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In SQL, wildcard characters can be used in LIKE expressions; the percent sign % matches zero or more characters, and underscore _ a single character. Transact-SQL also supports square brackets ([and ]) to list sets and ranges of characters to match, a leading caret ^ negates the set and matches only a character not within the list.
Example of QBE query with joins, designed in Borland's Paradox database. Query by Example (QBE) is a database query language for relational databases.It was devised by Moshé M. Zloof at IBM Research during the mid-1970s, in parallel to the development of SQL. [1]
Set operations in SQL is a type of operations which allow the results of multiple queries to be combined into a single result set. [1] Set operators in SQL include UNION, INTERSECT, and EXCEPT, which mathematically correspond to the concepts of union, intersection and set difference.
These operators take a predicate. The First operator returns the first element for which the predicate yields true, or, if nothing matches, throws an exception. The FirstOrDefault operator is like the First operator except that it returns the default value for the element type (usually a null reference) in case nothing matches the predicate.
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 is a well known query language and data manipulation language for relational databases; XQuery is a query language for XML data sources; XPath is a declarative language for navigating XML documents; YQL is an SQL-like query language created by Yahoo! Search engine query languages, e.g., as used by Google [5] or Bing [6]
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Microsoft Access is designed to scale to support more data and users by linking to multiple Access databases or using a back-end database like Microsoft SQL Server. With the latter design, the amount of data and users can scale to enterprise-level solutions.