Relational database

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A relational database matches data by using common characteristics found within the data set. The resulting groups of data are organized and are much easier for many people to understand.

For example, a data set containing all the real-estate transactions in a town can be grouped by the year the transaction occurred; or it can be grouped by the sale price of the transaction; or it can be grouped by the buyer's last name; and so on.

Such a grouping uses the relational model (a technical term for this is schema). Hence, such a database is called a "relational database."

The software used to do this grouping is called a relational database management system (RDBMS). The term "relational database" often refers to this type of software.

Relational databases are currently the predominant choice in storing financial records, medical records, manufacturing and logistical information, personnel data and much more.



Strictly, a relational database is a collection of relations (frequently called tables). Other items are frequently considered part of the database, as they help to organize and structure the data, in addition to forcing the database to conform to a set of requirements.


The term relational database was originally defined and coined by Edgar Codd at IBM Almaden Research Center in 1970.[1]

Relational database theory uses a set of mathematical terms, which are roughly equivalent to SQL database terminology. The table below summarizes some of the most important relational database terms and their SQL database equivalents.

Relations or Tables

A relation is defined as a set of tuples that have the same attributes. A tuple usually represents an object and information about that object. Objects are typically physical objects or concepts. A relation is usually described as a table, which is organized into rows and columns. All the data referenced by an attribute are in the same domain and conform to the same constraints.

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