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

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The term "relational database" was first defined 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 tướng all of Codd's rules,[4] ví the term has gradually come to tướng describe a broader class of database systems, which at a minimum:

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

In 1974, IBM began developing System R, a research project to tướng 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 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 4 chiều.[8]

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

  • University of Michigan – Micro DBMS (1969)[9]
  • Massachusetts Institute of Technology (1971)[10]
  • 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 tướng Codd's principles, would disqualify most DBMSs as not relational. For clarification, they often refer to tướng 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.[11]

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

Relational model[edit]

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.[12] 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 tướng that instance (such as address or price).

For example, each row of a class table corresponds to tướng a class, and a class corresponds to tướng multiple students, ví the relationship between the class table and the student table is "one to tướng many"[13]


Each row in a table has its own unique key. Rows in a table can be linked to tướng 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 phối of concepts.[1]

Part of this processing involves consistently being able to tướng 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 tướng 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 tướng size an AK (this is one reason why a single integer column is usually made the PK). Both PKs and AKs have the ability to tướng uniquely identify a row within a table. Additional technology may be applied to tướng 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 tướng define the relationships among the tables. When a PK migrates to tướng another table, it becomes a foreign key 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 tướng size a PK. The migration of PKs to tướng 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 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.


In order for a database management system (DBMS) to tướng operate efficiently and accurately, it must use ACID transactions.[14][15][16]

Stored procedures[edit]

Part of the programming within a RDBMS is accomplished using stored procedures (SPs). Often procedures can be used to tướng greatly reduce the amount of information transferred within and outside of a system. For increased security, the system design may grant access to tướng only the stored procedures and not directly to tướng the tables. Fundamental stored procedures contain the logic needed to tướng insert new and update existing data. More complex procedures may be written to tướng implement additional rules and logic related to tướng processing or selecting the data.


Relational database terminology

The relational database was first defined in June 1970 by 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 phối 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 phối of tuples sharing the same attributes; a phối of columns and rows
View or result set Derived relvar Any phối of tuples; a data report from the RDBMS in response to tướng a query

Relations or tables[edit]

In a relational database, a relation is a phối 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 name and conform to tướng 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 tướng identify tuples, project to tướng identify attributes, and join to tướng 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 tướng be a tuple. The definition of a tuple requires that it be unique, but does not require a primary key to tướng be defined. Because a tuple is unique, its attributes by definition constitute a superkey.

Base and derived relations[edit]

All data are stored and accessed via relations. Relations that store data are called "base relations", and in implementations are called "tables". Other relations bởi not store data, but are computed by applying relational operations to tướng 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.

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


Constraints are often used to tướng make it possible to tướng further restrict the domain name of an attribute. For instance, a constraint can restrict a given integer attribute to tướng values between 1 and 10. Constraints provide one method of implementing business rules in the database and tư vấn subsequent data use within the application layer. SQL implements constraint functionality in the size of kiểm tra 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 tướng single attributes, to tướng a tuple (restricting combinations of attributes) or to tướng an entire relation. Since every attribute has an associated domain name, there are constraints (domain constraints). The two principal rules for the relational model are known as entity integrity and referential integrity.

Primary key[edit]

Every relation/table has a primary key, this being a consequence of a relation being a phối.[17] A primary key uniquely specifies a tuple within a table. While natural attributes (attributes used to tướng 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 tướng 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 tướng differentiate them). The surrogate key has no intrinsic (inherent) meaning, but rather is useful through its ability to tướng uniquely identify a tuple. Another common occurrence, especially in regard to tướng 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[edit]

Foreign key refers to tướng 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 tướng cross-reference tables, and it effectively uses the values of attributes in the referenced relation to tướng restrict the domain name 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[edit]

A stored procedure is executable code that is associated with, and generally stored in, the database. Stored procedures usually collect and customize common operations, lượt thích inserting a tuple into a relation, gathering statistical information about usage patterns, or encapsulating complex business logic and calculations. Frequently they are used as an application programming interface (API) for security or simplicity. Implementations of stored procedures on SQL RDBMS's often allow developers to tướng take advantage of procedural extensions (often vendor-specific) to tướng the standard declarative SQL syntax. Stored procedures are not part of the relational database model, but all commercial implementations include them.


An index is one way of providing quicker access to tướng data. Indices can be created on any combination of attributes on a relation. Queries that filter using those attributes can find matching tuples directly using the index (similar to tướng Hash table lookup), without having to tướng kiểm tra each tuple in turn. This is analogous to tướng using the index of a book to tướng go directly to tướng the page on which the information you are looking for is found, ví that you bởi not have to tướng read the entire book to tướng find what you are looking for. Relational databases typically supply multiple indexing techniques, each of which is optimal for some combination of data distribution, relation size, and typical access pattern. Indices are usually implemented via B+ trees, R-trees, and bitmaps. Indices are usually not considered part of the database, as they are considered an implementation detail, though indices are usually maintained by the same group that maintains the other parts of the database. The use of efficient indexes on both primary and foreign keys can dramatically improve query performance. This is because B-tree indexes result in query times proportional to tướng log(n) where n is the number of rows in a table and hash indexes result in constant time queries (no size dependency as long as the relevant part of the index fits into memory).

Relational operations[edit]

Queries made against the relational database, and the derived relvars in the database are expressed in a relational calculus or a relational algebra. In his original relational algebra, Codd introduced eight relational operators in two groups of four operators each. The first four operators were based on the traditional mathematical phối operations:

  • The union operator (υ) combines the tuples of two relations and removes all duplicate tuples from the result. The relational union operator is equivalent to tướng the SQL UNION operator.
  • The intersection operator (∩) produces the phối of tuples that two relations share in common. Intersection is implemented in SQL in the size of the INTERSECT operator.
  • The phối difference operator (-) acts on two relations and produces the phối of tuples from the first relation that bởi not exist in the second relation. Difference is implemented in SQL in the size of the EXCEPT or MINUS operator.
  • The cartesian product (X) of two relations is a join that is not restricted by any criteria, resulting in every tuple of the first relation being matched with every tuple of the second relation. The cartesian product is implemented in SQL as the Cross join operator.

The remaining operators proposed by Codd involve special operations specific to tướng relational databases:

  • The selection, or restriction, operation (σ) retrieves tuples from a relation, limiting the results to tướng only those that meet a specific criterion, i.e. a subset in terms of phối theory. The SQL equivalent of selection is the SELECT query statement with a WHERE clause.
  • The projection operation (π) extracts only the specified attributes from a tuple or phối of tuples.
  • The join operation defined for relational databases is often referred to tướng as a natural join (⋈). In this type of join, two relations are connected by their common attributes. MySQL's approximation of a natural join is the Inner join operator. In SQL, an INNER JOIN prevents a cartesian product from occurring when there are two tables in a query. For each table added to tướng a SQL Query, one additional INNER JOIN is added to tướng prevent a cartesian product. Thus, for N tables in an SQL query, there must be N−1 INNER JOINS to tướng prevent a cartesian product.
  • The relational division (÷) operation is a slightly more complex operation and essentially involves using the tuples of one relation (the dividend) to tướng partition a second relation (the divisor). The relational division operator is effectively the opposite of the cartesian product operator (hence the name).

Other operators have been introduced or proposed since Codd's introduction of the original eight including relational comparison operators and extensions that offer tư vấn for nesting and hierarchical data, among others.


Normalization was first proposed by Codd as an integral part of the relational model. It encompasses a phối of procedures designed to tướng eliminate non-simple domains (non-atomic values) and the redundancy (duplication) of data, which in turn prevents data manipulation anomalies and loss of data integrity. The most common forms of normalization applied to tướng databases are called the normal forms.


The general structure of a relational database

Connolly and Begg define database management system (DBMS) as a "software system that enables users to tướng define, create, maintain and control access to tướng the database".[18] RDBMS is an extension of that acronym that is sometimes used when the underlying database is relational.

An alternative definition for a relational database management system is a database management system (DBMS) based on the relational model. Most databases in widespread use today are based on this model.[19]

RDBMSs have been a common option for the storage of information in databases used for financial records, manufacturing and logistical information, personnel data, and other applications since the 1980s. Relational databases have often replaced legacy hierarchical databases and network databases, because RDBMS were easier to tướng implement and administer. Nonetheless, relational stored data received continued, unsuccessful challenges by object database management systems in the 1980s and 1990s, (which were introduced in an attempt to tướng address the so-called object–relational impedance mismatch between relational databases and object-oriented application programs), as well as by XML database management systems in the 1990s.[citation needed] However, due to tướng the expanse of technologies, such as horizontal scaling of computer clusters, NoSQL databases have recently become popular as an alternative to tướng RDBMS databases.[20]

Distributed relational databases[edit]

Distributed Relational Database Architecture (DRDA) was designed by a workgroup within IBM in the period 1988 to tướng 1994. DRDA enables network connected relational databases to tướng cooperate to tướng fulfill SQL requests.[21][22] The messages, protocols, and structural components of DRDA are defined by the Distributed Data Management Architecture.


According to tướng DB-Engines, in January 2023 the most popular systems on the db-engines.com trang web site were:[23]

  1. Oracle Database
  2. MySQL
  3. Microsoft SQL Server
  4. PostgreSQL (free software)
  5. IBM Db2
  6. Microsoft Access
  7. SQLite (free software)
  8. MariaDB (free software)
  9. Snowflake
  10. Microsoft Azure SQL Database
  11. Apache Hive (free software)
  12. Teradata Vantage

According to tướng research company Gartner, in 2011, the five leading proprietary software relational database vendors by revenue were Oracle (48.8%), IBM (20.2%), Microsoft (17.0%), SAP including Sybase (4.6%), and Teradata (3.7%).[24]

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See also[edit]

  • SQL
  • Object database (OODBMS)
  • Online analytical processing (OLAP) and ROLAP (Relational Online Analytical Processing)
  • Data warehouse
  • Star schema
  • Snowflake schema
  • List of relational database management systems
  • Comparison of relational database management systems


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  13. ^ "A universal relation model for a nested database", The Nested Universal Relation Database Model, Lecture Notes in Computer Science, Berlin, Heidelberg: Springer Berlin Heidelberg, vol. 595, pp. 109–135, 1992, doi:10.1007/3-540-55493-9_5, ISBN 978-3-540-55493-6, retrieved 2020-11-01
  14. ^ "Gray to tướng be Honored With A. M. Turing Award This Spring". Microsoft PressPass. 1998-11-23. Archived from the original on 6 February 2009. Retrieved 2009-01-16.
  15. ^ Gray, Jim (September 1981). "The Transaction Concept: Virtues and Limitations" (PDF). Proceedings of the 7th International Conference on Very Large Databases. Cupertino, CA: Tandem Computers. pp. 144–154. Retrieved 2006-11-09.
  16. ^ Gray, Jim, and Reuter, Andreas, Distributed Transaction Processing: Concepts and Techniques. Morgan Kaufmann, 1993. ISBN 1-55860-190-2.
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  18. ^ Connolly, Thomas M.; Begg, Carolyn E. (2014). Database Systems – A Practical Approach to tướng Design Implementation and Management (6th ed.). Pearson. p. 64. ISBN 978-1292061184.
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  20. ^ "NoSQL databases eat into the relational database market". 4 March 2015. Retrieved 2018-03-14.
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  22. ^ Distributed Relational Database Architecture Reference. IBM Corp. SC26-4651-0. 1990.
  23. ^ "DB-Engines Ranking of Relational DBMS". DB-Engines. Retrieved 2022-04-29.
  24. ^ "Oracle the clear leader in $24 billion RDBMS market". 2012-04-12. Retrieved 2013-03-01.


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