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Database virtualization is the decoupling of the database layer, which lies between the storage and application layers within the application stack. Virtualization of the database layer enables a shift away from the physical, toward the logical or virtual. Virtualization enables compute and storage resources to be pooled and allocated on demand.
Data virtualization is an approach to data management that allows an application to retrieve and manipulate data without requiring technical details about the data, such as how it is formatted at source, or where it is physically located, [1] and can provide a single customer view (or single view of any other entity) of the overall data.
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 ...
Database connections are finite and expensive and can take a disproportionately long time to create relative to the operations performed on them. It is inefficient for an application to create, use, and close a database connection whenever it needs to update a database. Connection pooling is a technique designed to alleviate this problem. A ...
In relational databases a virtual column is a table column whose value(s) is automatically computed using other columns values, or another deterministic expression. Virtual columns are defined of SQL:2003 as Generated Column, [1] and are only implemented by some DBMSs, like MariaDB, SQL Server, Oracle, PostgreSQL, SQLite and Firebird (database server) (COMPUTED BY syntax).
Views take very little space to store; the database contains only the definition of a view, not a copy of all the data that it presents. Views structure data in a way that classes of users find natural and intuitive. [2] Just as a function (in programming) can provide abstraction, so can a database view. In another parallel with functions ...
The term is typical of the Oracle DBMS, where the implementation is very general: tables can be associated to SQL functions, which return a predicate as a SQL expression. Whenever a query is executed, the relevant predicates for the involved tables are transparently collected and used to filter rows.
This is an important element of SQL. Statements, which may have a persistent effect on schemata and data, or may control transactions, program flow, connections, sessions, or diagnostics. SQL statements also include the semicolon (";") statement terminator. Though not required on every platform, it is defined as a standard part of the SQL grammar.