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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]
An associative entity is a term used in relational and entity–relationship theory. A relational database requires the implementation of a base relation (or base table) to resolve many-to-many relationships. A base relation representing this kind of entity is called, informally, an associative table. An associative entity (using Chen notation)
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).
A table that conforms to the relational model has a primary key which uniquely identifies a row. In our example, the primary key is a composite key of {Title, Format} (indicated by the underlining):
A sample entity–relationship diagram. One of the most common types of conceptual schemas is the ER (entity–relationship model) diagrams. Attributes in ER diagrams are usually modeled as an oval with the name of the attribute, linked to the entity or relationship that contains the attribute.
A relational database contains multiple tables, each similar to the one in the "flat" database model. One of the strengths of the relational model is that, in principle, any value occurring in two different records (belonging to the same table or to different tables), implies a relationship among those two records.
The enhanced entity–relationship (EER) model (or extended entity–relationship model) in computer science is a high-level or conceptual data model incorporating extensions to the original entity–relationship (ER) model, used in the design of databases.
A table may contain both duplicate rows and duplicate columns, and a table's columns are explicitly ordered. SQL uses a Null value to indicate missing data, which has no analog in the relational model. Because a row can represent unknown information, SQL does not adhere to the relational model's Information Principle. [7]: 153–155, 162