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SQL (commonly expanded to Structured Query Language — see History for the term's derivation) is the most popular computer language used to create, modify, retrieve and manipulate data from relational database management systems. The language has evolved beyond its original purpose to support object-relational database management systems. It is an ANSI/ISO standard.

SQL is commonly spoken in initialism-style ess-cue-el (see English alphabet) — regarded as more formal — or in a phonetically-amalgamated form that mirrors the English word sequel. Concerning the names of major database products (or projects) containing the letters SQL, each has its own convention: MySQL is commonly pronounced my ess-cue-el; PostgreSQL is expediently pronounced postgres; and Microsoft SQL Server is commonly spoken as Microsoft-sequel-server.

History

An influential paper, ["A Relational Model of Data for Large Shared Data Banks"], by Dr. Edgar F. Codd, was published in June, 1970 in the Association for Computing Machinery (ACM) journal, Communications of the ACM, although drafts of it were circulated internally within IBM in 1969. Codd's model became widely accepted as the definitive model for relational database management systems (RDBMS or RDMS).

During the 1970s, a group at IBM's San Jose research center developed a database system "System R" based upon, but not strictly faithful to, Codd's model. Structured English Query Language ("SEQUEL") was designed to manipulate and retrieve data stored in System R. The acronym SEQUEL was later condensed to SQL because the word 'SEQUEL' was held as a trademark by the Hawker-Siddeley aircraft company of the UK. Although SQL was influenced by Codd's work, Donald D. Chamberlin and Raymond F. Boyce at IBM were the authors of the SEQUEL language design.Donald D. Chamberlin and Raymond F. Boyce, 1974. "[SEQUEL: A structured English query language]", International Conference on Management of Data, Proceedings of the 1974 ACM SIGFIDET (now SIGMOD) workshop on Data description, access and control, Ann Arbor, Michigan, pp. 249–264. Their concepts were published to increase interest in SQL.

The first non-commercial, relational, non-SQL database, Ingres, was developed in 1974 at U.C. Berkeley.

In 1978, methodical testing commenced at customer test sites. Demonstrating both the usefulness and practicality of the system, this testing proved to be a success for IBM. As a result, IBM began to develop commercial products based on their System R prototype that implemented SQL, including the System/38 (announced in 1978 and commercially available in August 1979), SQL/DS (introduced in 1981), and DB2 (in 1983).[link]

At the same time Relational Software, Inc. (now Oracle Corporation) saw the potential of the concepts described by Chamberlin and Boyce and developed their own version of a RDBMS for the Navy, CIA and others. In the summer of 1979 Relational Software, Inc. introduced Oracle V2 (Version2) for VAX computers as the first commercially available implementation of SQL. Oracle is often incorrectly cited as beating IBM to market by two years, when in fact they only beat IBM's release of the System/38 by a few weeks. Considerable public interest then developed; soon many other vendors developed versions, and Oracle's future was ensured.

Standardization

SQL was adopted as a standard by ANSI (American National Standards Institute) in 1986 and ISO (International Organization for Standardization) in 1987. ANSI has declared that the official pronunciation for SQL is /ɛs kjuː ɛl/, although many English-speaking database professionals still pronounce it as sequel, and with gaining popularity has received the alias 'SQuirreL'.

The SQL standard has gone through a number of revisions:
Year Name Alias Comments
1986 SQL-86 SQL-87 First published by ANSI. Ratified by ISO in 1987.
1989 SQL-89 Minor revision.
1992 SQL-92 SQL2 Major revision.
1999 SQL:1999 SQL3 Added regular expression matching, recursive queries, triggers, non-scalar types and some object-oriented features. (The last two are somewhat controversial and not yet widely supported.)
2003   Introduced XML-related features, window functions, standardized sequences and columns with auto-generated values (including identity-columns).

Scope

Although SQL is defined by both ANSI and ISO, there are many extensions to and variations on the version of the language defined by these standards bodies. Many of these extensions are of a proprietary nature, such as Oracle Corporation's PL/SQL or Sybase, IBM's SQL PL (SQL Procedural Language) and Microsoft's Transact-SQL. It is also somewhat common for commercial implementations to omit support for basic features of the standard, such as the DATE or TIME data types, preferring some variant of their own. As a result, in contrast to ANSI C or ANSI Fortran, which can usually be ported from platform to platform without major structural changes, SQL code can rarely be ported between database systems without major modifications. There are several reasons for this lack of portability between database systems: SQL is designed for a specific, limited purpose — querying data contained in a relational database. As such, it is a set-based, declarative computer language rather than an imperative language such as C or BASIC which, being programming languages, are designed to solve a much broader set of problems. Language extensions such as PL/SQL are designed to address this by turning SQL into a full-fledged programming language while maintaining the advantages of SQL. Another approach is to allow programming language code to be embedded in and interact with the database. For example, Oracle and others include Java in the database, while PostgreSQL allows functions to be written in a wide variety of languages, including Perl, Tcl, and C.

One joke about SQL is that "SQL is not structured, nor is it limited to queries, nor is it a language." This is founded on the notion that pure SQL is not a classic programming language since it is not Turing-complete. On the other hand, however, it is a programming language because it has a grammar, syntax, and programmatic purpose and intent. The joke recalls Voltaire's remark that the Holy Roman Empire was "not holy, nor Roman, nor an empire."

SQL contrasts with the more powerful database-oriented fourth-generation programming languages such as Focus or SAS in its relative functional simplicity and simpler command set. This greatly reduces the degree of difficulty involved in maintaining SQL source code, but it also makes programming such questions as 'Who had the top ten scores?' more difficult, leading to the development of procedural extensions, discussed above. However, it also makes it possible for SQL source code to be produced (and optimized) by software, leading to the development of a number of natural language database query languages, as well as 'drag and drop' database programming packages with 'object oriented' interfaces. Often these allow the resultant SQL source code to be examined, for educational purposes, further enhancement, or to be used in a different environment.

SQL keywords

SQL keywords fall into several groups.

Data retrieval

The most frequently used operation in transactional databases is the data retrieval operation. When restricted to data retrieval commands, SQL acts as a functional language
Example 1:
SELECT * FROM books
WHERE price > 100.00
ORDER BY title
This example retrieves the records from the books table that have a price field which is greater than 100.00. The result is sorted alphabetically by book title. The asterisk (*) means to show all columns of the books table. Alternatively, specific columns could be named.

Example 2:
SELECT books.title, count(*) AS Authors
FROM books
JOIN book_authors ON books.book_number = book_authors.book_number
GROUP BY books.title
Example 2 shows both the use of multiple tables in a join and aggregation (grouping). This example shows how many authors there are per book. Example output may resemble:

Title                   Authors
----------------------  -------
SQL Examples and Guide     3
The Joy of SQL             1
How to use Wikipedia       2
Pitfalls of SQL            1
How SQL Saved my Dog       1

Data manipulation

First there are the standard Data Manipulation Language (DML) elements. DML is the subset of the language used to add, update and delete data.
Example:
INSERT INTO my_table (field1, field2, field3) VALUES ('test', 'N', NULL);
UPDATE my_table SET field1 = 'updated value' WHERE field2 = 'N';
DELETE FROM my_table WHERE field2 = 'N';

Data transaction

Transaction, if available, can be used to wrap around the DML operations. COMMIT and ROLLBACK interact with areas such as transaction control and locking. Strictly, both terminate any open transaction and release any locks held on data. In the absence of a START TRANSACTION or similar statement, the semantics of SQL are implementation-dependent.

Example:
START TRANSACTION;
UPDATE inventory SET quantity = quantity - 3 WHERE item = 'pants';
COMMIT;

Data definition

The second group of keywords is the Data Definition Language (DDL). DDL allows the user to define new tables and associated elements. Most commercial SQL databases have proprietary extensions in their DDL, which allow control over nonstandard features of the database system.

The most basic items of DDL are the CREATE and DROP commands.

Some database systems also have an ALTER command, which permits the user to modify an existing object in various ways -- for example, adding a column to an existing table.

Example:
CREATE TABLE my_table (
my_field1   INT          UNSIGNED,
my_field2   VARCHAR (50),
my_field3   DATE         NOT NULL,
PRIMARY KEY (my_field1, my_field2)
)

Data control

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

Its two main keywords are:

Example:
GRANT SELECT, UPDATE ON my_table TO some_user, another_user

Other

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

Database systems using SQL

Criticisms of SQL

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

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

Alternatives to SQL

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

References

  1. [Discussion on alleged SQL flaws] (C2 wiki)
  2. [Web page about FSQL]: References and links.
  3. [Galindo J., Urrutia A., Piattini M., "Fuzzy Databases: Modeling, Design and Implementation"]. Idea Group Publishing Hershey, USA, 2005.

External links

[[wikibooks:Programming|Wikibooks Programming]] has more about this subject:
[[wikibooks:Programming:SQL|SQL]]

Topics in database management systems (DBMS)[ view][ talk][ edit] )
Concepts
Database | Database model | Relational database | Relational model | Relational algebra | Primary key - Foreign key - Surrogate key - Superkey
Database normalization | Referential integrity | Relational DBMS | Distributed DBMS | ACID

Objects
Trigger | View | Table | Cursor | Log | Transaction | Index | Stored procedure | Partition
Topics in SQL
Select | Insert | Update | Merge | Delete | Join | Union | Create | Drop
Comparison of syntax

Implementations of database management systems
Types of implementations
Flat file | Deductive | Dimensional | Hierarchical | Object oriented | Temporal

Products
dBASE | Oracle | Sybase | MySQL | Microsoft SQL Server | PostgreSQL | DB2 | Comparison - relational | Comparison - object-relational
Components
Query language | Query optimizer | Query plan | ODBC | JDBC
Lists
List of object-oriented database management systems
List of relational database management systems
List of truly relational database management systems

 


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