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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 is represented in terms of tuples, grouped into relations.
The concept of relational database was defined by E. F. Codd at IBM in 1970. Codd introduced the term relational in his research paper "A Relational Model of Data for Large Shared Data Banks". [2] In this paper and later papers, he defined what he meant by relation.
The dimensional model is a specialized adaptation of the relational model used to represent data in data warehouses in a way that data can be easily summarized using online analytical processing, or OLAP queries. In the dimensional model, a database schema consists of a single large table of facts that are described using dimensions and measures.
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).
A semantic model is a model of concepts and is sometimes called a "platform independent model". It is an intensional model. At least since Carnap, it is well known that: [18] "...the full meaning of a concept is constituted by two aspects, its intension and its extension.
As the relational model became fashionable in the early 1980s, Codd fought a sometimes bitter campaign to prevent the term from being misused by database vendors who had merely added a relational veneer to older technology. As part of this campaign, he published his 12 rules to define what constituted a relational database. This made his ...
The overall goal of semantic data models is to capture more meaning of data by integrating relational concepts with more powerful abstraction concepts known from the artificial intelligence field. The idea is to provide high level modeling primitives as integral part of a data model in order to facilitate the representation of real world ...
[5] [6] A relational database definition (database schema, sometimes referred to as a relational schema) can thus be thought of as a collection of named relation schemas. [7] [8] In implementations, the domain of each attribute is effectively a data type [9] and a named relation schema is effectively a relation variable (relvar for short).