A relational database (RDB) is a database based on the relational model of data, as proposed by E. F. Codd in 1970.
A Relational Database Management System (RDBMS) is a type of database management system that stores data in a structured format using rows and columns.
Many relational database systems are equipped with the option of using SQL (Structured Query Language) for querying and updating the database.
History 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". In this paper and later papers, he defined what he meant by relation. 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, so the term has gradually come to describe a broader class of database systems, which at a minimum:
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); 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. The first system sold as an RDBMS was Multics Relational Data Store (June 1976). Oracle was released in 1979 by Relational Software, now Oracle Corporation. Ingres and IBM BS12 followed. Other examples of an RDBMS include IBM Db2, SAP Sybase ASE, and Informix. In 1984, the first RDBMS for Macintosh began being developed, code-named Silver Surfer, and was released in 1987 as 4th Dimension and known today as 4D.
The first systems that were relatively faithful implementations of the relational model were from:
University of Michigan – Micro DBMS (1969) Massachusetts Institute of Technology (1971) 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 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.
Alternative query languages have been proposed and implemented, notably the pre-1996 implementation of Ingres QUEL.
Relational model
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. 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 represent 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"
Keys Each row in a table has its own unique key. Rows in a table can be linked to rows in other tables by adding a column for the unique key of the linked row (such columns are known as foreign keys). Codd showed that data relationships of arbitrary complexity can be represented by a simple set of concepts.
Part of this processing involves consistently being able to select or modify one and only one row in a table. Therefore, most physical implementations have a unique primary key (PK) for each row in a table. When a new row is written to the table, a new unique value for the primary key is generated; this is the key that the system uses primarily for accessing the table. System performance is optimized for PKs. Other, more natural keys may also be identified and defined as alternate keys (AK). Often several columns are needed to form an AK (this is one reason why a single integer column is usually made the PK). Both PKs and AKs have the ability to uniquely identify a row within a table. Additional technology may be applied to ensure a unique ID across the world, a globally unique identifier, when there are broader system requirements.
The primary keys within a database are used to define the relationships among the tables. When a PK migrates to another table, it becomes a foreign key (FK) in the other table. When each cell can contain only one value and the PK migrates into a regular entity table, this design pattern can represent either a one-to-one or one-to-many relationship. Most relational database designs resolve many-to-many relationships by creating an additional table that contains the PKs from both of the other entity tables the relationship becomes an entity; the resolution table is then named appropriately and the two FKs are combined to form a PK. The migration of PKs to other tables is the second major reason why system-assigned integers are used normally as PKs; there is usually neither efficiency nor clarity in migrating a bunch of other types of columns.
Relationships Relationships are a logical connection between different tables (entities), established on the basis of interaction among these tables. These relationships can be modelled as an entity-relationship model.
Transactions In order for a database management system (DBMS) to operate efficiently and accurately, it must use ACID transactions.Gray, Jim, and Reuter, Andreas, Distributed Transaction Processing: Concepts and Techniques. Morgan Kaufmann, 1993. .
Stored procedures Part of the programming within an RDBMS is accomplished using stored procedures (SPs). Often procedures can be used to greatly reduce the amount of information transferred within and outside of a system. For increased security, the system design may grant access to only the stored procedures and not directly to the tables. Fundamental stored procedures contain the logic needed to insert new and update existing data. More complex procedures may be written to implement additional rules and logic related to processing or selecting the data.
Terminology
The relational database was first defined in June 1970 by Edgar Codd, of IBM's San Jose Research Laboratory. 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 columns and rows View or result set Derived relvar Any set of tuples; a data report from the RDBMS in response to a query
Relations or tables
In a relational database, a relation is 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
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. 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 are often used to 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.
Primary key
Every relation/table has a primary key, this being a consequence of a relation being a set. 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.
Foreign key