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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 .
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).
Database tuning describes a group of activities used to optimize and homogenize the performance of a database. It usually overlaps with query tuning, but refers to design of the database files, selection of the database management system (DBMS) application, and configuration of the database's environment ( operating system , CPU , etc.).
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.
In a hierarchical database, a record can contain sets of child records ― known as repeating groups or table-valued attributes.If such a data model is represented as relations, a repeating group would be an attribute where the value is itself a relation.
Data redundancy leads to data anomalies and corruption and generally should be avoided by design; [5] applying database normalization prevents redundancy and makes the best possible usage of storage. [ 6 ]
A hierarchical database model is a data model in which the data is organized into a tree-like structure. The data are stored as records which is a collection of one or more fields . Each field contains a single value, and the collection of fields in a record defines its type .
The changes are first recorded in the log, which must be written to stable storage, before the changes are written to the database. [2] The main functionality of a write-ahead log can be summarized as: [3] Allow the page cache to buffer updates to disk-resident pages while ensuring durability semantics in the larger context of a database system.