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Referential integrity is a property of data stating that all its references are valid. In the context of relational databases , it requires that if a value of one attribute (column) of a relation (table) references a value of another attribute (either in the same or a different relation), then the referenced value must exist.
An example of a data-integrity mechanism is the parent-and-child relationship of related records. If a parent record owns one or more related child records all of the referential integrity processes are handled by the database itself, which automatically ensures the accuracy and integrity of the data so that no child record can exist without a parent (also called being orphaned) and that no ...
A foreign key is a set of attributes in a table that refers to the primary key of another table, linking these two tables. In the context of relational databases, a foreign key is subject to an inclusion dependency constraint that the tuples consisting of the foreign key attributes in one relation, R, must also exist in some other (not necessarily distinct) relation, S; furthermore that those ...
Third normal form (3NF) is a database schema design approach for relational databases which uses normalizing principles to reduce the duplication of data, avoid data anomalies, ensure referential integrity, and simplify data management.
Referential integrity statements [ edit ] Another type of DDL sentence in SQL is used to define referential integrity relationships, usually implemented as primary key and foreign key tags in some columns of the tables.
When surrogate keys supplant natural keys, then domain specific referential integrity will be compromised. For example, in a customer master table, the same customer may have multiple records under separate customer IDs, even though the natural key (a combination of customer name, date of birth, and e-mail address) would be unique.
Query rewriting is a typically automatic transformation that takes a set of database tables, views, and/or queries, usually indices, often gathered data and query statistics, and other metadata, and yields a set of different queries, which produce the same results but execute with better performance (for example, faster, or with lower memory use). [1]
It is particularly important in databases with referential integrity, third normal form, or perfect key. "Data hierarchy" is the result of proper arrangement of data without redundancy. Avoiding redundancy eventually leads to proper "data hierarchy" representing the relationship between data, and revealing its relational structure.