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The basic data structure of the relational model is the table, where information about a particular entity (say, an employee) is represented in rows (also called tuples) and columns. Thus, the "relation" in "relational database" refers to the various tables in the database; a relation is a set of tuples. The columns enumerate the various ...
A relational model organizes data into one or more tables (or "relations") of columns and rows, with a unique key identifying each row. Rows are also called records or tuples. [16] Columns are also called attributes. Generally, each table/relation represents one "entity type" (such as customer or product).
The relational model (RM) is an approach to managing data using a structure and language consistent with first-order predicate logic, first described in 1969 by English computer scientist Edgar F. Codd, [1] [2] where all data are represented in terms of tuples, grouped into relations.
Consequently, the ER model becomes an abstract data model, [1] that defines a data or information structure that can be implemented in a database, typically a relational database. Entity–relationship modeling was developed for database and design by Peter Chen and published in a 1976 paper, [2] with variants of the idea existing previously. [3]
Codd's twelve rules [1] are a set of thirteen rules (numbered zero to twelve) proposed by Edgar F. Codd, a pioneer of the relational model for databases, designed to define what is required from a database management system in order for it to be considered relational, i.e., a relational database management system (RDBMS).
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 ).
Database design is the organization of data according to a database model.The designer determines what data must be stored and how the data elements interrelate. With this information, they can begin to fit the data to the database model. [1]
Horizontal partitioning splits one or more tables by row, usually within a single instance of a schema and a database server. It may offer an advantage by reducing index size (and thus search effort) provided that there is some obvious, robust, implicit way to identify in which partition a particular row will be found, without first needing to search the index, e.g., the classic example of the ...