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The skyline operator is the subject of an optimization problem and computes the Pareto optimum on tuples with multiple dimensions. This operator is an extension to SQL proposed by Börzsönyi et al. [ 1 ] to filter results from a database to keep only those objects that are not worse in multiple dimensions than any other.
SQL includes operators and functions for calculating values on stored values. SQL allows the use of expressions in the select list to project data, as in the following example, which returns a list of books that cost more than 100.00 with an additional sales_tax column containing a sales tax figure calculated at 6% of the price.
SQL was initially developed at IBM by Donald D. Chamberlin and Raymond F. Boyce after learning about the relational model from Edgar F. Codd [12] in the early 1970s. [13] This version, initially called SEQUEL (Structured English Query Language), was designed to manipulate and retrieve data stored in IBM's original quasirelational database management system, System R, which a group at IBM San ...
The natural join is arguably one of the most important operators since it is the relational counterpart of the logical AND operator. Note that if the same variable appears in each of two predicates that are connected by AND, then that variable stands for the same thing and both appearances must always be substituted by the same value (this is a ...
FQL enables you to use a SQL-style interface to query the data exposed by the Graph API. It provides advanced features not available in the Graph API. [3] Gellish English is a language that can be used for queries in Gellish English Databases, for dialogues (requests and responses) as well as for information modeling and knowledge modeling; [4]
The most common numerical relational operators used in programming languages are shown below. Standard SQL uses the same operators as BASIC, while many databases allow != in addition to <> from the standard. SQL follows strict boolean algebra, i.e. doesn't use short-circuit evaluation, which is common to most languages below. E.g.
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Database activity monitoring (DAM, a.k.a. Enterprise database auditing and Real-time protection [1]) is a database security technology for monitoring and analyzing database activity. DAM may combine data from network-based monitoring and native audit information to provide a comprehensive picture of database activity.