SQL (Structured Query Language) is a domain-specific language used in programming and designed for managing data held in a relational database management system (RDBMS), or for stream processing in a relational data stream management system (RDSMS). It is particularly useful in handling structured data, i.e. data incorporating relations among entities and variables.

SQL offers two main advantages over older read–write APIs such as ISAM or VSAM. Firstly, it introduced the concept of accessing many records with one single command. Secondly, it eliminates the need to specify how to reach a record, e.g. with or without an index.

Originally based upon relational algebra and tuple relational calculus, SQL consists of many types of statements, which may be informally classed as sublanguages, commonly: a data query language (DQL), a data definition language (DDL),^[b] a data control language (DCL), and a data manipulation language (DML). The scope of SQL includes data query, data manipulation (insert, update and delete), data definition (schema creation and modification), and data access control. Although SQL is essentially a declarative language (4GL), it includes also procedural elements.

SQL was one of the first commercial languages to utilize Edgar F. Codd’s relational model. The model was described in his influential 1970 paper, "A Relational Model of Data for Large Shared Data Banks". Despite not entirely adhering to the relational model as described by Codd, it became the most widely used database language.

SQL became a standard of the American National Standards Institute (ANSI) in 1986, and of the International Organization for Standardization (ISO) in 1987. Since then, the standard has been revised to include a larger set of features. Despite the existence of such standards, most SQL code is not completely portable among different database systems without adjustments.

Paradigm	Multi-paradigm: declarative
Family	Programming language
Designed by	Donald D. Chamberlin Raymond F. Boyce
Developer	ISO/IEC
First appeared	1974; 46 years ago
Typing discipline	Static, strong
OS	Cross-platform
File formats	File format details
Filename extension	.sql
Internet media type	application/sql
Developed by	ISO/IEC
Initial release	1986
Latest release	SQL:2016 (December 2016; 3 years ago)
Type of format	Database
Standard	ISO/IEC 9075
Open format?	Yes
Major implementations
Many
Dialects
SQL-86 SQL-89 SQL-92 SQL:1999 SQL:2003 SQL:2006 SQL:2008 SQL:2011 SQL:2016
Influenced by
Datalog
Influenced
CQL, LINQ, SPARQL, SOQL, PowerShell, JPQL, jOOQ, N1QL
Structured Query Language at Wikibooks

Contents

• History
• Design
• Syntax
• Procedural extensions
• Interoperability and standardization
• Alternatives
• Distributed SQL processing
• Criticisms
  • Orthogonality and completeness
  • NULLs
  • Duplicates
  • Impedance mismatch
• Books

History

Edgar Frank Codd

Publications

• Relational Database: A Practical Foundation for Productivity
• Cellular Automata
• A Relational Model of Data for Large Shared Data Banks
• Relational Completeness of Data Base Sublanguages
• Extending the Database Relational Model to Capture More Meaning
• Multiprogramming STRETCH: feasibility considerations
• Derivability, Redundancy and Consistency of Relations Stored in Large Data Banks
• The Relational Model for Database Management: Version 2

Don Chamberlin at the Computer History Museum's 2009 Fellows Award event

Publications

• Integration of SQL and XQuery in IBM DB2
• Implementation of a Structured English Query Language
• System R: Relational Approach to Database Management
• Quilt: An XML Query Language for Heterogeneous Data Sources
• Extending XQuery for Analytics
• Access Path Selection in a Relational Database Management System
• SEQUEL: A structured English query language
• XML and Relational Database Management Systems: the Inside Story
• Specifying queries as relational expressions: The SQUARE Data Sublanguage
• A History and Evaluation of System R
• XQuery 1.0: An XML Query Language
• XQueryP: Programming with XQuery

SQL was initially developed at IBM by Donald D. Chamberlin and Raymond F. Boyce after learning about the relational model from Ted Codd in the early 1970s. This version, initially called SEQUEL (Structured English Query Language), was designed to manipulate and retrieve data stored in IBM's original quasi-relational database management system, System R, which a group at IBM San Jose Research Laboratory had developed during the 1970s.

Chamberlin and Boyce's first attempt of a relational database language was Square, but it was difficult to use due to subscript notation. After moving to the San Jose Research Laboratory in 1973, they began work on SEQUEL. The acronym SEQUEL was later changed to SQL because "SEQUEL" was a trademark of the UK-based Hawker Siddeley Dynamics Engineering Limited company.

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.

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 RDMS with aspirations of selling it to the U.S. Navy, Central Intelligence Agency, and other U.S. government agencies. In June 1979, Relational Software, Inc. introduced the first commercially available implementation of SQL, Oracle V2 (Version2) for VAX computers.

By 1986, ANSI and ISO standard groups officially adopted the standard "Database Language SQL" language definition. New versions of the standard were published in 1989, 1992, 1996, 1999, 2003, 2006, 2008, 2011 and, most recently, 2016.

Design

SQL deviates in several ways from its theoretical foundation, the relational model and its tuple calculus. In that model, a table is a set of tuples, while in SQL, tables and query results are lists of rows: the same row may occur multiple times, and the order of rows can be employed in queries (e.g. in the LIMIT clause).

Critics argue that SQL should be replaced with a language that returns strictly to the original foundation: for example, see The Third Manifesto. However, no known proof exists that such uniqueness cannot be added to SQL itself, or at least a variation of SQL. In other words, it's quite possible that SQL can be "fixed" or at least improved in this regard such that the industry may not have to switch to a completely different query language to obtain uniqueness. Debate on this remains open.

Syntax

The syntax of the SQL programming language is defined and maintained by ISO/IEC SC 32 as part of ISO/IEC 9075. This standard is not freely available. Despite the existence of the standard, SQL code is not completely portable among different database systems without adjustments.

Contents

• Language elements
• Operators
• Comments
• Queries
  • Subqueries
  • Derived table
  • Null or three-valued logic (3VL)
  • Data manipulation
  • Transaction controls
  • Data definition
  • Data types
  • Data control

Language elements

 

 

A chart showing several of the SQL language elements that compose a single statement. This adds one to the population of the USA in the country table.

 

 

The SQL language is subdivided into several language elements, including:

• Clauses, which are constituent components of statements and queries. (In some cases, these are optional.)
• 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) (true/false/unknown) or Boolean truth values and are used to limit the effects of statements and queries, or to change program flow.
• Queries, which retrieve the data based on specific criteria. This is an important element of SQL.
• Statements, which may have a persistent effect on schemata and data, or 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.

Operators

Operator	Description	Example
=	Equal to	Author = 'Alcott'
<>	Not equal to (many DBMSs accept != in addition to <>)	Dept <> 'Sales'
>	Greater than	Hire_Date > '2012-01-31'
<	Less than	Bonus < 50000.00
>=	Greater than or equal	Dependents >= 2
<=	Less than or equal	Rate <= 0.05
BETWEEN	Between an inclusive range	Cost BETWEEN 100.00 AND 500.00
LIKE	Begins with a character pattern	Full_Name LIKE 'Will%'
	Contains a character pattern	Full_Name LIKE '%Will%'
[NOT] IN	Equal to one of multiple possible values	DeptCode IN (101, 103, 209)
IS [NOT] NULL	Compare to null (missing data)	Address IS NOT NULL
IS [NOT] TRUE or IS [NOT] FALSE	Boolean truth value test	PaidVacation IS TRUE
IS NOT DISTINCT FROM	Is equal to value or both are nulls (missing data)	Debt IS NOT DISTINCT FROM - Receivables
AS	Used to change a column name when viewing results	SELECT employee AS "department1"

Other operators have at times been suggested or implemented, such as the skyline operator (for finding only those rows that are not 'worse' than any others).

SQL has the case expression, which was introduced in SQL-92. In its most general form, which is called a "searched case" in the SQL standard:

CASE WHEN n > 0
          THEN 'positive'
     WHEN n < 0
          THEN 'negative'
     ELSE 'zero'
END

SQL tests WHEN conditions in the order they appear in the source. If the source does not specify an ELSE expression, SQL defaults to ELSE NULL. An abbreviated syntax called "simple case" can also be used:

CASE n WHEN 1
            THEN 'One'
       WHEN 2
            THEN 'Two'
       ELSE 'I cannot count that high'
END

This syntax uses implicit equality comparisons, with the usual caveats for comparing with NULL.

There are two short forms for special CASE expressions: COALESCE and NULLIF.

The COALESCE expression returns the value of the first non-NULL operand, found by working from left to right, or NULL if all the operands equal NULL.

COALESCE(x1,x2)

is equivalent to:

CASE WHEN x1 IS NOT NULL THEN x1
     ELSE x2
END

The NULLIF expression has two operands and returns NULL if the operands have the same value, otherwise it has the value of the first operand.

NULLIF(x1, x2)

is equivalent to

CASE WHEN x1 = x2 THEN NULL ELSE x1 END

Comments

Standard SQL allows two formats for comments: -- comment, which is ended by the first newline, and /* comment */, which can span multiple lines.

Queries

The most common operation in SQL, the query, makes use of 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 provided in some databases.

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

A query includes a list of columns to include in the final result, normally immediately following the SELECT keyword. An asterisk ("*") can 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) to retrieve data from. 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 where the comparison predicate does not evaluate to True.
• The GROUP BY clause projects 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 column[s] to use to sort the resulting data, and in which direction to sort them (ascending or descending). Without an ORDER BY clause, the order of rows returned by an SQL query is undefined.
• The DISTINCT keyword eliminates duplicate data.
• The OFFSET clause specifies the number of rows to skip before starting to return data. The FETCH FIRST clause specifies the number of rows to return. (Some SQL databases instead have non-standard alternatives, e.g. LIMIT, TOP or ROWNUM.)

The clauses of a query have a particular order of execution, which is denoted by the number on the right hand side. It is as follows:

SELECT <columns>	5.
FROM <table>	1.
WHERE <predicate on rows>	2.
GROUP BY <columns>	3.
HAVING <predicate on groups>	4.
ORDER BY <columns>	6.
OFFSET	7.
FETCH FIRST	8.

The following example of a SELECT query 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 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 AS 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 Book table, one could re-write the query above 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 certain column-naming conventions for natural joins to work effectively.

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

Subqueries

Queries can be nested so that the results of one query can be used in another query via a relational operator or aggregation function. A nested query is also known as a subquery. While joins and other table operations provide computationally superior (i.e. faster) alternatives in many cases, the use of subqueries introduces a hierarchy in execution that can be useful or necessary. In the following example, the aggregation function AVG receives as input the result of a subquery:

SELECT isbn,
       title,
       price
 FROM  Book
 WHERE price < (SELECT AVG(price) FROM Book)
 ORDER BY title;

A subquery can use values from the outer query, in which case it is known as a correlated subquery.

Since 1999 the SQL standard allows WITH clauses for subqueries, i.e. named subqueries, usually called common table expressions (also called subquery factoring). CTEs can also be recursive by referring to themselves; the resulting mechanism allows tree or graph traversals (when represented as relations), and more generally fixpoint computations.

Derived table

A derived table is the use of referencing an SQL subquery in a FROM clause. Essentially, the derived table is a subquery that can be selected from or joined to. The derived table functionality allows the user to reference the subquery as a table. The inline view is also referred to as an inline view or a subselect.

In the following example, the SQL statement involves a join from the initial "Book" table to the derived table "sales". This derived table captures associated book sales information using the ISBN to join to the "Book" table. As a result, the derived table provides the result set with additional columns (the number of items sold and the company that sold the books):

SELECT b.isbn, b.title, b.price, sales.items_sold, sales.company_nm
FROM Book b
  JOIN (SELECT SUM(Items_Sold) Items_Sold, Company_Nm, ISBN
        FROM Book_Sales
        GROUP BY Company_Nm, ISBN) sales
  ON sales.isbn = b.isbn

Null or three-valued logic (3VL)

 

The concept of Null allows SQL to deal with missing information in the relational model. The word NULL is a reserved keyword in SQL, used to identify the Null special marker. Comparisons with Null, for instance equality (=) in WHERE clauses, results in an Unknown truth value. In SELECT statements SQL returns only results for which the WHERE clause returns a value of True; i.e., it excludes results with values of False and also excludes those whose value is Unknown.

Along with True and False, the Unknown resulting from direct comparisons with Null thus brings a fragment of three-valued logic to SQL. The truth tables SQL uses for AND, OR, and NOT correspond to a common fragment of the Kleene and Lukasiewicz three-valued logic (which differ in their definition of implication, however SQL defines no such operation).^[6]

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 = q p True False Unknown q True True False Unknown False False True Unknown Unknown Unknown Unknown Unknown

q NOT q True False False True Unknown Unknown

There are however disputes about the semantic interpretation of Nulls in SQL because of its treatment outside direct comparisons. As seen in the table above, direct equality comparisons between two NULLs in SQL (e.g. NULL = NULL) return a truth value of Unknown. This is in line with the interpretation that 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. However, the principle that two Nulls aren't equal to each other is effectively violated in the SQL specification for the UNION and INTERSECT operators, which do identify nulls with each other. Consequently, these set operations in SQL may produce results not representing sure information, unlike operations involving explicit comparisons with NULL (e.g. those in a WHERE clause discussed above). In Codd's 1979 proposal (which was basically adopted by SQL92) this semantic inconsistency is rationalized by arguing that removal of duplicates in set operations happens "at a lower level of detail than equality testing in the evaluation of retrieval operations". However, computer-science professor Ron van der Meyden concluded that "The inconsistencies in the SQL standard mean that it is not possible to ascribe any intuitive logical semantics to the treatment of nulls in SQL."

Additionally, because SQL operators return Unknown when comparing anything with Null directly, SQL provides two Null-specific comparison predicates: IS NULL and IS NOT NULL test whether data is or is not Null. SQL does not explicitly support universal quantification, and must work it out as a negated existential quantification. There is also the "<row value expression> IS DISTINCT FROM <row value expression>" infixed comparison operator, which returns TRUE unless 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>)". SQL:1999 also introduced BOOLEAN type variables, which according to the standard can also hold Unknown values if it is nullable. In practice, a number of systems (e.g. PostgreSQL) implement the BOOLEAN Unknown as a BOOLEAN NULL, which the standard says that the NULL BOOLEAN and UNKNOWN "may be used interchangeably to mean exactly the same thing".C. Date (2011). SQL and Relational Theory: How to Write Accurate SQL Code. O'Reilly Media, Inc. p. 83. ISBN 978-1-4493-1640-2.</ref>

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.:

INSERT INTO example
 (column1, column2, column3)
 VALUES
 ('test', 'N', NULL);

• UPDATE modifies a set of existing table rows, e.g.:

UPDATE example
 SET column1 = 'updated value'
 WHERE column2 = 'N';

• DELETE removes existing rows from a table, e.g.:

DELETE FROM example
 WHERE column2 = 'N';

• 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".

 MERGE INTO table_name USING table_reference ON (condition)
 WHEN MATCHED THEN
 UPDATE SET column1 = value1 [, column2 = value2 ...]
 WHEN NOT MATCHED THEN
 INSERT (column1 [, column2 ...]) VALUES (value1 [, value2 ...])

Transaction controls

Transactions, if available, wrap DML operations:

• START TRANSACTION (or BEGIN WORK, or BEGIN TRANSACTION, depending on SQL dialect) marks the start of a database transaction, which either completes entirely or not at all.
• SAVE TRANSACTION (or SAVEPOINT) saves the state of the database at the current point in transaction

CREATE TABLE tbl_1(id int);
 INSERT INTO tbl_1(id) VALUES(1);
 INSERT INTO tbl_1(id) VALUES(2);
COMMIT;
 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 makes all data changes in a transaction permanent.
• ROLLBACK discards all data changes since the last COMMIT or ROLLBACK, leaving 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. The following example shows a classic transfer of funds transaction, where money is removed from one account and added to another. If either the removal or the addition fails, the entire transaction is rolled back.

START TRANSACTION;
 UPDATE Account SET amount=amount-200 WHERE account_number=1234;
 UPDATE Account SET amount=amount+200 WHERE account_number=2345;
IF ERRORS=0 COMMIT;
IF ERRORS<>0 ROLLBACK;

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, e.g.:

CREATE TABLE example(
 column1 INTEGER,
 column2 VARCHAR(50),
 column3 DATE NOT NULL,
 PRIMARY KEY (column1, column2)
);

• ALTER modifies the structure of an existing object in various ways, for example, adding a column to an existing table or a constraint, e.g.:

ALTER TABLE example ADD column4 INTEGER DEFAULT 25 NOT NULL;

• TRUNCATE deletes all data from a table in a very fast way, deleting the data inside the table and not the table itself. It usually implies a subsequent COMMIT operation, i.e., it cannot be rolled back (data is not written to the logs for rollback later, unlike DELETE).

TRUNCATE TABLE example;

• DROP deletes an object in the database, usually irretrievably, i.e., it cannot be rolled back, e.g.:

DROP TABLE example;

Data types

Each column in an SQL table declares the type(s) that column may contain. ANSI SQL includes the following data types.

Character strings and national 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
• CHARACTER LARGE OBJECT(n [ K | M | G | T ]) (or CLOB(n [ K | M | G | T ])): character large object with a maximum size of n [ K | M | G | T ] 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
• NATIONAL CHARACTER LARGE OBJECT(n [ K | M | G | T ]) (or NCLOB(n [ K | M | G | T ])): national character large object with a maximum size of n [ K | M | G | T ] characters

For the CHARACTER LARGE OBJECT and NATIONAL CHARACTER LARGE OBJECT data types, the multipliers K (1 024), M (1 048 576), G (1 073 741 824) and T (1 099 511 627 776) can be optionally used when specifying the length.

Binary

• BINARY(n): Fixed length binary string, maximum length n.
• BINARY VARYING(n) (or VARBINARY(n)): Variable length binary string, maximum length n.
• BINARY LARGE OBJECT(n [ K | M | G | T ]) (or BLOB(n [ K | M | G | T ])): binary large object with a maximum length n [ K | M | G | T ].

For the BINARY LARGE OBJECT data type, the multipliers K (1 024), M (1 048 576), G (1 073 741 824) and T (1 099 511 627 776) can be optionally used when specifying the length.

Boolean

• BOOLEAN

The BOOLEAN data type can store the values TRUE and FALSE.

Numerical

• INTEGER (or INT), SMALLINT and BIGINT
• FLOAT, REAL and DOUBLE PRECISION
• NUMERIC(precision, scale) or DECIMAL(precision, scale)
• DECFLOAT(precision)

For example, the number 123.45 has a precision of 5 and a scale of 2. The precision is a positive integer that determines the number of significant digits in a particular radix (binary or decimal). The scale is a non-negative integer. A scale of 0 indicates that the number is an integer. For a decimal number with scale S, the exact numeric value is the integer value of the significant digits divided by 10^S.

SQL provides the functions CEILING and FLOOR to round numerical values. (Popular vendor specific functions are TRUNC (Informix, DB2, PostgreSQL, Oracle and MySQL) and ROUND (Informix, SQLite, Sybase, Oracle, PostgreSQL, Microsoft SQL Server and Mimer SQL.))

Temporal (datetime)

• DATE: for date values (e.g. 2011-05-03)
• TIME: for time values (e.g. 15:51:36).
• TIME WITH TIME ZONE: the same as TIME, but including details about the time zone in question.
• TIMESTAMP: This is a DATE and a TIME put together in one variable (e.g. 2011-05-03 15:51:36.123456).
• TIMESTAMP WITH TIME ZONE: the same as TIMESTAMP, but including details about the time zone in question.

The SQL function EXTRACT can be used for extracting a single field (seconds, for instance) of a datetime or interval value. The current system date / time of the database server can be called by using functions like CURRENT_DATE, CURRENT_TIMESTAMP, LOCALTIME, or LOCALTIMESTAMP. (Popular vendor specific functions are TO_DATE, TO_TIME, TO_TIMESTAMP, YEAR, MONTH, DAY, HOUR, MINUTE, SECOND, DAYOFYEAR, DAYOFMONTH and DAYOFWEEK.)

Interval (datetime)

• YEAR(precision): a number of years
• YEAR(precision) TO MONTH: a number of years and months
• MONTH(precision): a number of months
• DAY(precision): a number of days
• DAY(precision) TO HOUR: a number of days and hours
• DAY(precision) TO MINUTE: a number of days, hours and minutes
• DAY(precision) TO SECOND(scale): a number of days, hours, minutes and seconds
• HOUR(precision): a number of hours
• HOUR(precision) TO MINUTE: a number of hours and minutes
• HOUR(precision) TO SECOND(scale): a number of hours, minutes and seconds
• MINUTE(precision): a number of minutes
• MINUTE(precision) TO SECOND(scale): a number of minutes and seconds

Data control

The Data Control Language (DCL) authorizes 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.

Example:

GRANT SELECT, UPDATE
 ON example
 TO some_user, another_user;
REVOKE SELECT, UPDATE
ON example
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 programming language, not an imperative programming language like C or BASIC. However, extensions to Standard SQL add procedural programming language functionality, such as control-of-flow constructs. These include:

Source	Abbreviation	Full name
ANSI/ISO Standard	SQL/PSM	SQL/Persistent Stored Modules
Interbase / Firebird	PSQL	Procedural SQL
IBM DB2	SQL PL	SQL Procedural Language (implements SQL/PSM)
IBM Informix	SPL	Stored Procedural Language
IBM Netezza	NZPLSQL	(based on Postgres PL/pgSQL)
Invantive	PSQL	Invantive Procedural SQL (implements SQL/PSM and PL/SQL)
MariaDB	SQL/PSM, PL/SQL	SQL/Persistent Stored Module (implements SQL/PSM), Procedural Language/SQL (based on Ada)
Microsoft / Sybase	T-SQL	Transact-SQL
Mimer SQL	SQL/PSM	SQL/Persistent Stored Module (implements SQL/PSM)
MySQL	SQL/PSM	SQL/Persistent Stored Module (implements SQL/PSM)
MonetDB	SQL/PSM	SQL/Persistent Stored Module (implements SQL/PSM)
NuoDB	SSP	Starkey Stored Procedures
Oracle	PL/SQL	Procedural Language/SQL (based on Ada)
PostgreSQL	PL/pgSQL	Procedural Language/PostgreSQL Structured Query Language (implements SQL/PSM)
SAP R/3	ABAP	Advanced Business Application Programming
SAP HANA	SQLScript	SQLScript
Sybase	Watcom-SQL	SQL Anywhere Watcom-SQL Dialect
Teradata	SPL	Stored Procedural Language

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. Microsoft 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 unmanaged extended stored procedures primarily written in C. PostgreSQL lets users write functions in a wide variety of languages—including Perl, Python, Tcl, JavaScript (PL/V8) and C.

Interoperability and standardization

SQL implementations are incompatible between vendors and do not necessarily completely follow standards. In particular date and time syntax, string concatenation, NULLs, and comparison case sensitivity vary from vendor to vendor. Particular exceptions are PostgreSQL and Mimer SQL which strive for standards compliance, though PostgreSQL does not adhere to the standard in how folding of unquoted names is done. The folding of unquoted names to lower case in PostgreSQL is incompatible with the SQL standard, which says that unquoted names should be folded to upper case. Thus, Foo should be equivalent to FOO not foo according to the standard.

Popular implementations of SQL commonly omit support for basic features of Standard SQL, such as the DATE or TIME data types. The most obvious such examples, and incidentally the most popular commercial and proprietary SQL DBMSs, are Oracle (whose DATE behaves as DATETIME, and lacks a TIME type) and MS SQL Server (before the 2008 version). 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 newer version of the SQL standard conflicts with the prior behavior of the vendor's database, the vendor may be unwilling to break backward compatibility.
• There is little commercial incentive for vendors to make it easier for users to change database suppliers.
• Users evaluating database software tend to place other factors such as performance higher in their priorities than standards conformance.

SQL was adopted as a standard by the American National Standards Institute (ANSI) in 1986 as SQL-86 and the International Organization for Standardization (ISO) in 1987. It is maintained by ISO/IEC JTC 1, Information technology, Subcommittee SC 32, Data management and interchange. The standard is commonly denoted by the pattern: ISO/IEC 9075-n:yyyy Part n: title, or, as a shortcut, ISO/IEC 9075.

ISO/IEC 9075 is complemented by ISO/IEC 13249: SQL Multimedia and Application Packages (SQL/MM), which defines SQL based interfaces and packages to widely spread applications like video, audio and spatial data.

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.

The original standard declared that the official pronunciation for "SQL" was an initialism: /ˌɛsˌkjuːˈɛl/ ("ess cue el"). Regardless, many English-speaking database professionals (including Donald Chamberlin himself) use the acronym-like pronunciation of /ˈsiːkwəl/ ("sequel"), mirroring the language's pre-release development name of "SEQUEL". The SQL standard has gone through a number of revisions:

Year	Name	Alias	Comments
1986	SQL-86	SQL-87	First formalized by ANSI.
1989	SQL-89	FIPS 127-1	Minor revision that added integrity constraints, 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 (e.g. transitive closure), triggers, support for procedural and control-of-flow statements, non-scalar types (arrays), and some object-oriented features (e.g. structured types). Support for embedding SQL in Java (SQL/OLB) and vice versa (SQL/JRT).
2003	SQL:2003		Introduced XML-related features (SQL/XML), window functions, standardized sequences, and columns with auto-generated values (including identity-columns).
2006	SQL:2006		ISO/IEC 9075-14:2006 defines ways that SQL can be used 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 lets applications integrate queries into their SQL code with 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, TRUNCATE statement, FETCH clause.
2011	SQL:2011		Adds temporal data (PERIOD FOR) (more information at: Temporal database#History). Enhancements for window functions and FETCH clause.
2016	SQL:2016		Adds row pattern matching, polymorphic table functions, JSON.
2019	SQL:2019		Adds Part 15, multidimensional arrays (MDarray type and operators).

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

The SQL standard is divided into ten parts. There are gaps in the numbering due to the withdrawal of outdated parts.

• ISO/IEC 9075-1:2016 Part 1: Framework (SQL/Framework). It provides logical concepts.
• ISO/IEC 9075-2:2016 Part 2: Foundation (SQL/Foundation). It contains the most central elements of the language and consists of both mandatory and optional features.
• ISO/IEC 9075-3:2016 Part 3: Call-Level Interface (SQL/CLI). It defines interfacing components (structures, procedures, variable bindings) that can be used to execute SQL statements from applications written in Ada, C respectively C++, COBOL, Fortran, MUMPS, Pascal or PL/I. (For Java see part 10.) 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.
• ISO/IEC 9075-4:2016 Part 4: Persistent stored modules (SQL/PSM). It 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.
• ISO/IEC 9075-9:2016 Part 9: Management of External Data (SQL/MED). It 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.
• ISO/IEC 9075-10:2016 Part 10: Object language bindings (SQL/OLB). It defines the syntax and semantics of SQLJ, which is SQL embedded in Java (see also part 3). 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. Unlike SQL/OLB JDBC defines an API and is not part of the SQL standard.
• ISO/IEC 9075-11:2016 Part 11: Information and definition schemas (SQL/Schemata). It 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.^[41] This part of the standard contains both mandatory and optional features.
• ISO/IEC 9075-13:2016 Part 13: SQL Routines and types using the Java TM programming language (SQL/JRT). It specifies the ability to invoke static Java methods as routines from within SQL applications ('Java-in-the-database'). 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.
• ISO/IEC 9075-14:2016 Part 14: XML-Related Specifications (SQL/XML). It 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.
• ISO/IEC 9075-15:2019 Part 15: Multi-dimensional arrays (SQL/MDA). It specifies a multidimensional array type (MDarray) for SQL, along with operations on MDarrays, MDarray slices, MDarray cells, and related features. This part of the standard consists solely of optional features.

ISO/IEC 9075 is complemented by ISO/IEC 13249 SQL Multimedia and Application Packages. This closely related but separate standard is developed by the same committee. It defines interfaces and packages based on SQL. The aim is a unified access to typical database applications like text, pictures, data mining or spatial data.

• ISO/IEC 13249-1:2016 Part 1: Framework
• ISO/IEC 13249-2:2003 Part 2: Full-Text
• ISO/IEC 13249-3:2016 Part 3: Spatial
• ISO/IEC 13249-5:2003 Part 5: Still image
• ISO/IEC 13249-6:2006 Part 6: Data mining
• ISO/IEC 13249-7:2013 Part 7: History
• ISO/IEC 13249-8:xxxx Part 8: Metadata Registry Access MRA (work in progress)

ISO/IEC 9075 is also accompanied by a series of Technical Reports, published as ISO/IEC TR 19075 in 8 parts. These Technical Reports explain the justification for and usage of some features of SQL, giving examples where appropriate. The Technical Reports are non-normative; if there is any discrepancy from 9075, the text in 9075 holds. Currently available 19075 Technical Reports are:

• ISO/IEC TR 19075-1:2011 Part 1: XQuery Regular Expression Support in SQL
• ISO/IEC TR 19075-2:2015 Part 2: SQL Support for Time-Related Information
• ISO/IEC TR 19075-3:2015 Part 3: SQL Embedded in Programs using the Java^TM programming language
• ISO/IEC TR 19075-4:2015 Part 4: SQL with Routines and types using the Java^TM programming language
• ISO/IEC TR 19075-5:2016 Part 5: Row Pattern Recognition in SQL
• ISO/IEC TR 19075-6:2017 Part 6: SQL support for Javascript Object Notation (JSON)
• ISO/IEC TR 19075-7:2017 Part 7: Polymorphic table functions in SQL
• ISO/IEC TR 19075-8:2019 Part 8: Multi-Dimensional Arrays (SQL/MDA)

Alternatives

A distinction should be made between alternatives to SQL as a language, and alternatives to the relational model itself. Below are proposed relational alternatives to the SQL language. See navigational database and NoSQL for alternatives to the relational model.

• .QL: object-oriented Datalog
• 4D Query Language (4D QL)
• Datalog: critics suggest that Datalog has two advantages over SQL: it has cleaner semantics, which facilitates program understanding and maintenance, and it is more expressive, in particular for recursive queries.
• HTSQL: URL based query method
• IBM Business System 12 (IBM BS12): one of the first fully relational database management systems, introduced in 1982
• ISBL
• jOOQ: SQL implemented in Java as an internal domain-specific language
• Java Persistence Query Language (JPQL): The query language used by the Java Persistence API and Hibernate persistence library
• JavaScript: MongoDB implements its query language in a JavaScript API.
• LINQ: Runs SQL statements written like language constructs to query collections directly from inside .Net code.
• Object Query Language
• QBE (Query By Example) created by Moshè Zloof, IBM 1977
• Quel introduced in 1974 by the U.C. Berkeley Ingres project.
• Tutorial D
• XQuery

Distributed SQL processing

Distributed Relational Database Architecture (DRDA) was designed by a work group within IBM in the period 1988 to 1994. DRDA enables network connected relational databases to cooperate to fulfill SQL requests.

An interactive user or program can issue SQL statements to a local RDB and receive tables of data and status indicators in reply from remote RDBs. SQL statements can also be compiled and stored in remote RDBs as packages and then invoked by package name. This is important for the efficient operation of application programs that issue complex, high-frequency queries. It is especially important when the tables to be accessed are located in remote systems.

The messages, protocols, and structural components of DRDA are defined by the Distributed Data Management Architecture.

Criticisms

Chamberlin's 2012 paper discusses four historical criticisms of SQL:

Orthogonality and completeness

Early specifications did not support major features, such as primary keys. Result sets could not be named, and sub-queries had not been defined. These were added in 1992.

NULLs

SQL's controversial "NULL" and three-value logic. Predicates evaluated over nulls return the logical value of "unknown" rather than true or false. Features such as outer-join depend on nulls. Null is not equivalent to space. NULLS are not equal to another NULL. NULL represents no data in the column, or row.

Duplicates

Another popular criticism is that it allows duplicate rows, making integration with languages such as Python, whose data types might make it difficult to accurately represent the data, difficult in terms of parsing and by the absence of modularity.

This can be avoided declaring a unique constraint with one or more fields that identifies uniquely a row in the table. That constraint could also become the primary key of the table.

Impedance mismatch

In a similar sense to Object-relational impedance mismatch, there is a mismatch between the declarative SQL language and the procedural languages that SQL is typically embedded in.

• SQL Cheat Sheet
• Introduction to SQL
• SQL Server Interview Questions
• SQL videos
• SQL Quiz
• SQL Exercises

Books

• Data Science with Microsoft SQL Server 2016
• Learning SQL
• Programming Microsoft SQL Server 2012
• Healthy SQL: A Comprehensive Guide to Healthy SQL Server Performance
• Joe Celko's SQL for Smarties
• Learn SQL Server Administration in a Month of Lunches
• Mastering Oracle SQL and SQL*Plus
• Mastering SQL Queries for SAP Business One
• Microsoft SQL Server 2012 Bible
• Practical SQL: A Beginner's Guide to Storytelling with Data
• Pro SQL Server on Linux
• Real World SQL and PL/SQL
• Sams Teach Yourself Microsoft SQL Server T-SQL in 10 Minutes
• Sams Teach Yourself Oracle PL/SQL in 10 Minutes
• SQL For Dummies, 9th Edition
• SQL For Dummies, 8th Edition
• SQL in a Nutshell
• SQL Primer: An Accelerated Introduction to SQL Basics
• SQL Server 2017 Integration Services Cookbook
• SQL Server Interview Questions and Answers
• Microsoft SQL Server 2012 T-SQL Fundamentals
• SQL Stored Procedures and Embedded SQL
• SQL: Visual QuickStart Guide
• SQL: A Beginner's Guide
• SQL: Easy SQL Programming and Database Management For Beginners. Your Step-By- Step Guide To Learning The SQL Database
• SQL: with practice exercises, Learn SQL Fast
• SQL Injection Attacks and Defense
• SQL: The Complete Reference
• Microsoft course 2778, Writing Queries Using Microsoft SQL Server 2008 Transact-SQL
• SQL Practice Problems
• A guide to the SQL standard
• SQL Queries for Mere Mortals
• Oracle PL/SQL Language Pocket Reference
• Beginning SQL Server Modeling
• Pro SQL Database for Windows Azure
• PySpark SQL Recipes: With HiveQL, Dataframe and Graphframes
• Effective SQL
• SQL Anywhere Server SQL Reference
• Microsoft SQL Server 2008 Bible
• Mastering PostgreSQL 10
• Microsoft SQL Server 2005 Analysis Services
• SQL Server 2005 DBA Street Smarts: A Real World Guide to SQL Server 2005 Certification Skills
• Microsoft SQL Server 2012 Transact-SQL DML Reference
• SQL Server Query Performance Tuning
• SQL: Access to SOL Server
• SQL++ For SQL Users: A Tutorial
• Tabular Modeling with SQL Server 2016 Analysis Services Cookbook
• The Art of SQL
• What's New in SQL Server 2012: Unleash the new features of SQL Server 2012
• Advanced Transact SQL for SQL Server 2000
• Complete Microsoft SQL Server: Tips and Secrets for Professionals
• SQL Query for SQL Server User's Manual
• SQL for MySQL Developers
• SQL: Pocket Guide
• SQL Server Backup and Restore
• A Developer's Guide to Data Modeling for SQL Server