance, by adding redundant copies of data or by grouping data.
A database relation (e.g. a database table) is said to meet third normal form standards if all the attributes (e.g. database columns) are functionally dependent on solely a key, except the case of functional dependency whose right hand side is a prime attribute (an attribute which is strictly included into some key).
A database transaction symbolizes a unit of work, performed within a database management system (or similar system) against a database, that is treated in a coherent and reliable way independent of other transactions. A transaction generally represents any change in a database. Transactions in a database environment have two main purposes:
This represents a "commit" operation in which the corresponding transaction has successfully completed its preceding actions, and has made all its changes permanent in the database. Alternatively, a schedule can be represented with a directed acyclic graph (or DAG) in which there is an arc (i.e., directed edge ) between each ordered pair of ...
The relational model (RM) is an approach to managing data using a structure and language consistent with first-order predicate logic, first described in 1969 by English computer scientist Edgar F. Codd, [1] [2] where all data are represented in terms of tuples, grouped into relations.
In database systems, consistency (or correctness) refers to the requirement that any given database transaction must change affected data only in allowed ways. Any data written to the database must be valid according to all defined rules, including constraints, cascades, triggers, and any combination thereof. This does not guarantee correctness ...
Isolation is typically enforced at the database level. However, various client-side systems can also be used. It can be controlled in application frameworks or runtime containers such as J2EE Entity Beans [2] On older systems, it may be implemented systemically (by the application developers), for example through the use of temporary tables.