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Object Query Language (OQL) is a query language standard for object-oriented databases modeled after SQL and developed by the Object Data Management Group (ODMG). Because of its overall complexity the complete OQL standard has not yet been fully implemented in any software.
A database object is a structure for storing, managing and presenting application- or user-specific data in a database. Depending on the database management system (DBMS), many different types of database objects can exist. [1] [2] The following is a list of the most common types of database objects found in most relational databases (RDBMS):
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 ...
Consists of a curated set of orthogonal transformations, which are combined together to form a pipeline. PTQL based on relational queries over program traces, allowing programmers to write expressive, declarative queries about program behavior. QUEL is a relational database access language, similar in most ways to SQL; RDQL is a RDF query language;
This could be modeled in an object-oriented implementation by a "Person object" with an attribute/field to hold each data item that the entry comprises: the person's name, a list of phone numbers, and a list of addresses. The list of phone numbers would itself contain "PhoneNumber objects" and so on.
In a SQL database query, a correlated subquery (also known as a synchronized subquery) is a subquery (a query nested inside another query) that uses values from the outer query. This can have major impact on performance because the correlated subquery might get recomputed every time for each row of the outer query is processed.
The programming model becomes what a SQL statement would be like with multiple WHERE clauses. The combination of list-aware subjects and objects plus a pipeline approach can yield extremely expressive queries spanning many different domains of data. Here is a more comprehensive example that illustrates the pipeline using some syntax shortcuts.
DQL statements are used for performing queries on the data within schema objects. The purpose of DQL commands is to get the schema relation based on the query passed to it. Although often considered part of DML, the SQL SELECT statement is strictly speaking an example of DQL. When adding FROM or WHERE data manipulators to the SELECT statement ...