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A relation is in first normal form if and only if no attribute domain has relations as elements. [1] Or more informally, that no table column can have tables as values. Database normalization is the process of representing a database in terms of relations in standard normal forms, where first normal is a minimal requirement.
In situations where the number of unique values of a column is far less than the number of rows in the table, column-oriented storage allow significant savings in space through data compression. Columnar storage also allows fast execution of range queries (e.g., show all records where a particular column is between X and Y, or less than X.)
Columns have unique names within the same table. Each column has a domain (or data type) which defines the allowed values in the column. All rows in a table have the same set of columns. This definition does not preclude columns having sets or relations as values, e.g. nested tables. This is the major difference to first normal form.
A non-prime attribute of R is an attribute that does not belong to any candidate key of R. [3] Codd defines a transitive dependency of an attribute set X on an attribute set Z as a functional dependency chain X → Y → Z that must be satisfied for some attribute set Y, where it is not the case that Y → X, and all three sets must be disjoint.
Each column in an SQL table declares the type(s) that column may contain. ANSI SQL includes the following data types. [14] Character strings and national character strings. CHARACTER(n) (or CHAR(n)): fixed-width n-character string, padded with spaces as needed; CHARACTER VARYING(n) (or VARCHAR(n)): variable-width string with a maximum size of n ...
It is a tuple (pair) that consists of a key–value pair, where the key is mapped to a value that is a set of columns. In analogy with relational databases, a standard column family is as a "table", each key–value pair being a "row". [1] Each column is a tuple consisting of a column name, a value, and a timestamp. [2]
Normalization splits up data to avoid redundancy (duplication) by moving commonly repeating groups of data into new tables. Normalization therefore tends to increase the number of tables that need to be joined in order to perform a given query, but reduces the space required to hold the data and the number of places where it needs to be updated if the data changes.
In a database, a table is a collection of related data organized in table format; consisting of columns and rows.. In relational databases, and flat file databases, a table is a set of data elements (values) using a model of vertical columns (identifiable by name) and horizontal rows, the cell being the unit where a row and column intersect. [1]