SQL

structured query language

WordNet

1. the 19th letter of the Roman alphabet (同)s

PrepTutorEJDIC

1. sulfurの化学記号 / {略}South[ern]

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出典(authority):フリー百科事典『ウィキペディア（Wikipedia）』「2016/04/08 21:38:10」(JST)

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SQL（エスキューエルⁱ[ˈɛs kjuː ˈɛl]、シークェルⁱ[ˈsiːkwəl]、シーケル）は、リレーショナルデータベース管理システム (RDBMS) において、データの操作や定義を行うためのデータベース言語（問い合わせ言語）である。エドガー・F・コッドによって考案されたリレーショナルデータベースの関係モデル（リレーショナルモデル）における演算体系である、関係代数と関係論理（関係計算）にある程度基づいている。 データベース言語の国際標準としてのSQLは何かの略語ではない。

SQLは、シークェル [ˈsiːkwəl] と読まれることもある。これは、SQLの元となったデータベース言語が、IBM社が開発したRDBMSの実験実装である System R の操作言語「SEQUEL (Structured English Query Language)」であったことが由来である。

SQLに対しては、関係代数と関係論理に忠実に準拠していないとして批判する意見がある（The Third Manifesto - クリス・デイト、ヒュー・ダーウェン）。

標準SQL規格

当初は特に統一標準規格が存在しない状況で、各リレーショナルデータベース管理システム (RDBMS) ベンダーごとにさまざまな拡張がなされてきた。 近年になってANSI、後にISOで言語仕様の標準化が行われており、制定された年ごとにSQL86, SQL89, SQL92, SQL:1999, SQL:2003, SQL:2006, SQL:2008, SQL:2011 などの規格があるが、対応の程度はベンダーごとにバラバラである。これは標準SQL策定に時間がかかりすぎたことにより、ビジネスの現状から早期の機能拡張が迫られたベンダーの都合と、独自構文を頻繁に利用していたユーザに対し、互換性保持を保証する必要もあったためである。

SQL規格は非常に多くの改正が行われた。制定年度順に代表的な規格を以下に挙げる。

年	規格名称	別称	説明
1986	SQL86	SQL87	ANSIによって発表された最初の規約。1987年にISOによって批准された。 データ操作言語 (DML) 仕様策定: COBOL、FORTRAN、PL/Iなど、親言語（母言語、ホスト言語とも言う）への埋込みSQL文仕様策定
1989	SQL89		マイナーバージョン。 データ定義言語 (DDL) 仕様策定 （CREATE TABLE文、CREATE VIEW文、GRANT文。ただし、DROP文、ALTER文、REVOKE文はなし） 制約および整合性機能を追加 （DEFAULT、UNIQUE制約、NOT NULL制約、PRIMARY KEY制約、CHECK制約、参照整合性制約） C言語への埋込みSQL文仕様の追加
1992	SQL92	SQL2	メジャーバージョン 直交性の改善 （表式） データ型の拡張 （可変長文字列、ビット、文字集合、日付・時刻・時間間隔 (DATE, TIME, TIMESTAMP, INTERVAL)） 外部結合 (OUTER JOIN) 定義域 (DOMAIN) 表明 (ASSERTION) 一時表 （TEMPORARY TABLE: 永続化しないデータを格納） DDL仕様追加 （DROP文、ALTER文） 動的SQL仕様 前方・後方スクロール可能なカーソルサポート クライアント/サーバシステムのためのCONNECT/DISCONNECT文
1995	SQL/CLI		コールレベルインターフェース (Call Level Interface) 業界標準になった ODBC API のインタフェースに相当する機能を国際標準化した規格
1996	SQL/PSM		永続格納モジュール (Persistent Storage Module) 一般的にストアドプロシージャと呼ばれる機能を国際標準化した規格
1999	SQL:1999 (SQL99)	SQL3	RDBMSのための完全な言語になることを目指した仕様。 正規表現による値照合 共通表式(WITH句) 再帰クエリ OLAP (ROLLUP、CUBE、GROUPING SETS) ユニオン (UNION)・結合経由の更新 カーソル操作の機能強化 （トランザクション完了後のオープン状態保持）・ユーザ定義権限 (ROLE)・トランザクション管理の新機能 (SAVEPOINT) SQL/PSM強化 （制御構文 （IF、WHILEなど） サポートなど） SQLJ （Javaを親言語とする埋め込みSQL規格） データベーストリガ ユーザ定義関数 （ストアドファンクション） 非スカラー型の新しいデータ型: 真理値 (BOOLEAN) 型と配列 (ARRAY) 型、LOB (Large Object)、ユーザ定義型、構造型 上位表と下位表 （スーパーテーブルとサブテーブル） オブジェクト指向の考え方を取り入れたオブジェクトリレーショナルデータベース技術 (ORDB)。配列型やユーザ定義型、ユーザ定義関数と上位表/下位表仕様により実現されている。
2003	SQL:2003		SQL/MM （マルチメディア: フレームワーク、全文検索、空間データ (Spatial)、静止画像） SQL/MED （外部データ管理: 非リレーショナルデータ （順編成ファイルや階層型データベースなど） や他社のリレーショナルデータをSQLでアクセスするための規格） SQL/OLB （オブジェクト言語バインディング: SQLJを標準化する。Javaプログラムに埋め込むSQL文） XML関連の機能 ウィンドウ関数 順序（シーケンス）の標準化と識別キー列に対する値の自動生成を行う列仕様の導入 （ID型） (See Eisenberg et al.: SQL:2003 Has Been Published.)
2008	SQL:2008		INSTEAD OF トリガ TRUNCATE TABLE ステートメント 配列型の集約と展開 (array_agg, unnest)

SQLとオンライン処理

当初はリレーショナルデータベース管理システム (RDBMS) に端末から直接命令を発行することを想定していたため、制御文法の仕様が存在しなかった。このため、SQLは「宣言型プログラミング言語」と分類される。これに対し、COBOLやC言語などは「手続き型プログラミング言語」と分類される。

その後、手続き型プログラミング言語（母言語）からリレーショナルデータベースへのアクセスを行えるようにするため、母言語のソースコードにSQL文を記述し、プリプロセッサによってSQL部分を母言語のソースコードに変換してデータベースアプリケーションを開発する方式が普及した。これを「埋め込みSQL」(Embedded SQL/ESQL) と呼び、後にANSIにより仕様が標準化された。

暫くの間、データベースアプリケーションは、RDBMSベンダーが製品に同封したユーティリティや埋め込みSQLにより開発されてきたが、マイクロソフト社がC言語からAPIレベルで統一したソースコードを記述し、クライアント・サーバ型アプリケーションシステムの構築に有用である仕組み「Open Database Connectivity」(ODBC) を発表し、その有用性からANSIではODBC仕様を参考に「SQL/CLI」という仕様を標準化した。

SQLとバッチ処理

埋め込みSQLやODBCの普及により、オンライントランザクション処理向きのSQLアクセス方法は確立されたが、バッチ処理性能向上の必要性が求められるようになった。

ある表 (テーブル)の内容を編集して別の表に格納する大量データの更新処理などをデータベースエンジン内部で処理プログラムを実行し、入出力 (I/O) のほとんどをデータベース内部で完結することにより、クライアント側とのデータ通信によるオーバヘッドを削減することでバッチ処理性能を向上させる「ストアドプロシージャ」が考え出された。

ストアドプロシージャは、同じくデータベース内部に定義し、データベースに発生したイベントの内容に応じて任意の処理を実行する機能である「データベーストリガ」とともに、標準SQL仕様に採用され、SQL:1999 (SQL99) 規格の永続格納モジュール (SQL/PSM) として標準化された。

しかし、標準化される以前から各リレーショナルデータベース管理システム (RDBMS) ベンダーがデータベースエンジン内部で制御文法を記述し実行できるように独自の拡張が行われていたため、ストアドプロシージャの処理ロジック記述文法はそれ以前に標準化されたSQL文法と比較して著しい非互換が認められるため、アプリケーションソフトウェアの移植性・開発生産性・保守性を損なう場合がある。

標準SQLのSQL/PSMを採用したRDBMSを以下に挙げる。これらは概ね仕様に準拠しているが、仕様に定められていない部分や実装上の理由により細部には違いがある。

• SQL/PSM (DB2, MySQL)

各RDBMSベンダーによる標準以外の独自のプロシージャには以下のようなものがある。これらには、独自追加された制御構文だけでなく、命令やデータ型の非互換も含むため注意が必要である。

• PL/SQL (Oracle, DB2)
• Transact-SQL (Adaptive Server Enterprise, Microsoft SQL Server)
• PL/pgSQL (PostgreSQL)
• PSQL (Firebird, InterBase)

SQLの対話的実行

SQLを対話的に実行する場合、リレーショナルデータベース管理システム (RDBMS) に付属するコマンドラインタイプのアクセスユーティリティを利用するのが一般的である。SQL文を記述したテキストファイルをスクリプトとして実行し、バッチ的に実行することが可能なものもあり、広く利用されている。RDBMSごとに、そのユーティリティ固有の命令を備えているものもあるため、データベースを扱うアプリケーションソフトウェア開発の初心者はその命令もデータベースエンジンが解釈するSQL文法のひとつであると間違って覚えてしまい、ODBCやJDBCなどAPIからSQLを実行したときのエラーの原因が理解できずに混乱することもある。

ユーティリティ固有の文法で誤解しやすいものには、データベースでSQL文の文末に指定する文字である。全データベース共通では「;」、Oracle Database の ユーティリティであるSQL*Plusで、ストアドプロシージャの定義や無名PL/SQLブロックを発行するときに文末行に指定する「/」 や、Sybase/SQL Serverのisql/osqlではすべてのSQL文の文末行に指定する「GO」などがある。このなかでもっとも間違えやすいのが「;」である。これは、一般的なSQL教科書でも構文の終端文字として例が記載されているが、標準SQLの構文の終端文字ではない。

SQL文法

コマンド種別

データベース言語SQLの文法の種別は、以下の3つに大別される。

• データ定義言語 (DDL: Data Definition Language)
• データ操作言語 (DML: Data Manipulation Language)
• データ制御言語 (DCL: Data Control Language)

その他に、これらの命令の適用範囲を補完するための機能として、SQL文を実行時に解釈する「動的SQL」や、埋め込みSQLのための命令などが用意されている。 リレーショナルデータベース管理システム (RDBMS) 以前のデータベース管理システム (DBMS) では、これらは必ずしも同一の言語ではなかった。データ定義言語は存在せずにすべて専用のコマンドにパラメタを指定して実行する実装も存在した。

コマンド文法

データ定義言語

「データ定義言語」も参照

• CREATE （データベースオブジェクト（表、インデックス、制約など）の定義）
• DROP （データベースオブジェクトの削除）
• ALTER （データベースオブジェクトの定義変更）

データ操作言語

「データ操作言語」も参照

• INSERT INTO （行データもしくは表データの挿入）
• UPDATE 〜 SET （表を更新）
• DELETE FROM （表から特定行の削除）
• SELECT 〜 FROM 〜 WHERE （表データの検索、結果集合の取り出し）
  • 後述する「動的SQL」でのSELECT文には、一度の実行で1行の結果を取得する「単一行SELECT文」と、カーソルにより複数行の結果を取得する「カーソルSELECT文」がある。

列名と値を、対で指定

INSERT INTO 表名(列名1,列名2) VALUES(値1,値2)

表を構成するすべての列に値を格納する場合は、列名の記述を省略可能

INSERT INTO 表名 VALUES (値1, 値2)

他表のデータを検索して格納

INSERT INTO 表名1 SELECT 列名1, 列名2 FROM 表名2 〜

更新

UPDATE 表名
 SET 列名2=値2, 列名3=値3
 WHERE 列名1=値1

削除

DELETE FROM 表名
 WHERE 列名1=値1

1行以上の検索

SELECT *
 FROM 表名
 WHERE 列名1 BETWEEN 値1 AND 値2
 ORDER BY 列名1

1行だけの検索

SELECT *
 INTO 受け取り変数 
 FROM 表名
 WHERE 列名1=値1

データ制御言語

「データ制御言語」も参照

• GRANT （特定のデータベース利用者に特定の作業を行う権限を与える）
• REVOKE （特定のデータベース利用者からすでに与えた権限を剥奪する）
• SET TRANSACTION （トランザクションモードの設定（並行トランザクションの分離レベル (ISOLATION MODE) など））
• BEGIN （トランザクションの開始）
• COMMIT （トランザクションの確定）
• ROLLBACK （トランザクションの取り消し）
• SAVEPOINT （任意にロールバック地点を設定する）
• LOCK （表などの資源を占有する）

カーソル定義・操作

「カーソル」とは、SELECT文などによるデータベース検索による検索実行の結果を1行ずつ取得して処理するために、データベースサーバ側にある結果集合と行取得位置を示す概念をいう。 カーソルの定義とその操作は、主にアプリケーションプログラムなどの手続き型言語からのSQL実行において利用する。

• DECLARE CURSOR （カーソル定義）
• OPEN （カーソルのオープン）
• FETCH （カーソルのポインタが指し示す位置の行データを取得し、ポインタを一行分進める。）
• UPDATE （カーソルのポインタが指し示す位置の行データを更新する）
• DELETE （カーソルのポインタが指し示す位置の行データを削除する）
• CLOSE （カーソルのクローズ）

カーソル宣言例

DECLARE CR1 CURSOR FOR
 SELECT CLMA, CLMB, CLMC
  FROM TBL1
  WHERE CLMA BETWEEN :V開始値 AND :V終了値

※V開始値、V終了値は、埋め込み変数あるいはホスト変数と呼ばれ、埋め込みSQLの場合は、プログラム中のBEGIN DECLARE SECTION〜END DECLARE SECTIONの間で宣言する。

カーソルのオープン例

OPEN CR1

※カーソルのオープン前に、V開始値、V終了値には値を設定しておく。

行の取り出し例

FETCH CR1 INTO :V列A, :V列B, :V列C

検索条件に合致した行をすべて取り出すには、「データなし」になるまでFETCHを繰り返す。

※V列A, :V列B, :V列C は、埋め込み変数あるいはホスト変数と呼ばれ、埋め込みSQLの場合は、プログラム中のBEGIN DECLARE SECTION〜END DECLARE SECTIONの間で宣言する。

取り出した行の更新例

UPDATE TBL1
 SET CLMB=CLMB+1, CLMC=:V列C更新値
 WHERE CURRENT OF CR1

FETCHで位置付けた行を更新するには、UPDATE文でWHERE CURRENT OF カーソル名を指定する。

※V列C更新値は、埋め込み変数あるいはホスト変数と呼ばれ、埋め込みSQLの場合は、プログラム中のBEGIN DECLARE SECTION〜END DECLARE SECTIONの間で宣言する。

取り出した行の削除例

DELETE FROM TBL1
 WHERE CURRENT OF CR1

FETCHで位置付けた行を削除するには、DELETE文でWHERE CURRENT OF カーソル名を指定する。

カーソルのクローズ例

CLOSE CR1

動的SQL

動的SQLは、通常SQL文をRDBMSに対して送信の度にデータベースエンジンで実行可能な内部中間コードに翻訳する作業を事前に行うことによって、翻訳済みSQLコードを再度利用してSQL解析のオーバーヘッドを削減することと、SQL文をソースコードで固定せずにデータベースへのアクセス毎に構文を書き換えたい場合に、有用である。データ操作言語 (DML) ももちろん実行できるが、データ定義言語 (DDL) のようにデータベース製品の機能アップによって新しい命令が追加されるものは、プリプロセッサの対応作業が重荷になるため、ほとんどのデータベース製品ではDDL文は動的SQLにて実行することが一般的となっている。

• PREPARE （文字列で与えたSQL文を解析・翻訳する）
• EXECUTE （PREPAREで翻訳したSQL文を実行する）

パラメタなし
PREPARE PRESQL FROM 'DELETE FROM TBL1 WHERE CLMA=1'
  ↓
EXECUTE PRESQL

パラメタあり（1回のPREPAREで、EXECUTEの繰り返し実行が可能）
PREPARE PRESQL FROM 'DELETE FROM TBL1 WHERE CLMA=? AND CLMB=?'
　↓
EXECUTE PRESQL USING :XCLMA,:XCLMB

埋め込みSQL

もともとカーソルは、埋め込みSQLでホスト言語（母言語）から結果集合を取得するために、都合のよい方法として考えられたものである。データベースと通信するためのリソースの割り当て確保や開放、1行ごとにホスト言語のループ処理で取得するための命令 (FETCH) などがある。

• ALLOCATE (DEALLOCATE) DESCRIPTOR　（データベースとホスト言語（母言語）間での通信領域の確保と開放。）
• WHENEVER （エラー発生時の振る舞いを定義）
• SQLSTATE （SQL文実行後の状態が保存される領域）

EXEC SQL INCLUDE SQLCA         END-EXEC.
EXEC SQL BEGIN DECLARE SECTION END-EXEC.
77  XPARM              PIC X(3).
01  XTBL1.
  03  XCLMA            PIC X(3).
  03  XCLMB            PIC X(10). 
01  XTBL2.
  03  XCLM1            PIC S9(5) COMP-3.
  03  XCLM2            PIC S9(9) COMP.
EXEC SQL END   DECLARE SECTION END-EXEC.

    EXEC SQL
     DECLARE CR1 CURSOR FOR
      SELECT CLMA, CLMB FROM TBL1
       WHERE CLMA>=:XPARM
       ORDER BY CLMA
    END-EXEC.

    EXEC SQL WHENEVER SQLERROR GO TO ERR--PROC END-EXEC.

*   SQLの静的実行（カーソル操作例）
    MOVE  'ABC'    TO  XPARM.
    EXEC SQL OPEN CR1          END-EXEC.
    PERFORM TEST BEFORE
     UNTIL SQLCODE NOT = ZERO 
      EXEC SQL
       FETCH CR1 INTO :XCLMA, :XCLMB 
      END-EXEC
      IF SQLCODE = ZERO
       データ検索時の処理
       END-IF
    END-PERFORM.
    IF SQLCODE = 100
     EXEC SQL CLOSE CR1          END-EXEC
    END-EXEC.
*   SQLの動的実行（？パラメタ使用）
    EXEC SQL
     PREPARE PRESQL FROM
      'INSERT INTO TBL2 (CLM1, CLM2) VALUES(?, ?)'
    END-EXEC.
    MOVE ZERO       TO  XCLM2.
    PERFORM TEST AFTER
     VARYING XCLM1 FROM 1 BY 1
     UNTIL XCLM1 >= 10
      EXEC SQL
       EXECUTE PRESQL USING :XCLM1, :XCLM2
      END-EXEC
    END-PERFORM.
    GOBACK.
ERR--PROC.
    例外処理

3値論理

SQLで用いられる論理値は、コンピュータの世界でもっとも広く利用されている2値論理 (TRUE, FALSE) ではなく、3値論理 (TRUE, FALSE, UNKNOWN) となっている。

主な SQL DBMS 実装

• Ingres（オープンソース、UNIX、Linux、Windows、Mac OS対応）
• Oracle Database（プロプライエタリ、UNIX、Linux、Windows対応）
• SQL/DS (VSE, VM/CMS)
• IBM DB2 (プロプライエタリ、AS/400、z/OS、UNIX、Linux、Windows対応）
• IBM Informix Dynamic Server（プロプライエタリ、UNIX、Linux、Windows対応）
• Sybase Adaptive Server Enterprise（プロプライエタリ、UNIX、Linux、Windows対応）
• Microsoft SQL Server（プロプライエタリ、Windows対応）
• PostgreSQL（オープンソース、UNIX、Linux、Windows対応）
• MySQL（オープンソース、UNIX、Linux、Windows対応）
• InterBase（プロプライエタリ、Linux、Windows、Solaris、Mac OS X 対応）
• Firebird（オープンソース、Linux、Windows、Mac OS X 、Solaris、HP-UX対応）
• SQLite（オープンソース(パブリックドメイン)、標準のC言語で実装されており再コンパイルであらゆる環境に対応）

関連項目

• 関係モデル (リレーショナルモデル)
  • 関係代数 (関係モデル)
  • 関係論理
• SQLインジェクション

脚注

wiki en

[Wiki en表示]

This article is about the database language. For the IATA code, see San Carlos Airport (California).

SQL

Paradigm	Multi-paradigm: declarative, procedural
Designed by	Donald D. Chamberlin Raymond F. Boyce
Developer	ISO/IEC
First appeared	1974
Stable release	SQL:2011 / 2011
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 (1986)
Latest release	SQL:2011 (2011 (2011))
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
Influenced by
Datalog
Influenced
CQL, LINQ, SOQL, Windows PowerShell, JPQL, jOOQ

SQL (ⁱ/ˈɛs kjuː ˈɛl/, or ⁱ/ˈsiːkwəl/; Structured Query Language) is a special-purpose programming language designed for managing data held in a relational database management system (RDBMS), or for stream processing in a relational data stream management system (RDSMS).

Originally based upon relational algebra and tuple relational calculus, SQL consists of a data definition language, data manipulation language, and a data control language. The scope of SQL includes data insert, query, update and delete, schema creation and modification, and data access control. Although SQL is often described as, and to a great extent is, a declarative language (4GL), it also includes procedural elements.

SQL was one of the first commercial languages for Edgar F. Codd's relational model, as 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, though, most SQL code is not completely portable among different database systems without adjustments.

History

SQL was initially developed at IBM by Donald D. Chamberlin and Raymond F. Boyce 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. The acronym SEQUEL was later changed to SQL because "SEQUEL" was a trademark of the UK-based Hawker Siddeley aircraft company.

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 June 1979, Relational Software, Inc. introduced the first commercially available implementation of SQL, Oracle V2 (Version2) for VAX computers.

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.

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 strictly returns to the original foundation: for example, see The Third Manifesto.

Syntax

Language elements

A chart showing several of the SQL language elements that compose a single statement

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	Match a character pattern	First_Name LIKE 'Will%'
IN	Equal to one of multiple possible values	DeptCode IN (101, 103, 209)
IS or IS NOT	Compare to null (missing data)	Address IS NOT NULL
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 field name when viewing results	SELECT employee AS 'department1'

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

SQL has the case/when/then/else/end expression, which was introduced in SQL-92. In its most general form, which is called a "searched case" in the SQL standard, it works like else if in other programming languages:

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" in the SQL standard—mirrors switch statements:

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.

For the Oracle-SQL dialect, the latter can be shortened to an equivalent DECODE construct:

SELECT DECODE(n, 1, 'one',
                 2, 'two',
                    'i cannot count that high')
FROM   some_table;

The last value is the default; if none is specified, it also defaults to NULL. However, unlike the standard's "simple case", Oracle's DECODE considers two NULLs equal with each other.

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 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 named subqueries called common table expressions (named and designed after the IBM DB2 version 2 implementation; Oracle calls these 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.

Inline view

An Inline view is the use of referencing an SQL subquery in a FROM clause. Essentially, the inline view is a subquery that can be selected from or joined to. Inline View functionality allows the user to reference the subquery as a table. The inline view also is referred to as a derived table or a subselect. Inline view functionality was introduced in Oracle 9i.

In the following example, the SQL statement involves a join from the initial Books table to the Inline view "Sales". This inline view captures associated book sales information using the ISBN to join to the Books table. As a result, the inline view 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)

Main article: Null (SQL)

The concept of Null was introduced into SQL to handle 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).

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. In practice, a number of systems (e.g. PostgreSQL) implement the BOOLEAN Unknown as a BOOLEAN NULL.

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

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

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

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

DELETE FROM example
 WHERE field2 = '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 NUMBER(3) 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

• 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

Numbers

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

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 a function to round numerics or dates, called TRUNC (in Informix, DB2, PostgreSQL, Oracle and MySQL) or ROUND (in Informix, SQLite, Sybase, Oracle, PostgreSQL and Microsoft SQL Server)

Temporal (date/time)

• DATE: for date values (e.g. 2011-05-03)
• TIME: for time values (e.g. 15:51:36). The granularity of the time value is usually a tick (100 nanoseconds).
• TIME WITH TIME ZONE or TIMETZ: 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).
• TIMESTAMP WITH TIME ZONE or TIMESTAMPTZ: the same as TIMESTAMP, but including details about the time zone in question.

SQL provides several functions for generating a date / time variable out of a date / time string (TO_DATE, TO_TIME, TO_TIMESTAMP), as well as for extracting the respective members (seconds, for instance) of such variables. The current system date / time of the database server can be called by using functions like NOW. The IBM Informix implementation provides the EXTEND and the FRACTION functions to increase the accuracy of time, for systems requiring sub-second precision.

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	Common name	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 [3]	(based on Postgres PL/pgSQL)
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)
Sybase	Watcom-SQL	SQL Anywhere Watcom-SQL Dialect
Teradata	SPL	Stored Procedural Language
SAP	SAP HANA	SQL Script

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 unmanaged extended stored procedures primarily written in C. PostgreSQL lets users write functions in a wide variety of languages—including Perl, Python, Tcl, 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. A particular exception is PostgreSQL, which strives for standards compliance.

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 (see vendor lock-in).
• 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. Nowadays the standard is subject to continuous improvement by the Joint Technical Committee ISO/IEC JTC 1, Information technology, Subcommittee SC 32, Data management and interchange, which affiliate to ISO as well as IEC. It 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: /ˈɛs kjuː ˈɛl/ ("es queue 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, 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	SQL 2003	Introduced XML-related features (SQL/XML), window functions, standardized sequences, and columns with auto-generated values (including identity-columns).
2006	SQL: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	SQL 2008	Legalizes ORDER BY outside cursor definitions. Adds INSTEAD OF triggers. Adds the TRUNCATE statement.
2011	SQL:2011

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 nine parts.

• ISO/IEC 9075-1:2011 Part 1: Framework (SQL/Framework). It provides logical concepts.
• ISO/IEC 9075-2:2011 Part 2: Foundation (SQL/Foundation). It contains the most central elements of the language and consists of both mandatory and optional features.
• ISO/IEC 9075-3:2008 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 9075-4:2011 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 9075-9:2008 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 9075-10:2008 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, as opposed to SQL/OLB JDBC, which is not part of the SQL standard, which defines an API.
• ISO/IEC 9075-11:2011 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. This part of the standard contains both mandatory and optional features.
• ISO/IEC 9075-13:2008 Part 13: SQL Routines and Types Using the Java 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 9075-14:2011 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 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 13249-1:2007 Part 1: Framework
• ISO/IEC 13249-2:2003 Part 2: Full-Text
• ISO/IEC 13249-3:2011 Part 3: Spatial
• ISO/IEC 13249-5:2003 Part 5: Still image
• ISO/IEC 13249-6:2006 Part 6: Data mining
• ISO/IEC 13249-8:xxxx Part 8: Metadata registries (MDR) (work in progress)

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)
• BQL: a superset that compiles down to SQL
• 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
• 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.

See also

• Comparison of object-relational database management systems
• Comparison of relational database management systems
• D (data language specification)
• D4 (programming language)
• Hierarchical model
• List of relational database management systems
• MUMPS
• NoSQL
• Transact-SQL
• Online analytical processing (OLAP)
• Online transaction processing (OLTP)
• Data warehouse
• relational data stream management system
• Star schema
• Snowflake schema
• DB2 SQL return codes

Notes

References

• Codd, Edgar F (June 1970). "A Relational Model of Data for Large Shared Data Banks". Communications of the ACM 13 (6): 377–87. doi:10.1145/362384.362685. 
• Discussion on alleged SQL flaws (C2 wiki)
• C. J. Date with Hugh Darwen: A Guide to the SQL standard : a users guide to the standard database language SQL, 4th ed., Addison Wesley, USA 1997, ISBN 978-0-201-96426-4

External links

• 1995 SQL Reunion: People, Projects, and Politics, by Paul McJones (ed.): transcript of a reunion meeting devoted to the personal history of relational databases and SQL.
• American National Standards Institute. X3H2 Records, 1978–1995 Charles Babbage Institute Collection documents the H2 committee's development of the NDL and SQL standards.
• Oral history interview with Donald D. Chamberlin Charles Babbage Institute In this oral history Chamberlin recounts his early life, his education at Harvey Mudd College and Stanford University, and his work on relational database technology. Chamberlin was a member of the System R research team and, with Raymond F. Boyce, developed the SQL database language. Chamberlin also briefly discusses his more recent research on XML query languages.
• Comparison of Different SQL Implementations This comparison of various SQL implementations is intended to serve as a guide to those interested in porting SQL code between various RDBMS products, and includes comparisons between SQL:2008, PostgreSQL, DB2, MS SQL Server, MySQL, Oracle, and Informix.
• Event stream processing with SQL - An introduction to real-time processing of streaming data with continuous SQL queries

English Journal

• Sonochemical synthesis of two nanostructured silver(I) coordination polymers based on semi-rigid bis(benzimidazole) ligands.

• Hao SY1, Li YH1, Hao ZC1, Cui GH2.
• Ultrasonics sonochemistry.Ultrason Sonochem.2017 Nov;39:636-644. doi: 10.1016/j.ultsonch.2017.04.008. Epub 2017 Apr 9.
• PMID 28732988

• Hydrogen-bonded structures and interaction energies in two forms of the SGLT-2 inhibitor sotagliflozin.

• Gelbrich T1, Adamer V2, Stefinovic M2, Thaler A2, Griesser UJ1.
• Acta crystallographica. Section C, Structural chemistry.Acta Crystallogr C Struct Chem.2017 Sep 1;73(Pt 9):718-723. doi: 10.1107/S2053229617011603. Epub 2017 Aug 14.
• PMID 28872070

• Graphiti: Interactive Specification of Attribute-based Edges for Network Modeling and Visualization.

• Srinivasan A, Park H, Endert A, Basole RC.
• IEEE transactions on visualization and computer graphics.IEEE Trans Vis Comput Graph.2017 Aug 29. doi: 10.1109/TVCG.2017.2744843. [Epub ahead of print]
• Network visualizations, often in the form of node-link diagrams, are an effective means to understand relationships between entities, discover entities with interesting characteristics, and to identify clusters. While several existing tools allow users to visualize pre-defined networks, creating the
• PMID 28866561

Japanese Journal

• 非線形な潜在曲線モデルを応用したSQLインジェクション攻撃の特徴抽出 (情報論的学習理論と機械学習)

• 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報 115(112), 247-252, 2015-06-23
• NAID 40020525288

• 非線形な潜在曲線モデルを応用したSQLインジェクション攻撃の特徴抽出 (ニューロコンピューティング)

• 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報 115(111), 131-136, 2015-06-23
• NAID 40020524650

• 技術革新 大規模データ処理基盤は随時見直す HadoopアプリもSQLで開発 柔軟性高いクラウドDWH (特集 データベースの新常識 ゆるハヤ設計)

• 日経systems (265), 43-47, 2015-05
• NAID 40020463586

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