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It occurs when a (master) table links to multiple tables in a one-to-many relationship. The issue derives its name from the visual appearance of the model when it is drawn in an entity–relationship diagram, as the linked tables 'fan out' from the master table. This type of model resembles a star schema, which is a common design in data ...
Visual schema/E-R design: the ability to draw entity-relationship diagrams for the database. If missing, the following two features will also be missing; Reverse engineering - the ability to produce an ER diagram from a database, complete with foreign key relationships
The entity–relationship model proposes a technique that produces entity–relationship diagrams (ERDs), which can be employed to capture information about data model entity types, relationships and cardinality. A Crow's foot shows a one-to-many relationship. Alternatively a single line represents a one-to-one relationship. [4]
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)
The snowflake schema is a variation of the star schema, featuring normalization of dimension tables. In computing, a snowflake schema or snowflake model is a logical arrangement of tables in a multidimensional database such that the entity relationship diagram resembles a snowflake shape.
A table in a SQL database schema corresponds to a predicate variable; the contents of a table to a relation; key constraints, other constraints, and SQL queries correspond to predicates. However, SQL databases deviate from the relational model in many details, and Codd fiercely argued against deviations that compromise the original principles. [3]
This article is a comparison of data modeling tools which are notable, including standalone, conventional data modeling tools and modeling tools supporting data modeling as part of a larger modeling environment.
For example, think of A as Authors, and B as Books. An Author can write several Books, and a Book can be written by several Authors. In a relational database management system, such relationships are usually implemented by means of an associative table (also known as join table, junction table or cross-reference table), say, AB with two one-to-many relationships A → AB and B → AB.