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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 .
T2 could read a database object A, modified by T1 which hasn't committed. This is a dirty or inconsistent read. T1 may write some value into A which makes the database inconsistent. It is possible that interleaved execution can expose this inconsistency and lead to an inconsistent final database state, violating ACID rules.
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).
In computer science, in the field of databases, read–write conflict, also known as unrepeatable reads, is a computational anomaly associated with interleaved execution of transactions. Specifically, a read–write conflict occurs when a "transaction requests to read an entity for which an unclosed transaction has already made a write request."
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.
"Don't repeat yourself" (DRY), also known as "duplication is evil", is a principle of software development aimed at reducing repetition of information which is likely to change, replacing it with abstractions that are less likely to change, or using data normalization which avoids redundancy in the first place.
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.
In computer science, Algorithms for Recovery and Isolation Exploiting Semantics, or ARIES, is a recovery algorithm designed to work with a no-force, steal database approach; it is used by IBM Db2, Microsoft SQL Server and many other database systems. [1] IBM Fellow Chandrasekaran Mohan is the primary inventor of the ARIES family of algorithms. [2]