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A database refactoring is a simple change to a database schema that improves its design while retaining both its behavioral and informational semantics. Database refactoring does not change the way data is interpreted or used and does not fix bugs or add new functionality. Every refactoring to a database leaves the system in a working state ...
SQL refers to Structured Query Language, a kind of language used to access, update and manipulate database. In SQL, ROLLBACK is a command that causes all data changes since the last START TRANSACTION or BEGIN to be discarded by the relational database management systems (RDBMS), so that the state of the data is "rolled back" to the way it was before those changes were made.
A database trigger is procedural code that is automatically executed in response to certain events on a particular table or view in a database. The trigger is mostly used for maintaining the integrity of the information on the database. For example, when a new record (representing a new worker) is added to the employees table, new records ...
The DROP statement destroys an existing database, table, index, or view. A DROP statement in SQL removes a component from a relational database management system (RDBMS). The types of objects that can be dropped depends on which RDBMS is being used, but most support the dropping of tables , users , and databases .
The database schema is the structure of a database described in a formal language supported typically by a relational database management system (RDBMS). The term " schema " refers to the organization of data as a blueprint of how the database is constructed (divided into database tables in the case of relational databases ).
[4] [5] Supporting schema evolution is a difficult problem involving complex mapping among schema versions and the tool support has been so far very limited. The recent theoretical advances on mapping composition [ 6 ] and mapping invertibility, [ 7 ] which represent the core problems underlying the schema evolution remains almost inaccessible ...
The terms schema matching and mapping are often used interchangeably for a database process. For this article, we differentiate the two as follows: schema matching is the process of identifying that two objects are semantically related (scope of this article) while mapping refers to the transformations between the objects.
An example of a database that has not enforced referential integrity. In this example, there is a foreign key ( artist_id ) value in the album table that references a non-existent artist — in other words there is a foreign key value with no corresponding primary key value in the referenced table.