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Create, alter, and drop schema objects; Grant and revoke privileges and roles; Analyze information on a table, index, or cluster; Establish auditing options; Add comments to the data dictionary; So Oracle Database DDL commands include the Grant and revoke privileges which is actually part of Data control Language in Microsoft SQL server.
PL/SQL refers to a class as an "Abstract Data Type" (ADT) or "User Defined Type" (UDT), and defines it as an Oracle SQL data-type as opposed to a PL/SQL user-defined type, allowing its use in both the Oracle SQL Engine and the Oracle PL/SQL engine. The constructor and methods of an Abstract Data Type are written in PL/SQL.
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).
This is often useful when either tables or their columns have very long or complex names. An alias name could be anything, but usually it is kept short. For example, it might be common to use a table alias such as "pi" for a table named "price_information". The general syntax of an alias is SELECT * FROM table_name [AS] alias_name. Note that ...
Reserved words in SQL and related products In SQL:2023 [3] In IBM Db2 13 [4] In Mimer SQL 11.0 [5] In MySQL 8.0 [6] In Oracle Database 23c [7] In PostgreSQL 16 [1] In Microsoft SQL Server 2022 [2]
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Create/alter table: Yes - can create table, alter its definition and data, and add new rows; Some - can only create/alter table definition, not data; Browse table: Yes - can browse table definition and data; Some - can only browse table definition; Multi-server support: Yes - can manage from the same window/session multiple servers
Only Oracle, DB2, Spark/Hive, and Google Big Query fully implement this feature. More recently, vendors have added new extensions to the standard, e.g. array aggregation functions. These are particularly useful in the context of running SQL against a distributed file system (Hadoop, Spark, Google BigQuery) where we have weaker data co-locality ...