control condition


SQL (Structured Query Language) (officially, although the unofficial pronunciation "sequel", /ˈsiːkwəl/, is often used) (see below), is a database computer language designed for the retrieval and management of data in relational database management systems (RDBMS), database schema creation and modification, and database object access control management.

SQL is a standard interactive and programming language for querying and modifying data and managing databases. Although SQL is both an ANSI and an ISO standard, many database products support SQL with proprietary extensions to the standard language. The core of SQL is formed by a command language that allows the retrieval, insertion, updating, and deletion of data, and performing management and administrative functions. SQL also includes a Call Level Interface (SQL/CLI) for accessing and managing data and databases remotely.

The first version of SQL was developed at IBM by Donald D. Chamberlin and Raymond F. Boyce in the early 1970s. This version, initially called SEQUEL, was designed to manipulate and retrieve data stored in IBM's original relational database product, System R. The SQL language was later formally standardized by the American National Standards Institute (ANSI) in 1986. Subsequent versions of the SQL standard have been released as International Organization for Standardization (ISO) standards.

Originally designed as a declarative query and data manipulation language, variations of SQL have been created by SQL database management system (DBMS) vendors that add procedural constructs, control-of-flow statements, user-defined data types, and various other language extensions. With the release of the SQL:1999 standard, many such extensions were formally adopted as part of the SQL language via the SQL Persistent Stored Modules (SQL/PSM) portion of the standard.

Common criticisms of SQL include a perceived lack of cross-platform portability between vendors, inappropriate handling of missing data (see Null (SQL)), and unnecessarily complex and occasionally ambiguous language grammar and semantics.


During the 1970s, a group at IBM San Jose Research Laboratory developed the System R relational database management system, based on the model introduced by Edgar F. Codd in his influential paper, A Relational Model of Data for Large Shared Data Banks. Donald D. Chamberlin and Raymond F. Boyce of IBM subsequently created the Structured English Query Language (SEQUEL) to manipulate and manage data stored in System R. The acronym SEQUEL was later changed to SQL because "SEQUEL" was a trademark of the UK-based Hawker Siddeley aircraft company.

The first non-commercial non-SQL RDBMS, Ingres, was developed in 1974 at the U.C. Berkeley. Ingres implemented a query language known as QUEL, which was later supplanted in the marketplace by SQL.

In the late 1970s, Relational Software, Inc. (now Oracle Corporation) saw the potential of the concepts described by Codd, Chamberlin, and Boyce and developed their own SQL-based RDBMS with aspirations of selling it to the U.S. Navy, CIA, and other government agencies. In the summer of 1979, Relational Software, Inc. introduced the first commercially available implementation of SQL, Oracle V2 (Version2) for VAX computers. Oracle V2 beat IBM's release of the System/38 RDBMS to market by a few weeks.

After testing SQL at customer test sites to determine the usefulness and practicality of the system, IBM began developing commercial products based on their System R prototype including System/38, SQL/DS, and DB2, which were commercially available in 1979, 1981, and 1983, respectively.


SQL was adopted as a standard by ANSI in 1986 and ISO in 1987. In the original SQL standard, ANSI declared that the official pronunciation for SQL is "es queue el". However, many English-speaking database professionals still use the nonstandard pronunciation /ˈsiːkwəl/ (like the word "sequel"). SEQUEL was an earlier IBM database language, a predecessor to the SQL language.

Until 1996, the National Institute of Standards and Technology (NIST) data management standards program was tasked with certifying SQL DBMS compliance with the SQL standard. In 1996, however, the NIST data management standards program was dissolved, and vendors are now relied upon to self-certify their products for compliance.

The SQL standard has gone through a number of revisions, as shown below:

Year Name Alias Comments
1986 SQL-86 SQL-87 First published by ANSI. Ratified by ISO in 1987.
1989 SQL-89 FIPS 127-1 Minor revision, adopted as FIPS 127-1.
1992 SQL-92 SQL2, FIPS 127-2 Major revision (ISO 9075), Entry Level SQL-92 adopted as FIPS 127-2.
1999 SQL3 Added regular expression matching, recursive queries, triggers, support for procedural and control-of-flow statements, non-scalar types, and some object-oriented features.
2003   Introduced XML-related features, window functions, standardized sequences, and columns with auto-generated values (including identity-columns).
2006   ISO/IEC 9075-14:2006 defines ways in which SQL can be used in conjunction with XML. It defines ways of importing and storing XML data in an SQL database, manipulating it within the database and publishing both XML and conventional SQL-data in XML form. In addition, it provides facilities that permit applications to integrate into their SQL code the use of XQuery, the XML Query Language published by the World Wide Web Consortium (W3C), to concurrently access ordinary SQL-data and XML documents.
2008   Defines more flexible windowing functions, clarifies SQL 2003 items that were still unclear

The SQL standard is not freely available. SQL:2003 and SQL:2006 may be purchased from ISO or ANSI. A late draft of SQL:2003 is freely available as a zip archive, however, from Whitemarsh Information Systems Corporation The zip archive contains a number of PDF files that define the parts of the SQL:2003 specification.

Scope and extensions

Procedural extensions

SQL is designed for a specific purpose: to query data contained in a relational database. SQL is a set-based, declarative query language, not an imperative language such as C or BASIC. However, there are extensions to Standard SQL which add procedural programming language functionality, such as control-of-flow constructs. These are:

Source Common
Full Name
ANSI/ISO Standard SQL/PSM SQL/Persistent Stored Modules
PSQL Procedural SQL
IBM SQL PL SQL Procedural Language (implements SQL/PSM)
T-SQL Transact-SQL
MySQL SQL/PSM SQL/Persistent Stored Module (as in ISO SQL:2003)
Oracle PL/SQL Procedural Language/SQL (based on Ada)
PostgreSQL PL/pgSQL Procedural Language/PostgreSQL Structured Query Language (based on Oracle PL/SQL)
PostgreSQL PL/PSM Procedural Language/Persistent Stored Modules (implements SQL/PSM)

In addition to the standard SQL/PSM extensions and proprietary SQL extensions, procedural and object-oriented programmability is available on many SQL platforms via DBMS integration with other languages. The SQL standard defines SQL/JRT extensions (SQL Routines and Types for the Java Programming Language) to support Java code in SQL databases. SQL Server 2005 uses the SQLCLR (SQL Server Common Language Runtime) to host managed .NET assemblies in the database, while prior versions of SQL Server were restricted to using unmanaged extended stored procedures which were primarily written in C. Other database platforms, like MySQL and Postgres, allow functions to be written in a wide variety of languages including Perl, Python, Tcl, and C.

Additional extensions

SQL:2003 also defines several additional extensions to the standard to increase SQL functionality overall. These extensions include:

The SQL/CLI, or Call-Level Interface, extension is defined in ISO/IEC 9075-3:2003. This extension defines common interfacing components (structures and procedures) that can be used to execute SQL statements from applications written in other programming languages. The SQL/CLI extension is defined in such a way that SQL statements and SQL/CLI procedure calls are treated as separate from the calling application's source code.

The SQL/MED, or Management of External Data, extension is defined by ISO/IEC 9075-9:2003. SQL/MED provides extensions to SQL that define foreign-data wrappers and datalink types to allow SQL to manage external data. External data is data that is accessible to, but not managed by, an SQL-based DBMS.

The SQL/OLB, or Object Language Bindings, extension is defined by ISO/IEC 9075-10:2003. SQL/OLB defines the syntax and symantics of SQLJ, which is SQL embedded in Java. The standard also describes mechanisms to ensure binary portability of SQLJ applications, and specifies various Java packages and their contained classes.

The SQL/Schemata, or Information and Definition Schemas, extension is defined by ISO/IEC 9075-11:2003. SQL/Schemata defines the Information Schema and Definition Schema, providing a common set of tools to make SQL databases and objects self-describing. These tools include the SQL object identifier, structure and integrity constraints, security and authorization specifications, features and packages of ISO/IEC 9075, support of features provided by SQL-based DBMS implementations, SQL-based DBMS implementation information and sizing items, and the values supported by the DBMS implementations.

The SQL/JRT, or SQL Routines and Types for the Java Programming Language, extension is defined by ISO/IEC 9075-13:2003. SQL/JRT specifies the ability to invoke static Java methods as routines from within SQL applications. It also calls for the ability to use Java classes as SQL structured user-defined types.

The SQL/XML, or XML-Related Specifications, extension is defined by ISO/IEC 9075-14:2003. SQL/XML specifies SQL-based extensions for using XML in conjunction with SQL. The XML data type is introduced, as well as several routines, functions, and XML-to-SQL data type mappings to support manipulation and storage of XML in an SQL database.

The SQL/PSM, or Persistent Stored Modules, extension is defined by ISO/IEC 9075-4:2003. SQL/PSM standardizes procedural extensions for SQL, including flow of control, condition handling, statement condition signals and resignals, cursors and local variables, and assignment of expressions to variables and parameters. In addition, SQL/PSM formalizes declaration and maintenance of persistent database language routines (e.g., "stored procedures").

Language elements

The SQL language is sub-divided into several language elements, including:

  • Statements which may have a persistent effect on schemas and data, or which may control transactions, program flow, connections, sessions, or diagnostics.
  • Queries which retrieve data based on specific criteria.
  • Expressions which can produce either scalar values or tables consisting of columns and rows of data.
  • Predicates which specify conditions that can be evaluated to SQL three-valued logic (3VL) Boolean truth values and which are used to limit the effects of statements and queries, or to change program flow.
  • Clauses, which are in some cases optional, constituent components of statements and queries.
  • Whitespace is generally ignored in SQL statements and queries, making it easier to format SQL code for readability.
  • SQL statements also include the semicolon (";") statement terminator. Though not required on every platform, it is defined as a standard part of the SQL grammar.


The most common operation in SQL databases is the query, which is performed with the declarative SELECT keyword. SELECT retrieves data from a specified table, or multiple related tables, in a database. While often grouped with Data Manipulation Language (DML) statements, the standard SELECT query is considered separate from SQL DML, as it has no persistent effects on the data stored in a database. Note that there are some platform-specific variations of SELECT that can persist their effects in a database, such as the SELECT INTO syntax that exists in some databases.

SQL queries allow the user to specify a description of the desired result set, but it is left to the devices of the database management system (DBMS) to plan, optimize, and perform the physical operations necessary to produce that result set in as efficient a manner as possible. An SQL query includes a list of columns to be included in the final result immediately following the SELECT keyword. An asterisk ("*") can also be used as a "wildcard" indicator to specify that all available columns of a table (or multiple tables) are to be returned. SELECT is the most complex statement in SQL, with several optional keywords and clauses, including:

  • The FROM clause which indicates the source table or tables from which the data is to be retrieved. The FROM clause can include optional JOIN clauses to join related tables to one another based on user-specified criteria.
  • The WHERE clause includes a comparison predicate, which is used to restrict the number of rows returned by the query. The WHERE clause is applied before the GROUP BY clause. The WHERE clause eliminates all rows from the result set where the comparison predicate does not evaluate to True.
  • The GROUP BY clause is used to combine, or group, rows with related values into elements of a smaller set of rows. GROUP BY is often used in conjunction with SQL aggregate functions or to eliminate duplicate rows from a result set.
  • The HAVING clause includes a comparison predicate used to eliminate rows after the GROUP BY clause is applied to the result set. Because it acts on the results of the GROUP BY clause, aggregate functions can be used in the HAVING clause predicate.
  • The ORDER BY clause is used to identify which columns are used to sort the resulting data, and in which order they should be sorted (options are ascending or descending). The order of rows returned by an SQL query is never guaranteed unless an ORDER BY clause is specified.

The following is an example of a SELECT query that returns a list of expensive books. The query retrieves all rows from the Book table in which the price column contains a value greater than 100.00. The result is sorted in ascending order by title. The asterisk (*) in the select list indicates that all columns of the Book table should be included in the result set. SELECT * FROM Book WHERE price > 100.00 ORDER BY title;

The example below demonstrates the use of multiple tables in a join, grouping, and aggregation in an SQL query, by returning a list of books and the number of authors associated with each book. SELECT Book.title, count(*) AS Authors FROM Book JOIN Book_author ON Book.isbn = Book_author.isbn GROUP BY Book.title; Example output might resemble the following:

Title                   Authors
----------------------  -------
SQL Examples and Guide     3
The Joy of SQL             1
How to use Wikipedia       2
Pitfalls of SQL            1
Under the precondition that isbn is the only common column name of the two tables and that a column named title only exists in the Books table, the above query could be rewritten in the following form:

SELECT title, count(*) AS Authors FROM Book NATURAL JOIN Book_author GROUP BY title;

However, many vendors either do not support this approach, or it requires certain column naming conventions. Thus, it is less common in practice.

Data retrieval is very often combined with data projection when the user is looking for calculated values and not just the verbatim data stored in primitive data types, or when the data needs to be expressed in a form that is different from how it's stored. SQL allows the use of expressions in the select list to project data, as in the following example which returns a list of books that cost more than 100.00 with an additional sales_tax column containing a sales tax figure calculated at 6% of the price.

SELECT isbn, title, price, price * 0.06 AS sales_tax FROM Book WHERE price > 100.00 ORDER BY title;

Some modern day SQL queries may include extra WHERE statements that are conditional to each other. They may look like this example:

SELECT isbn, title, price, date FROM Book WHERE price > 100.00 AND (date = '16042004' or date = '16042005') ORDER BY title;

Universal quantification is not explicitly supported by sql, and must be worked out as a negated existential quantification.

Data manipulation

First, there are the standard Data Manipulation Language (DML) elements. DML is the subset of the language used to add, update and delete data:

  • INSERT is used to add rows (formally tuples) to an existing table, for example:

INSERT INTO My_table (field1, field2, field3) VALUES ('test', 'N', NULL);

  • UPDATE is used to modify the values of a set of existing table rows, eg:

UPDATE My_table SET field1 = 'updated value' WHERE field2 = 'N';

  • DELETE removes zero or more existing rows from a table, eg:

DELETE FROM My_table WHERE field2 = 'N';

  • MERGE is used to combine the data of multiple tables. It is something of a combination of the INSERT and UPDATE elements. It is defined in the SQL:2003 standard; prior to that, some databases provided similar functionality via different syntax, sometimes called an "upsert".

Transaction controls

Transactions, if available, can be used to wrap around the DML operations:

  • START TRANSACTION (or BEGIN WORK, or BEGIN TRANSACTION, depending on SQL dialect) can be used to mark the start of a database transaction, which either completes entirely or not at all.
  • COMMIT causes all data changes in a transaction to be made permanent.
  • ROLLBACK causes all data changes since the last COMMIT or ROLLBACK to be discarded, so that the state of the data is "rolled back" to the way it was prior to those changes being requested.

Once the COMMIT statement has been executed, the changes cannot be rolled back. In other words, its meaningless to have ROLLBACK executed after COMMIT statement and vice versa.

COMMIT and ROLLBACK interact with areas such as transaction control and locking. Strictly, both terminate any open transaction and release any locks held on data. In the absence of a START TRANSACTION or similar statement, the semantics of SQL are implementation-dependent. Example: A classic bank transfer of funds transaction.


 UPDATE Account SET amount=amount-200 WHERE account_number=1234;
 UPDATE Account SET amount=amount+200 WHERE account_number=2345;

Data definition

The second group of keywords is the Data Definition Language (DDL). DDL allows the user to define new tables and associated elements. Most commercial SQL databases have proprietary extensions in their DDL, which allow control over nonstandard features of the database system. The most basic items of DDL are the CREATE, ALTER, RENAME, TRUNCATE and DROP statements:

  • CREATE causes an object (a table, for example) to be created within the database.
  • DROP causes an existing object within the database to be deleted, usually irretrievably.
  • TRUNCATE deletes all data from a table (non-standard, but common SQL statement).
  • ALTER statement permits the user to modify an existing object in various ways -- for example, adding a column to an existing table.

Example: CREATE TABLE My_table (

 my_field1   INT,
 my_field2   VARCHAR (50),
 my_field3   DATE         NOT NULL,
 PRIMARY KEY (my_field1, my_field2)

Data control

The third group of SQL keywords is the Data Control Language (DCL). DCL handles the authorization aspects of data and permits the user to control who has access to see or manipulate data within the database. Its two main keywords are:

  • GRANT authorizes one or more users to perform an operation or a set of operations on an object.
  • REVOKE removes or restricts the capability of a user to perform an operation or a set of operations.

Example: GRANT SELECT, UPDATE ON My_table TO some_user, another_user;


  • ANSI-standard SQL supports double dash, --, as a single line comment identifier (some extensions also support curly brackets or C style /* comments */ for multi-line comments).

Example: SELECT * FROM Inventory -- Retrieve everything from inventory table

Criticisms of SQL

Technically, SQL is a declarative computer language for use with "SQL databases". Theorists and some practitioners note that many of the original SQL features were inspired by, but violated, the relational model for database management and its tuple calculus realization. Recent extensions to SQL achieved relational completeness, but have worsened the violations, as documented in The Third Manifesto.

In addition, there are also some criticisms about the practical use of SQL:

  • Implementations are inconsistent and, usually, incompatible between vendors. In particular date and time syntax, string concatenation, nulls, and comparison case sensitivity often vary from vendor to vendor.
  • The language makes it too easy to do a Cartesian join (joining all possible combinations), which results in "run-away" result sets when WHERE clauses are mistyped. Cartesian joins are so rarely used in practice that requiring an explicit CARTESIAN keyword may be warranted.
    SQL 1992 introduced the CROSS JOIN keyword that allows the user to make clear that a cartesian join is intended, but the shorthand "comma-join" with no predicate is still acceptable syntax.
  • It is also possible to misconstruct a WHERE on an update or delete, thereby affecting more rows in a table than desired.
  • The grammar of SQL is perhaps unnecessarily complex, borrowing a COBOL-like keyword approach, when a function-influenced syntax could result in more re-use of fewer grammar and syntax rules. This is perhaps due to IBM's early goal of making the language more English-like so that it is more approachable to those without a mathematical or programming background. (Predecessors to SQL were more mathematical.)

Reasons for lack of portability

Popular implementations of SQL commonly omit support for basic features of Standard SQL, such as the DATE or TIME data types, preferring variations of their own. As a result, SQL code can rarely be ported between database systems without modifications.

There are several reasons for this lack of portability between database systems:

  • The complexity and size of the SQL standard means that most databases do not implement the entire standard.
  • The standard does not specify database behavior in several important areas (e.g. indexes, file storage...), leaving it up to implementations of the database to decide how to behave.
  • The SQL standard precisely specifies the syntax that a conforming database system must implement. However, the standard's specification of the semantics of language constructs is less well-defined, leading to areas of ambiguity.
  • Many database vendors have large existing customer bases; where the SQL standard conflicts with the prior behavior of the vendor's database, the vendor may be unwilling to break backward compatibility.

Alternatives to SQL

A distinction should be made between alternatives to relational query languages and alternatives to SQL. The list below are proposed alternatives to SQL, but are still (nominally) relational. See navigational database for alternatives to entity:

See also


External links

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