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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]
Query optimization is a feature of many relational database management systems and other databases such as NoSQL and graph databases.The query optimizer attempts to determine the most efficient way to execute a given query by considering the possible query plans.
Data cleansing or data cleaning is the process of identifying and correcting (or removing) corrupt, inaccurate, or irrelevant records from a dataset, table, or database.It involves detecting incomplete, incorrect, or inaccurate parts of the data and then replacing, modifying, or deleting the affected data. [1]
One thing the most visited websites have in common is that they are dynamic websites. Their development typically involves server-side coding, client-side coding and database technology. The programming languages applied to deliver such dynamic web content vary vastly between sites.
Informix v12.10 and later versions support using sharding techniques to distribute a table across multiple server instances. A distributed Informix database has no upper limit on table or database size. Note (13): Informix DECIMAL type supports up to 32 decimal digits of precision with a range of 10 −130 to 10 125. Fixed and variable ...
The database design documented in these schemas is converted through a Data Definition Language, which can then be used to generate a database. A fully attributed data model contains detailed attributes (descriptions) for every entity within it. The term "database design" can describe many different parts of the design of an overall database ...
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.
The terms schema matching and mapping are often used interchangeably for a database process. For this article, we differentiate the two as follows: schema matching is the process of identifying that two objects are semantically related (scope of this article) while mapping refers to the transformations between the objects.