Structured Query Language
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| Structured Query Language | |
|---|---|
| Name | Structured Query Language |
| Paradigm | Declarative |
| Designed by | Donald Chamberlin, Ray Boyce |
| Developed by | IBM |
| First appeared | 1974 |
| Typing | Static |
| Implementations | MySQL, PostgreSQL, Microsoft SQL Server |
| Influenced by | COBOL, PL/1 |
| Influenced | SQL/PSM, T-SQL |
Structured Query Language is a standard programming language designed for managing and manipulating data in relational database management systems like Oracle Database, Microsoft Access, and SQLite. It was developed by IBM in the 1970s, with significant contributions from Donald Chamberlin and Ray Boyce, who drew inspiration from COBOL and PL/1. The language has since become a widely accepted standard, supported by various database systems, including MySQL, PostgreSQL, and Microsoft SQL Server. As a result, it has been widely adopted by organizations such as NASA, Google, and Amazon.
Introduction
The introduction of Structured Query Language revolutionized the way data is managed and analyzed, enabling users to perform complex queries and operations on large datasets. This language has been instrumental in the development of various database systems, including DB2, Informix, and Sybase. Its simplicity and flexibility have made it a popular choice among developers, including those at Facebook, Twitter, and LinkedIn. The language's ability to handle complex queries has also made it a crucial tool for data analysts and scientists working with Apache Hadoop, Apache Spark, and R programming language.
History
The history of Structured Query Language dates back to the 1970s, when IBM developed the first version of the language. The initial version, known as SEQUEL, was designed to manage data in System R, a relational database system developed by IBM. The language was later renamed to Structured Query Language and has since undergone several revisions, with significant contributions from ANSI and ISO. The language has been influenced by various individuals, including Edgar Codd, Chris Date, and Hugh Darwen, who have worked with organizations such as University of California, Berkeley, Stanford University, and Massachusetts Institute of Technology.
Syntax
The syntax of Structured Query Language is designed to be simple and intuitive, with a focus on readability and ease of use. The language consists of a set of commands, including SELECT, INSERT, UPDATE, and DELETE, which are used to perform various operations on data. The language also supports various data types, including integer, string, and date, which are used to store and manipulate data. Developers, such as those at Apple, Microsoft, and Oracle Corporation, use the language to create complex queries and operations, often in conjunction with Java, Python, and C++.
Data Types
Structured Query Language supports a wide range of data types, including numeric, character, and datetime. The language also supports various data structures, including arrays and lists, which are used to store and manipulate complex data. The data types and structures supported by the language are similar to those found in other programming languages, such as C++ and Java. The language's support for various data types has made it a popular choice among developers, including those working with Apache Cassandra, MongoDB, and Couchbase.
Commands
The commands in Structured Query Language are used to perform various operations on data, including data retrieval, data manipulation, and data definition. The language supports a wide range of commands, including CREATE, ALTER, and DROP, which are used to create, modify, and delete database objects. The language also supports various query commands, including SELECT and JOIN, which are used to retrieve and manipulate data. The commands in the language are similar to those found in other programming languages, such as SQL/PSM and T-SQL, and are used by developers at organizations such as IBM, Google, and Amazon.
Applications
The applications of Structured Query Language are diverse and widespread, with the language being used in a wide range of industries, including finance, healthcare, and e-commerce. The language is used by various organizations, including NASA, Google, and Amazon, to manage and analyze large datasets. The language's ability to handle complex queries and operations has made it a crucial tool for data analysts and scientists working with Apache Hadoop, Apache Spark, and R programming language. The language is also used in various academic institutions, including Harvard University, Stanford University, and Massachusetts Institute of Technology, to teach database management and data analysis. Additionally, the language is used by United Nations, World Health Organization, and International Monetary Fund to manage and analyze data related to global issues.