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The word 'field' is normally used interchangeably with 'column'. [5] However, database perfectionists tend to favor using 'field' to signify a specific cell of a given row. [citation needed] This is to enable accuracy in communicating with other developers. Columns (really column names) being referred to as field names (common for each row ...
Relation, tuple, and attribute represented as table, row, and column respectively. In database theory, a relation, as originally defined by E. F. Codd, [1] is a set of tuples (d 1,d 2,...,d n), where each element d j is a member of D j, a data domain. Codd's original definition notwithstanding, and contrary to the usual definition in ...
An attribute in a relational database can be represented as a column or field. In computing, an attribute is a specification that defines a property of an object, element, or file. It may also refer to or set the specific value for a given instance of such. For clarity, attributes should more correctly be considered metadata. An attribute is ...
Attribute or field: A labeled element of a tuple, e.g. "Address" or "Date of birth" Table: Relation or Base relvar: A set of tuples sharing the same attributes; a set of columns and rows View or result set: Derived relvar: Any set of tuples; a data report from the RDBMS in response to a query
The heading defines a set of attributes, each with a name and data type (sometimes called a domain). The number of attributes in this set is the relation's degree or arity. The body is a set of tuples. A tuple is a collection of n values, where n is the relation's degree, and each value in the tuple corresponds to a unique attribute. [6]
In the relational model of databases, a primary key is a designated attribute that can reliably identify and distinguish between each individual record in a table.The database creator can choose an existing unique attribute or combination of attributes from the table (a natural key) to act as its primary key, or create a new attribute containing a unique ID that exists solely for this purpose ...
Multivalue databases are "lumpy" data, in that they can store exactly the same way as relational databases, but they also permit a level of depth which the relational model can only approximate using sub-tables. This is nearly identical to the way XML expresses data, where a given field/attribute can have multiple right answers at the same time.
In practice, data elements (fields, columns, attributes, etc.) are sometimes "overloaded", meaning a given data element will have multiple potential meanings. While a known bad practice, overloading is nevertheless a very real factor or barrier to understanding what a system is doing.