SQL
What is SQL?
How has SQL integrated cloud computing and artificial intelligence?
SQL, computer language designed for extracting information from databases.
In the 1970s computer scientists began developing a standardized way to manipulate databases, and out of that research came SQL. The late 1970s and early ’80s saw the release of a number of SQL-based products. SQL gained popularity when the American National Standards Institute (ANSI) adopted the first SQL standard in 1986. Continued work on relational databases led to improvements in SQL, making it one of the most popular database languages in existence. Some large software companies, such as Microsoft Corporation and Oracle Corporation, produced their own versions of SQL, and an open-source version, MySQL, became extremely popular.
SQL works by providing a way for programmers and other computer users to get desired information from a database using something resembling normal English. On the simplest level, SQL consists of only a few commands: Select, which grabs data; Insert, which adds data to a database; Update, which changes information; and Delete, which deletes information. Other commands exist to create, modify, and administer databases.
- In full:
- structured query language
- Related Topics:
- computer programming language
- MySQL
- query language
- fourth-generation language
SQL is used in everything from government databases to e-commerce sites on the Internet. As the popularity of SQL grew, programmers and computer scientists continued to optimize the way that relational databases work.In the 2010s and 2020s, SQL evolved to support cloud computing and large-scale analytics. Modern SQL systems increasingly operate across distributed cloud servers rather than on a single local machine, allowing them to process larger datasets. Artificial intelligence (AI) also became more central to SQL platforms. Microsoft’s SQL Server 2025, for example, introduced vector search and natural-language querying, both of which use AI to help the user craft queries using conversational prompts to return results that broadly match the semantics of the request rather than the stringent keyword matches required by earlier SQL iterations.
