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Paradigm Multi-paradigm
Appeared in 1974
Designed by Donald D. Chamberlin
Raymond F. Boyce
Developer IBM
Stable release SQL:2008 (2008)
Typing discipline Static, strong
Major implementations Many
Dialects SQL-86, SQL-89, SQL-92, SQL:1999, SQL:2003, SQL:2008
Influenced by Datalog
Influenced CQL, LINQ, Windows PowerShell
OS Cross-platform

SQL (pronounced /ˌsɛ.kwɛl/ SE-kwEL[1], often referred to as Structured Query Language[2][3]) is a database computer language designed for managing data in relational database management systems (RDBMS), and originally based upon Relational Algebra. Its scope includes data query and update, schema creation and modification, and data access control. SQL was one of the first languages for Edgar F. Codd's relational model in his influential 1970 paper, "A Relational Model of Data for Large Shared Data Banks"[4] and became the most widely used language for relational databases.[5][6]



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.

During the 1970s, a group at IBM San Jose Research Laboratory developed the System R relational database management system. Donald D. Chamberlin and Raymond F. Boyce of IBM subsequently created the Structured English Query Language (SEQUEL or SEQL) to manage data stored in System R.[7] The acronym SEQUEL was later changed to SQL because "SEQUEL" was a trademark of the UK-based Hawker Siddeley aircraft company.[8]

The first Relational Database Management System (RDBMS) was RDMS, developed at MIT in the early 1970s, soon followed by Ingres, developed in 1974 at U.C. Berkeley. Ingres implemented a query language known as QUEL, which was later supplanted in the marketplace by SQL.[8]

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, Central Intelligence Agency, and other U.S. 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.[citation needed]

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.[9]

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. It also lacks the rigour of more formal languages such as Relational Algebra.

Language elements

This chart shows several of the SQL language elements that compose a single statement.

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

  • Clauses, which are in some cases optional, constituent components of statements and queries.[10]
  • 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.
  • Queries which retrieve data based on specific criteria.
  • Statements which may have a persistent effect on schemas and data, or which may control transactions, program flow, connections, sessions, or diagnostics.
    • 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.
  • Insignificant whitespace is generally ignored in SQL statements and queries, making it easier to format SQL code for readability.


The most common operation in SQL is the query, which is performed with the declarative SELECT statement. SELECT retrieves data from one or more tables, or expressions. Standard SELECT statements have no persistent effects on the database. Some non-standard implementations of SELECT can have persistent effects, such as the SELECT INTO syntax that exists in some databases.[11]

Queries allow the user to describe desired data, leaving the database management system (DBMS) responsible for planning, optimizing, and performing the physical operations necessary to produce that result as it chooses.

A query includes a list of columns to be included in the final result immediately following the SELECT keyword. An asterisk ("*") can also be used to specify that the query should return all columns of the queried tables. SELECT is the most complex statement in SQL, with optional keywords and clauses that include:

  • The FROM clause which indicates the table(s) from which data is to be retrieved. The FROM clause can include optional JOIN subclauses to specify the rules for joining tables.
  • The WHERE clause includes a comparison predicate, which restricts the rows returned by the query. The WHERE clause eliminates all rows from the result set for which the comparison predicate does not evaluate to True.
  • The GROUP BY clause is used to project rows having common values into a smaller set of rows. GROUP BY is often used in conjunction with SQL aggregation functions or to eliminate duplicate rows from a result set. The WHERE clause is applied before the GROUP BY clause.
  • The HAVING clause includes a predicate used to filter rows resulting from the GROUP BY clause. Because it acts on the results of the GROUP BY clause, aggregation functions can be used in the HAVING clause predicate.
  • The ORDER BY clause identifies which columns are used to sort the resulting data, and in which direction they should be sorted (options are ascending or descending). Without an ORDER BY clause, the order of rows returned by an SQL query is undefined.

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.

    FROM Book
    WHERE price > 100.00
    ORDER BY title;

The example below demonstrates a query of multiple tables, grouping, and aggregation, 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     4
The Joy of SQL             1
An Introduction to SQL     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 require column naming conventions.

SQL includes operators and functions for calculating values on stored values. 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,
        price * 0.06 AS sales_tax
    FROM Book
    WHERE price > 100.00
    ORDER BY title;

Null and Three-Valued Logic (3VL)

The idea of Null was introduced into SQL to handle missing information in the relational model. The introduction of Null (or Unknown) along with True and False is the foundation of Three-Valued Logic. Null does not have a value (and is not a member of any data domain) but is rather a placeholder or “mark” for missing information. Therefore comparisons with Null can never result in either True or False but always in the third logical result, Unknown.[12]

SQL uses Null to handle missing information. It supports three-valued logic (3VL) and the rules governing SQL three-valued logic (3VL) are shown below (p and q represent logical states).[13] The word NULL is also a reserved keyword in SQL, used to identify the Null special marker.

Additionally, since SQL operators return Unknown when comparing anything with Null, SQL provides two Null-specific comparison predicates: The IS NULL and IS NOT NULL test whether data is or is not Null.[14]

Note that SQL returns only results for which the WHERE clause returns a value of True. I.e., it excludes results with values of False, but also those whose value is Unknown.

p AND q p
True False Unknown
q True True False Unknown
False False False False
Unknown Unknown False Unknown
p OR q p
True False Unknown
q True True True True
False True False Unknown
Unknown True Unknown Unknown
p NOT p
True False
False True
Unknown Unknown
p = q p
True False Unknown
q True True False Unknown
False False True Unknown
Unknown Unknown Unknown Unknown

Universal quantification is not explicitly supported by SQL, and must be worked out as a negated existential quantification.[15][16][17]

There is also the "<row value expression> IS DISTINCT FROM <row value expression>" infixed comparison operator which returns TRUE if both operands are equal or both are NULL. Likewise, IS NOT DISTINCT FROM is defined as "NOT (<row value expression> IS DISTINCT FROM <row value expression>")

Data manipulation

The Data Manipulation Language (DML) is the subset of SQL used to add, update and delete data:

  • INSERT adds rows (formally tuples) to an existing table, e.g.,:
        (field1, field2, field3) 
        ('test', 'N', NULL);
  • UPDATE modifies a set of existing table rows, e.g.,:
UPDATE My_table 
    SET field1 = 'updated value' 
    WHERE field2 = 'N';
  • DELETE removes existing rows from a table, e.g.,:
    WHERE field2 = 'N';
  • TRUNCATE deletes all data from a table in a very fast way. It usually implies a subsequent COMMIT operation.
  • MERGE is used to combine the data of multiple tables. It combines 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 "upsert".

Transaction controls

Transactions, if available, wrap DML operations:

  • START TRANSACTION (or BEGIN WORK, or BEGIN TRANSACTION, depending on SQL dialect) mark the start of a database transaction, which either completes entirely or not at all.
  • SAVE TRANSACTION (or SAVEPOINT ) save the state of the database at the current point in transaction
CREATE TABLE tbl_1(id int);
  INSERT INTO tbl_1(id) value(1);
  INSERT INTO tbl_1(id) value(2);
  UPDATE tbl_1 SET id=200 WHERE id=1;
SAVEPOINT id-1upd;
  UPDATE tbl_1 SET id=1000 WHERE id=2;
ROLLBACK TO id-1upd;
  SELECT id FROM tbl_1;
  • 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, leaving the state of the data as it was prior to those changes.

Once the COMMIT statement completes, the transaction's changes cannot be rolled back.

COMMIT and ROLLBACK terminate the current transaction and release data locks. 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 Data Definition Language (DDL) manages table and index structure. The most basic items of DDL are the CREATE, ALTER, RENAME, DROP and TRUNCATE statements:

  • CREATE creates an object (a table, for example) in the database.
  • DROP deletes an object in the database, usually irretrievably.
  • ALTER modifies the structure of an existing object in various ways—for example, adding a column to an existing table.


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

Data types

Each column in an SQL table declares the type(s) that column may contain. ANSI SQL includes the following datatypes.[18]

Character strings

  • CHARACTER(n) or CHAR(n) — fixed-width n-character string, padded with spaces as needed
  • CHARACTER VARYING(n) or VARCHAR(n) — variable-width string with a maximum size of n characters
  • NATIONAL CHARACTER(n) or NCHAR(n) — fixed width string supporting an international character set
  • NATIONAL CHARACTER VARYING(n) or NVARCHAR(n) — variable-width NCHAR string

Bit strings

  • BIT(n) — an array of n bits
  • BIT VARYING(n) — an array of up to n bits


  • NUMERIC(precision, scale) or DECIMAL(precision, scale)

SQL provides a function to round numerics or dates, called TRUNC (in DB2, PostgreSQL, Oracle and MySQL) or ROUND (in Sybase, Oracle and Microsoft SQL Server)[19]

Date and Time

  • DATE
  • TIME

Data control

The Data Control Language (DCL) authorizes users and groups of users to access and manipulate data. Its two main statements are:

  • GRANT authorizes one or more users to perform an operation or a set of operations on an object.
  • REVOKE eliminates a grant, which may be the default grant.


    ON My_table 
    TO some_user, another_user;
    ON My_table 
    FROM some_user, another_user;

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 (implements SQL/PSM)
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.

Criticisms of SQL

SQL is a declarative computer language for use with relational databases. Interestingly, many of the original SQL features were inspired by, but violated, the semantics of the relational model and its tuple calculus realization. Recent extensions to SQL achieved relational completeness, but have worsened the violations, as documented in The Third Manifesto.

Practical criticisms of SQL include:

  • Implementations are inconsistent and, usually, incompatible between vendors. In particular date and time syntax, string concatenation, nulls, and comparison case sensitivity 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, which still invites the same mistake.)
  • It is also possible to misconstruct a WHERE on an update or delete, thereby affecting more rows in a table than desired. (A work-around is to use transactions or habitually type in the WHERE clause first, then fill in the rest later.)
  • 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.

Cross-vendor portability

Popular implementations of SQL commonly omit support for basic features of Standard SQL, such as the DATE or TIME data types. 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 implementors do not support the entire standard.
  • The standard does not specify database behavior in several important areas (e.g., indexes, file storage...), leaving implementations 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 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.
  • Software vendors often desire to create incompatibilities with other products, as it provides a strong incentive for their existing users to remain loyal (see vendor lock-in).


SQL was adopted as a standard by the American National Standards Institute (ANSI) in 1986 as SQL-86[20] and International Organization for Standardization (ISO) in 1987. The original SQL standard declared that the official pronunciation for SQL is "es queue el".[2] Many English-speaking database professionals still use the nonstandard[21] pronunciation /ˈsiːkwəl/ (like the word "sequel").

Until 1996, the National Institute of Standards and Technology (NIST) data management standards program certified SQL DBMS compliance with the SQL standard. Vendors now self-certify the compliance of their products.[22]

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

Year Name Alias Comments
1986 SQL-86 SQL-87 First formalized by ANSI.
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 SQL: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 SQL:2003   Introduced XML-related features, window functions, standardized sequences, and columns with auto-generated values (including identity-columns).
2006 SQL: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 enables 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 SQL:2008   Legalizes ORDER BY outside cursor definitions. Adds INSTEAD OF triggers. Adds the TRUNCATE statement.[23]

Interested parties may purchase SQL standards documents from ISO or ANSI. A draft of SQL:2008 is freely available as a zip archive.[24]

Standard structure

The SQL standard is divided into several parts, including:

SQL Framework, provides logical concept

SQL/Foundation, defined in ISO/IEC 9075, Part 2. This part of the standard contains the most central elements of the language. It consists of both mandatory and optional features.

The SQL/Bindings, specifies how SQL is to be bound to variable host languages,excluding Java.

The SQL/CLI, or Call-Level Interface, part is defined in ISO/IEC 9075, Part 3. SQL/CLI defines common interfacing components (structures and procedures) that can be used to execute SQL statements from applications written in other programming languages. SQL/CLI 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. Open Database Connectivity is a well-known superset of SQL/CLI. This part of the standard consists solely of mandatory features.

The SQL/PSM, or Persistent Stored Modules, part is defined by ISO/IEC 9075, Part 4. 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"). This part of the standard consists solely of optional features.

The SQL/MED, or Management of External Data, part is defined by ISO/IEC 9075, Part 9. 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. This part of the standard consists solely of optional features.

The SQL/OLB, or Object Language Bindings, part is defined by ISO/IEC 9075, Part 10. 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. This part of the standard consists solely of optional features.

The SQL/MM (Multimedia), This extends SQL to deal intelligently with large,complex and sometimes streaming items of data, such as video,audio and spatial data.

The SQL/Schemata, or Information and Definition Schemas, part is defined by ISO/IEC 9075, Part 11. 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.[25] This part of the standard contains both mandatory and optional features.

The SQL/JRT, or SQL Routines and Types for the Java Programming Language, part is defined by ISO/IEC 9075, Part 13. 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. This part of the standard consists solely of optional features.

The SQL/XML, or XML-Related Specifications, part is defined by ISO/IEC 9075, Part 14. 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. This part of the standard consists solely of optional features.

Alternatives to SQL

A distinction should be made between alternatives to relational query languages and alternatives to SQL. Below are proposed relational alternatives to SQL. See navigational database for alternatives to relational:

See also


  1. ^ Beaulieu, Alan (April 2009). Mary E. Treseler. ed. Learning SQL (2nd ed.). Sebastapol, CA, USA: O'Reilly. ISBN 978-0-596-52083-0. 
  2. ^ a b Chapple, Mike. "SQL Fundamentals". Databases. Retrieved 2009-01-28. 
  3. ^ Connolly, Thomas. Database Systems (2nd ed.). Addison-Wesley. p. 384. ISBN 0-201-34287-1. 
  4. ^ Codd, E.F. (June 1970). "A Relational Model of Data for Large Shared Data Banks". Communications of the ACM (Association for Computing Machinery) 13 (6): 377–387. doi:10.1145/362384.362685. Retrieved 2007-06-09. 
  5. ^ Chapple, Mike. "SQL Fundamentals". Databases. Retrieved 2007-06-10. 
  6. ^ "Structured Query Language (SQL)". International Business Machines. October 27, 2006. Retrieved 2007-06-10. 
  7. ^ Chamberlin, Donald D.; Boyce, Raymond F. (1974). "SEQUEL: A Structured English Query Language" (PDF). Proceedings of the 1974 ACM SIGFIDET Workshop on Data Description, Access and Control (Association for Computing Machinery): 249–264. Retrieved 2007-06-09. 
  8. ^ a b Oppel, Andy (March 1, 2004). Databases Demystified. San Francisco, CA: McGraw-Hill Osborne Media. pp. 90–91. ISBN 0-07-225364-9. 
  9. ^ "History of IBM, 1978". IBM Archives. IBM. Retrieved 2007-06-09. 
  10. ^ ANSI/ISO/IEC International Standard (IS). Database Language SQL—Part 2: Foundation (SQL/Foundation). 1999.
  11. ^ "INTO Clause (Transact-SQL)". SQL Server 2005 Books Online. Microsoft. 2007. Retrieved 2007-06-17;. 
  12. ^ ISO/IEC (2003). ISO/IEC 9075-1:2003, "SQL/Framework". ISO/IEC. Section 4.4.2: The null value. 
  13. ^ Coles, Michael (2005-06-27). "Four Rules for Nulls". SQL Server Central (Red Gate Software). 
  14. ^ ISO/IEC. ISO/IEC 9075-2:2003, "SQL/Foundation". ISO/IEC. 
  15. ^ M. Negri, G. Pelagatti, L. Sbattella (1989) Semantics and problems of universal quantification in SQL.
  16. ^ Fratarcangeli, Claudio (1991). Technique for universal quantification in SQL. Retrieved from
  17. ^ Kawash, Jalal (2004). Complex quantification in Structured Query Language (SQL): a tutorial using relational calculus - Journal of Computers in Mathematics and Science Teaching ISSN 0731-9258 Volume 23, Issue 2, 2004 AACE Norfolk, Virginia. Retrieved from
  18. ^ Information Technology - Database Language SQL (Proposed revised text of DIS 9075)
  19. ^ Arie Jones, Ryan K. Stephens, Ronald R. Plew, Alex Kriegel, Robert F. Garrett (2005), SQL Functions Programmer's Reference. Wiley, 127 pages
  20. ^ American National Standards Institute. X3H2 Records, 1978-1995. Finding Aid.
  21. ^ Melton, Jim; Alan R Simon (1993). Understanding the New SQL: A Complete Guide. Morgan Kaufmann. p. 536. ISBN 1558602453. "chapter 1.2 What is SQL? SQL (correctly pronounced "ess cue ell," instead of the somewhat common "sequel"), is a..." 
  22. ^ Doll, Shelley (June 19, 2002). "Is SQL a Standard Anymore?". TechRepublic's TechRepublic. Retrieved 2010-01-07. 
  23. ^
  24. ^ Zip archive of the SQL:2008 draft from Whitemarsh Information Systems Corporation.
  25. ^ ISO/IEC 9075-11:2008: Information and Definition Schemas (SQL/Schemata). 2008. p. 1. 

External links


Up to date as of January 15, 2010

Definition from Wiktionary, a free dictionary



Wikipedia has an article on:



See usage note below.



  1. Structured Query Language.


Usage notes

  • (structured query language): The first form of SQL was called SEQUEL, pronounced like sequel. As a result, many speakers still pronounce SQL like sequel. (For these speakers, SQL is an acronym.)


Up to date as of January 23, 2010
(Redirected to Structured Query Language article)

From Wikibooks, the open-content textbooks collection

See also: MySQL for a thorough look at one SQL variant.



Relational Databases

The main drive behind a relational database is to increase accuracy by increasing the efficiency with which data is stored. For example, the names of each of the millions of people who immigrated to the United States through Ellis Island at the turn of the 20th century were recorded by hand on large sheets of paper; people from the city of London had their country of origin entered as England, or Great Britain, or United Kingdom, or U.K., or UK, or Engl., etc. Multiple ways of recording the same information leads to future confusion when there is a need to simply know how many people came from the country now known as the United Kingdom.

The modern solution to this problem is the database. A single entry is made for each country, for example, in a reference list that might be called the Country table. When someone needs to indicate the United Kingdom, he only has one choice available to him from the list: a single entry called "United Kingdom". In this example, "United Kingdom" is the unique representation of a country, and any further information about this country can use the same term from the same list to refer to the same country. For example, a list of telephone country codes and a list of European castles both need to refer to countries; by using the same Country table to provide this identical information to both of the new lists, we've established new relationships among different lists that only have one item in common: country. A relational database, therefore, is simply a collection of lists that share some common pieces of information.

If you are not familiar with the concepts of databases, you can begin with Database Programming. For more technical information on different software applications that allow users to create databases, see the Wikipedia article Relational database management system (RDBMS)s.

Structured Query Language (SQL)

SQL, which is an initialism for Structured Query Language, is a language to request data from a database, to add, update, or remove data within a database, or to manipulate the metadata of the database.

SQL is generally pronounced as the three letters in the name, e.g. ess-cue-ell, or in some people's usage, as the word sequel.

SQL is a declarative language in which the expected result or operation is given without the specific details about how to accomplish the task. The steps required to execute SQL commands are handled transparently by the SQL database. Sometimes SQL is characterized as non-procedural because procedural languages generally require the details of the operations to be specified, such as opening and closing tables, loading and searching indexes, or flushing buffers and writing data to filesystems. Therefore, SQL is considered to be designed at a higher conceptual level of operation than procedural languages because the lower level logical and physical operations aren't specified and are determined by the SQL engine or server process that executes it.

Instructions are given in the form of commands, consisting of a specific SQL command and additional parameters and operands that apply to that command. The simplest example of how to retrieve all of the rows and columns of a table named Customers is:

SELECT * FROM Customers

The asterisk (*) that follows the SELECT command is a wildcard character that refers to all of the columns of the table. SQL assumes that the whole set of records is to be retrieved unless you provide conditional logic to restrict the result to a subset, which is added using a WHERE clause. Following are a few typical SQL examples for a table named Customers with three columns: CustomerID, LastName, and FirstName.

SELECT LastName, FirstName FROM Customers WHERE CustomerID=99;

Returns the last name and first name of the customers that have a CustomerID value of 99. Typically this will return a single row, if it exists, because values such as CustomerID would be defined as a primary key that uniquely identifies one customer and cannot have other rows identified with the same value

SELECT LastName, FirstName FROM Customers ORDER BY LastName, FirstName

Returns an alphabetized list of the last and first names of all customers

INSERT INTO Customers (CustomerID, LastName, FirstName) VALUES (1, "Doe", "John")

Creates a row with the CustomerID of 1 for John Doe.

UPDATE Customers SET FirstName="Johnny" WHERE CustomerID=1

Changes John Doe's first name to Johnny

DELETE Customers WHERE CustomerID=1

Removes the row where the CustomerID is the value 1

In general, SQL isn't case sensitive and ignores excess whitespace characters, except for the contents of an alphanumeric string. Upper case is frequently used for SQL commands as a matter of style, but this is not a universal convention.

Some databases support stored procedures in which SQL is embedded within another procedural language to manipulate data or tables on the server for more complex operations than allowed by SQL alone, and without necessarily returning data from the server. These procedural languages are usually proprietary to the vendor of the SQL server. For example, Oracle uses its own language PL/SQL while Microsoft SQL Server uses T-SQL. These procedural languages are similar in design and function, but use different syntax that are not interoperable.

SQL can also be embedded within other languages using SQL modules, libraries, or pre-compilers that offer functions to open a path of communication to the SQL server to send commands and retrieve results. Since the execution of an SQL command is a useful service that is performed externally to the host language by the SQL server, the overall processing is divided into two tiers: the client tier and the server tier. The modules and libraries used to provide the connection between the client and server are usually referred to as middleware, particularly when connections are allowed with one interface from the client to various servers from different vendors. ODBC, JDBC, OLEDB are common middleware libraries, among a large number of others specific to a wide range of client hosting operating systems and programming models. The use of SQL has become so prevalent that it would be unusual to find an application language that doesn't support it in some manner.

SQL commands and their modifiers are based upon official SQL standards and certain extensions to that each database provider implements. Commonly commands are grouped into the following categories:

Data Definition Language ( DDL )
  • CREATE - Used to create a new table, a view of a table, or other object in database.
  • ALTER - Used to modify an existing database object, such as a table.
  • DROP - Used to delete an entire table, a view of a table or other object in the database.
Data Control Language ( DCL )
  • GRANT - Used to give a privilege to someone.
  • REVOKE - Used to take back privileges granted to someone.
Data Manipulation Language ( DML )
  • INSERT - Used to create a record.
  • UPDATE - Used to change certain records.
  • DELETE - Used to delete certain records.
Data Query Language ( DQL )
  • SELECT - Used to retrieve certain records from one or more tables.

Getting a database to work with

you will need a database system to work with. Popular database systems are listed as RDBMSes in Wikipedia. Among them are:

  • PostgreSQL and MySQL (Wikibook), two free and Open-Source database systems for Linux, Mac OS X, Windows
  • SQLite, a small-scale public domain embedded client/server that may also be used. The primary benefit is the zero configuration required to run it, and each database is a single file
  • Oracle, IBM DB2 and Microsoft SQL Server are three popular commercial systems.

Once installed there are many ways to enter SQL commands. Common ways include a command-line-interface tool such as psql or a text-box inside a graphical-user-interface tool such as pgAdminIII.

SQL commands are often stored together in text files or embedded in source code so a text editor is recommended.

Data Definition

The data definition statements are used to CREATE, to ALTER and to DROP the tables that contain data.

Tables, rows and columns

The easiest and most fun way to think about database structure is to compare it to a spreadsheet.

Think of the entire spreadsheet as a representation of the database. A sheet in a spreadsheet is the same as a table in a database. Just as each sheet in a spreadsheet has columns and rows, so does a table.

Columns in database tables are the type of each bit of data contained in a row.

Think of a row of data like a sentence. A sentence has different words of different types (nouns, adjectives, etc) likewise a column can be a different type. Different column types include (but are not limited to) integer, varchar (that is a variable number of characters - so VARCHAR(20) would be able to contain up to 20 ASCII values), date or blob (binary large object).

Creating Tables

Example code for a table that describes the produce section of the grocery store:

     fruit_name TEXT,
     price_per_pound NUMERIC,
     quantity_available NUMERIC

This would produce an empty table that has field names of fruit_name, price_per_pound and quantity_available. Their type is also specified (as in "TEXT" and "NUMERIC") and any data entered must be of that type.

Foreign Keys

In most database systems, you can specify that values in one column match values in a column in another table. For example, you have a table that tracks all the dog owners in the neighborhood:

owner dog name dog breed
Joe Smith Rex mastiff
Rosa Gomez Gato chihuahua
Smitty Jones Spot mastiff

And let's say you have another table that describes the attributes of different dog breeds:

dog breed average size poop description
mastiff enormous horrible; will kill most grasses and flowers.
chihuahua tiny surprisingly pungent

Ok, so you want to make sure that when you add new neighbors to the list, you only add valid dog breeds off your dog breed table. You can use the following sql code to enforce that:

 CREATE TABLE dog_types (
     dog_breed TEXT,
     average_size TEXT,
     poop_description TEXT
 CREATE TABLE dog_owners (
     owners TEXT,
     dog_name TEXT,
     dog_breed TEXT REFERENCES dog_types

This is a foreign key in SQL jargon. There are much more interesting applications than this.


Write a set of tables that a teacher can use to create an online multiple-choice testing program. One table will hold questions and the answer_id of the correct answer. Another table will hold a list of answers. A third table will hold the available answers for each question.

For example, imagine two questions exist in the question table:

1. what is 6 * 30?
2. who was the first US president?

And imagine the following four answers exist in the answer table:

1. 45
2. George Washington
3. Thomas Jefferson
4. 180

Now create a third table that lists answers one and four as possible answers for question 1 and answers 2 and 3 for question 2.

Got it?

Exercise solution

This program illustrates one use of a compound foreign key constraint. I needed a way to track answers to multiple-choice questions, and to limit possible answers to each question. For example, I want to make sure that if I ask the question "what is your favorite color?" then the answer is a color, and not something silly like "yes."

This table holds each question:

 CREATE TABLE questions (
     q_text TEXT

Here are some questions. Since I used the serial data type, I'm not going to assign the q_id column. Postgresql will assign the q_id automatically.

 INSERT INTO questions (q_text) VALUES ('What is your favorite color?'); /* q_id 1 */
 INSERT INTO questions (q_text) VALUES ('Is it raining outside?');       /* q_id 2 */

After inserting, let's see what the database looks like now:

 SELECT * FROM questions;

This results in:

q_id q_text
1 What is your favorite color?
2 Is it raining outside?

Now, create a table which lists every possible answer, each with a unique id:

CREATE TABLE all_answers (
   a_text TEXT

These are some answers:

 INSERT INTO all_answers (a_text) VALUES ('red');      /* a_id 1 */
 INSERT INTO all_answers (a_text) VALUES ('yes');      /* a_id 2 */
 INSERT INTO all_answers (a_text) VALUES ('green');    /* a_id 3 */
 INSERT INTO all_answers (a_text) VALUES ('no');       /* a_id 4 */

Here's what all_answers looks like after adding data:

 SELECT * FROM all_answers;


a_id a_text
1 red
2 yes
3 green
4 no

This table links each question to meaningful possible answers. I am using question ID (q_id) and answer ID (a_id) numbers in order to save space.

 CREATE TABLE possible_answers (
     q_id INTEGER REFERENCES questions (q_id),
     a_id INTEGER REFERENCES all_answers (a_id),
     PRIMARY KEY (q_id, a_id)

Now, I'll link certain questions with certain answers:

 INSERT INTO possible_answers (q_id, a_id) VALUES (1, 1);

This statement linked 'What is your favorite color?' with 'red'.

 INSERT INTO possible_answers (q_id, a_id) VALUES (1, 3);
 INSERT INTO possible_answers (q_id, a_id) VALUES (2, 2);
 INSERT INTO possible_answers (q_id, a_id) VALUES (2, 4);

The last statement linked 'Is it raining outside?' with 'no'.

And, just to continue the trend...

 SELECT * FROM possible_answers;
q_id a_id
1 1
1 3
2 2
2 4

Finally, this is the table that will record the actual answer given for a question and make sure that the answer is appropriate for the question:

 CREATE TABLE real_answers (
    q_id INTEGER REFERENCES questions (q_id),
    a_id INTEGER REFERENCES all_answers (a_id),
    FOREIGN KEY (q_id, a_id) REFERENCES possible_answers (q_id, a_id)

Now, watch what happens when I try to insert an answer that doesn't match the question into the database. I'm going to try to answer the question:

"What is your favorite color?"

with the answer


Hopefully the database will prevent me.

SELECT q_text FROM questions WHERE q_id = 1;


What is your favorite color?
SELECT a_text FROM all_answers WHERE a_id = 2;


INSERT INTO real_answers (q_id, a_id) VALUES (1, 2);

Database answer:

ERROR:  $3 referential integrity violation - key referenced from real_answers
not found in possible_answers

Hurray! We are prevented from entering the data! Now, let's try storing an acceptable answer.

INSERT INTO real_answers (q_id, a_id) VALUES (1,1);

Database answer:

INSERT 17196 1

That means it worked!

Data Manipulation

Adding Data

The insert statement adds new records.

Extending the fruit store metaphor:

INSERT INTO fruit ( fruit_name, price_per_pound, quantity_available ) VALUES ('apples', 0.90, 400);
INSERT INTO fruit ( fruit_name, price_per_pound, quantity_available ) VALUES ('bananas', 0.59, 800);

SELECT * FROM fruit;
fruit_name price_per_pound quantity_available
bananas 0.59 800
apples 0.90 400

Removing Data

The DELETE statement removes existing records.


Deletes every row in table fruit.

DELETE FROM fruit WHERE fruit_name = 'pears';

Deletes every fruit named pears in table fruit.

Updating Data

The UPDATE statement changes existing records.

UPDATE fruit SET QUANTITY = 200 WHERE fruit_name = 'apples';

This query changes every fruit named apples, to give it a quantity of 200.

Data Querying

Retrieving Data

All data retrieval is via a SELECT statement. A SELECT statement will return a new table, and the statement describes the rows and columns of the table. The statement basically answers three questions: what will the new table's columns be, what will its rows be, and where will the data come from.

The basic structure is as follows:

SELECT FirstColumnName [, SecondColumnName...]

FROM FirstTableName [, SecondTableName...]

WHERE FirstCondition [AND SecondCondition...]

ORDER BY colname [, colname,...];

The first line, SELECT FirstColumnName, SecondColumnName, ... tells us what the columns of the table will be. The next line, FROM FirstTableName, SecondTableName, ... tells us where the data will be pulled from. The remainder of the query — usually WHERE FirstCondition AND SecondCondition ... — specifies a list of conditions which will be true for every output row.

For example if a table named pets has a field, PetID, and a field, PetName,


would print out the entire table.

SELECT PetName FROM pets;

would print out only the names, and


would print out only the name of the pet in the table whose ID number was 1.


The power of relational databases is that they allow us to "JOIN" different tables together and view associated information.

Inner Join

If we have two tables Pet_Types and Pet_Owners, and they look like this:
Pet_Types (Pet_Type_ID [primary key], Breed, Characteristic)
Pet_Owners (Owner_ID [primary key], Owner_Name, Pet_Type_ID)

Let us say that we are looking for humans who own yappy dogs:

What we do is an inner join on Pet_Types and Pet_Owners ON the column which is the same.

SELECT Owner_name
FROM Pet_Types
INNER JOIN Pet_Owners ON Pet_Types.Pet_Type_ID = Pet_Owners.Pet_Type_ID
WHERE Pet_Types.Characteristic= 'yappy';

How this query is processed: first, since it specified two tables, a new table would be generated that includes every combination of one row from the first table and one row from the second. If there are 8 rows in the first and 5 in the second, then this joined table would include 8x5=40 rows. Most of these rows are just noise. The only ones which make sense are the ones for which the breed in the first and the breed in the second match, so the ON Pet_Types.Pet_Type_ID = Pet_Owners.Pet_Type_ID tells the engine to throw out every row for which the Pet_Type_IDs don't match. Within this much smaller and much more coherent table, we want only those rows for which Pet_Types.Characteristics="yappy". Within those rows (if any), we ask to see the Owner_name column.

Outer Join

If we have two tables Pet_Types and Pet_Owners, and they look like this:
Pet_Types (Pet_Type_ID [primary key], Breed, Characteristic)
Pet_Owners (Owner_ID [primary key], Owner_Name, Pet_Type_ID)

Let us say that we are looking for all humans, and any dogs that they own, still listing a human that does not own a dog.

What we can do is an outer join on Pet_Types and Pet_Owners ON the column which is the same.

SELECT Owner_name, Breed
FROM Pet_Types
RIGHT OUTER JOIN Pet_Owners ON Pet_Types.Pet_Type_ID = Pet_Owners.Pet_Type_ID;

This query is processed just like the Inner Join but the result set will contain all records from the Pet_Owners table (the right side of the join) even if there is no matching Pet_Type_ID in the Pet_Types table. The Breed name for these records will be null.

Alternatively we can look for all pet types, also adding human owners where they exist.

SELECT Owner_name, Breed
FROM Pet_Types
LEFT OUTER JOIN Pet_Owners ON Pet_Types.Pet_Type_ID = Pet_Owners.Pet_Type_ID;

This time the result set will contain all records from the Pet_Types table (the left side of the join) even if there is no matching Pet_Type_ID in the Pet_Owners table. The Owner name for these records will be null.

If we want to look at all records, we can use a full outer join, to see all Pet_Types and all Pet_Owners. For example, show all Yappy dogs, with owners where they exist:

SELECT Owner_name, Breed
FROM Pet_Types
FULL OUTER JOIN Pet_Owners ON Pet_Types.Pet_Type_ID = Pet_Owners.Pet_Type_ID
WHERE Pet_Types.Characteristic = 'yappy';

This combines the two previous Outer join types.


UNION, EXCEPT, and INTERSECT expressions The UNION, EXCEPT, and INTERSECT operators all operate on multiple result sets to return a single result set: · The UNION operator combines the output of two query expressions into a single result set. Query expressions are executed independently, and their output is combined into a single result table. The EXCEPT operator evaluates the output of two query expressions and returns the difference between the results. The result set contains all rows returned from the first query expression except those rows that are also returned from the second query expression. The INTERSECT operator evaluates the output of two query expressions and returns only the rows common to each. The following figure illustrates these concepts with Venn diagrams, in which the shaded portion indicates the result set.

The UNION operator is used to combine the information from 2 different tables into one result set.

For example, let's say that one table lists pet owners in LA and another lists pet owners in Chicago, and we would like them in one table. The UNION statement lies between two SELECT statements, and does what we desire:

SELECT * FROM Chicago_pets

The converse to this is the EXCLUDE: say that we want only pets outside of LA:

SELECT * FROM California_pets

See also

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