SQL
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| SQL | |
|---|---|
| Name | SQL |
| Developer | Donald D. Chamberlin, Raymond F. Boyce, IBM |
| Released | 1970s |
| Latest release | Varied (standards and vendor implementations) |
| Programming language | English language-based query language |
| Operating system | Cross-platform |
| Genre | Query language, Database management system |
| License | Varies by implementation |
SQL Structured Query Language is a domain-specific language designed for managing and querying relational data in Database Management Systems. Originating as a research project at IBM in the early 1970s, it became the de facto lingua franca for interacting with relational Databases such as Oracle Database, MySQL, Microsoft SQL Server, and PostgreSQL. The language balances declarative query constructs with data definition and data control capabilities, and it underpins transactional systems across industries including finance, healthcare, telecommunications, and e-commerce.
History
SQL traces to the SEQUEL project at IBM's San Jose Research Laboratory led by Donald D. Chamberlin and Raymond F. Boyce during the development of the System R prototype. Early demonstrations influenced commercial products such as Oracle Corporation's first database and the Ingres project from University of California, Berkeley. Standardization efforts began with ANSI and ISO committees producing formal specifications; milestone events include the publication of the SQL-92 standard and successive revisions like SQL:1999 and SQL:2003. Legal and commercial episodes shaped adoption, including litigation between vendors and patent discussions involving IBM and other corporations. Academic research from figures such as E. F. Codd (relational model) and institutions like MIT and Stanford University informed theoretical foundations.
Language Elements
The language provides statements for data manipulation, data definition, and data control. Core constructs include SELECT for queries, INSERT for adding rows, UPDATE for modifying rows, and DELETE for removing rows. Schema-related statements such as CREATE TABLE, ALTER TABLE, and DROP TABLE manage table structures; integrity is enforced by constraints like PRIMARY KEY, FOREIGN KEY, UNIQUE, and CHECK. Transactional control uses COMMIT, ROLLBACK, and isolation levels described by the ACID model originating from database research. Advanced elements encompass JOIN types (INNER, LEFT, RIGHT, FULL), set operations like UNION, window functions introduced in standards influenced by vendors such as Oracle Corporation and Microsoft Corporation, and procedural extensions including PL/SQL (Oracle) and T-SQL (Microsoft) that add control flow and error handling. Optimization relies on Query optimizer techniques and execution plans produced by engines at IBM, Oracle Corporation, and open-source projects.
Implementations and Dialects
Major commercial implementations include Oracle Database by Oracle Corporation, Microsoft SQL Server by Microsoft Corporation, and IBM Db2 by IBM. Prominent open-source and community projects are PostgreSQL, MySQL (originally by MySQL AB and later stewarded by Oracle Corporation), and MariaDB initiated by original MySQL AB developers. Embedded and analytical systems implement variations: SQLite for lightweight local storage, Amazon Redshift by Amazon (company) and Snowflake Inc. for cloud analytics, and Google BigQuery by Google LLC for distributed query execution. Each vendor and project introduces dialect-specific extensions—procedural languages, built-in functions, and optimizer hints—leading to portability considerations addressed by tools from companies such as IBM, Redgate, and Percona.
Standards and Compliance
Formal standardization is coordinated by ANSI and ISO/IEC committees producing editions like SQL:2011 and SQL:2016. Standards define grammar, data types, and conformance levels; compliance is partial across vendors, with profiling and optional features (e.g., XML support, temporal tables, JSON functions) adopted variably by Oracle Corporation, Microsoft Corporation, IBM, and open-source projects like PostgreSQL. Industry consortia and certification programs—offered by Oracle Corporation, Microsoft Corporation, and community foundations—help assess compatibility. Historical standardization milestones reflected input from Bell Labs, University of California, Berkeley, and corporate research groups.
Use Cases and Applications
Relational query capabilities enable transactional online transaction processing systems used by banks such as JPMorgan Chase and insurers including Aetna. Analytical and business intelligence workloads run on platforms like Teradata and Snowflake Inc. for reporting and data warehousing. Embedded databases such as SQLite are ubiquitous in mobile platforms from Apple Inc. and Google LLC devices for local persistence. Scientific projects at institutions like CERN and NASA use relational databases for metadata and publication catalogs. Enterprise resource planning vendors including SAP SE and customer relationship management suites like Salesforce integrate SQL backends for persistence and queries.
Security and Administration
Security features include authentication integrations with directory services such as Active Directory by Microsoft Corporation, authorization models using role-based access control found in Oracle Database and PostgreSQL, and encryption-at-rest and in-transit options provided by IBM, Amazon (company), and Google LLC. Administration tasks involve backup and recovery utilities (e.g., RMAN for Oracle Database), replication and high-availability solutions like Oracle Data Guard, Microsoft Always On, and logical replication in PostgreSQL. Compliance with regulations enforced by bodies such as FINRA and HIPAA drives auditing, masking, and retention policies implemented in enterprise solutions from Oracle Corporation and Microsoft Corporation.