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A database trigger is like a stored procedure that Oracle Database invokes automatically whenever a specified event occurs. It is a named PL/SQL unit that is stored in the database and can be invoked repeatedly. Unlike a stored procedure, you can enable and disable a trigger, but you cannot explicitly invoke it.
In SQL, the data manipulation language comprises the SQL-data change statements, [3] which modify stored data but not the schema or database objects. Manipulation of persistent database objects, e.g., tables or stored procedures, via the SQL schema statements, [3] rather than the data stored within them, is considered to be part of a separate data definition language (DDL).
These sub-languages are mainly categorized into four categories: a data query language (DQL), a data definition language (DDL), a data control language (DCL), and a data manipulation language (DML). Sometimes a transaction control language (TCL) [ 1 ] is argued to be part of the sub-language set as well.
Oracle Database 23ai: 23.4.0 On May 2, 2024, Oracle Database 23ai [10] was released on Oracle Cloud Infrastructure (OCI) as cloud services, including OCI Exadata Database Service, OCI Exadata Database Cloud@Customer, and OCI Base Database Service. It is also available in Always Free Autonomous Database.
Oracle Streams was the flow of information either within a single database or from one database to another. Oracle Streams can be set up in homogeneous (all Oracle databases) or heterogeneous (non-Oracle and Oracle databases) environments. The Streams setup used a set of processes and database objects to share data and messages.
A data control language (DCL) is a syntax similar to a computer programming language used to control access to data stored in a database (authorization).In particular, it is a component of Structured Query Language (SQL).
A parallel database system seeks to improve performance through parallelization of various operations, such as loading data, building indexes and evaluating queries. [1] Although data may be stored in a distributed fashion, the distribution is governed solely by performance considerations.
Sequential vs. data-parallel job execution. Data parallelism is parallelization across multiple processors in parallel computing environments. It focuses on distributing the data across different nodes, which operate on the data in parallel. It can be applied on regular data structures like arrays and matrices by working on each element in ...