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A relational database is a digital database based on the relational model of data, as proposed by E. F. Codd in 1970.[1] A software system used to maintain relational databases is a relational database management system (RDBMS). Many relational database systems have an option of using the SQL (Structured Query Language) for querying and maintaining the database.[2]

History

The term "relational database" was invented by E. F. Codd at IBM in 1970. Codd introduced the term in his research paper "A Relational Model of Data for Large Shared Data Banks".[3] In this paper and later papers, he defined what he meant by "relational". One well-known definition of what constitutes a relational database system is composed of Codd's 12 rules. However, no commercial implementations of the relational model conform to all of Codd's rules,[4] so the term has gradually come to describe a broader class of database systems, which at a minimum:

  1. Present the data to the user as relations (a presentation in tabular form, i.e. as a collection of tables with each table consisting of a set of rows and columns);
  2. Provide relational operators to manipulate the data in tabular form.

In 1974, IBM began developing System R, a research project to develop a prototype RDBMS.[5][6] The first system sold as an RDBMS was Multics Relational Data Store (June 1976).[citation needed] Oracle was released in 1979 by Relational Software, now Oracle Corporation.[7] Ingres and IBM BS12 followed. Other examples of an RDBMS include DB2, SAP Sybase ASE, and Informix. In 1984,

The term "relational database" was invented by E. F. Codd at IBM in 1970. Codd introduced the term in his research paper "A Relational Model of Data for Large Shared Data Banks".[3] In this paper and later papers, he defined what he meant by "relational". One well-known definition of what constitutes a relational database system is composed of Codd's 12 rules. However, no commercial implementations of the relational model conform to all of Codd's rules,[4] so the term has gradually come to describe a broader class of database systems, which at a minimum:

  1. Present the data to the user as relations (a presentation in tabular form, i.e. as a collection of tables with each table consisting of a set of rows and columns);
  2. Provide relational operators to manipulate the data in tabular form.

In 1974, IBM began developing System R, a research project to develop a prototype RDBMS.[5][6] The first system sold as an RDBMS was Multics Relational Data Store (June 1976).[citation needed] Oracle was released in 1979 by Relational Software, now Oracle Corporation.[7] Ingres and IBM BS12 followed. Other examples of an RDBMS include DB2, SAP Sybase ASE, and Informix. In 1984, the first RDBMS for Macintosh began being developed, code-named Silver Surfer, it was later released in 1987 as 4th Dimension and known today as 4D.[8]

The first systems that were relatively faithful implementations of the relational model were from:

  • University of Michigan – Micro DBMS (1969)[citation needed]
  • Massachusetts Institute of Technology (1971)[9]
  • IBM UK Scientific Centre at Peterlee – IS1 (1970–72) and its successor, PRTV (1973–79)

The most common definition of an RDBMS is a product that presents a view of data as a collection of rows and columns, even if it is not based strictly upon relational theory. By this definition, RDBMS products typically implement some but not all of Codd's 12 rules.

A second school of thought argues that if a database does not implement all of Codd's rules (or the current understanding on the relational model, as expressed by Christopher J. Date, Hugh Darwen and others), it is not relational. This view, shared by many theorists and other strict adherents to Codd's principles, would disqualify most DB

In 1974, IBM began developing System R, a research project to develop a prototype RDBMS.[5][6] The first system sold as an RDBMS was Multics Relational Data Store (June 1976).[citation needed] Oracle was released in 1979 by Relational Software, now Oracle Corporation.[7] Ingres and IBM BS12 followed. Other examples of an RDBMS include DB2, SAP Sybase ASE, and Informix. In 1984, the first RDBMS for Macintosh began being developed, code-named Silver Surfer, it was later released in 1987 as 4th Dimension and known today as 4D.[8]

The first systems that were relatively faithful implementations of the relational model were from:

  • University of Michigan – Micro DBMS (1969)[relational theory. By this definition, RDBMS products typically implement some but not all of Codd's 12 rules.

    A second school of thought argues that if a database does not implement all of Codd's rules (or the current understanding on the relational model, as expressed by Christopher J. Date, Hugh Darwen and others), it is not relational. This view, shared by many theorists and other strict adherents to Codd's principles, would disqualify most DBMSs as not relational. For clarification, they often refer to some RDBMSs as truly-relational database management systems (TRDBMS), naming others pseudo-relational database management systems (PRDBMS).

    As of 2009, most commercial relational DBMSs employ SQL as their Christopher J. Date, Hugh Darwen and others), it is not relational. This view, shared by many theorists and other strict adherents to Codd's principles, would disqualify most DBMSs as not relational. For clarification, they often refer to some RDBMSs as truly-relational database management systems (TRDBMS), naming others pseudo-relational database management systems (PRDBMS).

    As of 2009, most commercial relational DBMSs employ SQL as their query language.[10]

    Alternative query languages have been proposed and implemented, notably the pre-1996 implementation of Ingres QUEL.

    This 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.[11] Columns are also called attributes. Generally, each table/relation represents one "entity type" (such as customer or product). The rows represent instances of that type of entity (such as "Lee" or "chair") and the columns representing values attributed to that instance (such as address or price).

    For example, each row of a class table corresponds to a class, and a class corresponds to multiple students, so the relationship between the class table and the student table is "one to many"[12]

    Keys

    In order for a database management system (DBMS) to operate efficiently and accurately, it must use ACID transactions.[13][14][15]

    Stored procedures

    Edgar Codd, of IBM's San Jose Research Laboratory.[1] Codd's view of what qualifies as an RDBMS is summarized in Codd's 12 rules. A relational database has become the predominant type of database. Other models besides the relational model include the hierarchical database model and the network model.

    The table below summarizes some of the most important relational database terms and the corresponding SQL term:

    SQL term Relational database term Description
    Row Tuple or record A data set representing a single item
    Column Attribute or field A labeled element of a tuple, e.g. "Address" or "Date of birth"
    Table Relation or Base relvar A set of tuples sharing the same attributes; a set of colum

    The table below summarizes some of the most important relational database terms and the corresponding SQL term:

    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.

    The relational model specifies that the tuples of a relation have no specific order and that the tuples, in turn, impose no order on the attributes. Applications access data by specifying queries, which use operations such as select to identify tuples, project to identify attributes, and join to combine relations. Relations can be modified using the insert, delete, and update operators. New tuples can supply explicit values or be derived from a query. Similarly, queries identify tuples for updating or deleting.

    Tuples by definition are unique. If the tuple contains a candidate or primary key then obviously it is unique; however, a primary key need not be defined for a row or record to be a tuple. The definition of a tuple requires that it be unique, but does not require a primary key to be defined. Because a tuple is unique, its attributes by definition constitute a superkey.

    Base and derived relations

    In a relational database, all data are stored and accessed via relations. Relations that store data are called "base relations", and in implementations are called "tables". Other relations do not store data, but are computed by applying relational operations to other relat

    The relational model specifies that the tuples of a relation have no specific order and that the tuples, in turn, impose no order on the attributes. Applications access data by specifying queries, which use operations such as select to identify tuples, project to identify attributes, and join to combine relations. Relations can be modified using the insert, delete, and update operators. New tuples can supply explicit values or be derived from a query. Similarly, queries identify tuples for updating or deleting.

    Tuples by definition are unique. If the tuple contains a candidate or primary key then obviously it is unique; however, a primary key need not be defined for a row or record to be a tuple. The definition of a tuple requires that it be unique, but does not require a primary key to be defined. Because a tuple is unique, its attributes by definition constitute a superkey.

    In a relational database, all data are stored and accessed via relations. Relations that store data are called "base relations", and in implementations are called "tables". Other relations do not store data, but are computed by applying relational operations to other relations. These relations are sometimes called "derived relations". In implementations these are called "views" or "queries". Derived relations are convenient in that they act as a single relation, even though they may grab information from several relations. Also, derived relations can be used as an abstraction layer.

    Domain

    A domain describes the set of possible values for a given attribute, and can be considered a constraint on the value of the attribute. Mathema

    A domain describes the set of possible values for a given attribute, and can be considered a constraint on the value of the attribute. Mathematically, attaching a domain to an attribute means that any value for the attribute must be an element of the specified set. The character string "ABC", for instance, is not in the integer domain, but the integer value 123 is. Another example of domain describes the possible values for the field "CoinFace" as ("Heads","Tails"). So, the field "CoinFace" will not accept input values like (0,1) or (H,T).

    Constraints

    Constraints make it possible to further restrict the domain of an attribute. For instance, a constraint can restrict a given

    Constraints make it possible to further restrict the domain of an attribute. For instance, a constraint can restrict a given integer attribute to values between 1 and 10. Constraints provide one method of implementing business rules in the database and support subsequent data use within the application layer. SQL implements constraint functionality in the form of check constraints. Constraints restrict the data that can be stored in relations. These are usually defined using expressions that result in a boolean value, indicating whether or not the data satisfies the constraint. Constraints can apply to single attributes, to a tuple (restricting combinations of attributes) or to an entire relation. Since every attribute has an associated domain, there are constraints (domain constraints). The two principal rules for the relational model are known as entity integrity and referential integrity.

    Referential integrity is based on the simple concept of relational vector based analytic algorithms, commonly employed in cloud platforms. This enables multiple interface processing within the referential database, with the additional feature of adding an additional security layer over the dynamically defined virtua

    Referential integrity is based on the simple concept of relational vector based analytic algorithms, commonly employed in cloud platforms. This enables multiple interface processing within the referential database, with the additional feature of adding an additional security layer over the dynamically defined virtual environment.[16]

    Each relation/table has a primary key, this being a consequence of a relation being a set.[17] A primary key uniquely specifies a tuple within a table. While natural attributes (attributes used to describe the data being entered) are sometimes good primary keys, surrogate keys are often used instead. A surrogate key is an artificial attribute assigned to an object which uniquely identifies it (for instance, in a table of information about students at a school they might all be assigned a student ID in order to differentiate them). The surrogate key has no intrinsic (inherent) meaning, but rather is useful through its ability to uniquely identify a tuple. Another common occurrence, especially in regard to N:M cardinality is the composite key. A composite key is a key made up of two or more attributes within a table that (together) uniquely identify a record.[citation needed]

    Foreign key

    A foreign key is a field in a relational table that matches the

    A foreign key is a field in a relational table that matches the primary key column of another table. It relates the two keys. Foreign keys need not have unique values in the referencing relation. A foreign key can be used to cross-reference tables, and it effectively uses the values of attributes in the referenced relation to restrict the domain of one or more attributes in the referencing relation. The concept is described formally as: "For all tuples in the referencing relation projected over the referencing attributes, there must exist a tuple in the referenced relation projected over those same attributes such that the values in each of the referencing attributes match the corresponding values in the referenced attributes."

    Stored procedures