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A trigger cannot be attached to more than one operation (INSERT, DELETE, UPDATE), so a trigger must be created for each operation. The old and new values are exposed as fields of a record data structures. The names of these records can be defined, in this example they are named as O for old values and N for new values.
An example of implementation of triggers in non-relational database can be Sedna, that provides support for triggers based on XQuery. Triggers in Sedna were designed to be analogous to SQL:2003 triggers, but natively base on XML query and update languages (XPath, XQuery and XML update language). A trigger in Sedna is set on any nodes of an XML ...
A view update is done by key preservation. Some systems support the definition of INSTEAD OF triggers on views. This technique allows the definition of other logic for execution in place of an insert, update, or delete operation on the views. Thus database systems can implement data modifications based on read-only views.
If the trigger is created on a schema or the database, then the triggering event is composed of either DDL or database operation statements, and the trigger is called a system trigger. An INSTEAD OF trigger is either: A DML trigger created on a view or a system trigger defined on a CREATE statement.
Data Control Language is one of the logical group in SQL Commands. SQL [1] is the standard language for relational database management systems. SQL statements are used to perform tasks such as insert data to a database, delete or update data in a database, or retrieve data from a database.
Each column in an SQL table declares the type(s) that column may contain. ANSI SQL includes the following data types. [14] Character strings and national character strings. CHARACTER(n) (or CHAR(n)): fixed-width n-character string, padded with spaces as needed; CHARACTER VARYING(n) (or VARCHAR(n)): variable-width string with a maximum size of n ...
Whenever a query or an update addresses an ordinary view's virtual table, the DBMS converts these into queries or updates against the underlying base tables. A materialized view takes a different approach: the query result is cached as a concrete ("materialized") table (rather than a view as such) that may be updated from the original base ...
Microsoft's Entity Framework (including Code-First) has built-in support for OCC based on a binary timestamp value. [9] Most revision control systems support the "merge" model for concurrency, which is OCC. [citation needed] Mimer SQL is a DBMS that only implements optimistic concurrency control. [10] Google App Engine data store uses OCC. [11]