Introduction and Brief History of SQL (with timelines)

SQL, or Structured Query Language, popularly pronounced as (/ˌɛsˌkjuːˈɛl/ S-Q-L, sometimes /ˈsiːkwəl/ "sequel", based on the history), is a domain-specific programming language designed for managing and manipulating relational databases. It provides a standardized way to interact with relational database management systems (RDBMS), allowing users to define, query, update, and manage databases.

BRIEF HISTORY OF SQL

Structured Query Language (SQL) boasts a rich historical narrative dating back to the early 1970s.

According to Wikipedia, IBM engineers Donald D. Chamberlin and Raymond F. Boyce embarked on the development of SQL after being introduced to the relational model by Edgar F. Codd, in the early 1970s. Initially named SEQUEL (Structured English QUEry Language), this language aimed to manipulate and retrieve data from IBM's original quasirelational database management system, System R, created by a team at IBM San Jose Research Laboratory during the 1970s.

Chamberlin and Boyce's initial attempt at a relational database language, SQUARE (Specifying Queries in A Relational Environment), faced usability challenges due to subscript/superscript notation. Upon relocating to the San Jose Research Laboratory in 1973, they commenced the development of a successor to SQUARE. The original moniker, SEQUEL, often considered a play on words referencing QUEL, the query language of Ingres, underwent a name change to SQL (with the vowels omitted) because "SEQUEL" was a trademark of the UK-based company Hawker Siddeley Dynamics Engineering Limited. Eventually, SQL evolved into the acronym for Structured Query Language.

MILESTONES AND TIMELINES OF SQL
Here is a succinct account of the key milestones and timelines shaping the evolution of SQL:

1970s: Genesis and Early Progressions

• 1970: Dr. Edgar F. Codd, an IBM researcher, pens the influential paper "A Relational Model of Data for Large Shared Data Banks," introducing the foundational concept of a relational database model.
• 1974: IBM's System R project, spearheaded by Donald D. Chamberlin and Raymond F. Boyce, pioneers the initial version of SQL as a query language for the management of relational databases.

1980s: Standardization and Commercial Integration

• 1986: The American National Standards Institute (ANSI) formally adopts SQL as a standard (ANSI SQL-86).
• 1987: The International Organization for Standardization (ISO) globally adopts ANSI SQL as the international standard (ISO SQL:1987).
• 1989: SQL-89, or SQL-1, is standardized, introducing fundamental concepts while lacking certain features found in subsequent versions.

1990s: Progression and Feature Enrichment

• 1992: SQL-92, or SQL-2, is unveiled as a significant revision to the SQL standard. It incorporates numerous new features, including support for integrity constraints, outer joins, and more.
• 1999: SQL-99, or SQL-3, introduces pivotal features such as support for procedural programming with SQL/PSM (Persistent Stored Modules), triggers, and recursive queries.

2000s: Continuous Standardization and Vendor-Specific Innovations

• SQL standards maintain their evolution, with subsequent releases bringing forth new features and enhancements.
• Vendors frequently introduce additional features beyond the standard, resulting in variations in SQL dialects.

2010s: NoSQL Emergence and Big Data Dynamics

• The ascent of NoSQL databases poses challenges to traditional relational databases, yet SQL remains a prevalent language for querying structured data.
• Novel SQL-based technologies and tools arise to contend with the escalating volume and diversity of data, with SQL finding application in big data processing frameworks like Apache Hive and Apache Spark.

2020s: Persistent Relevance and Contemporary Advancements

• SQL maintains its pivotal role as a fundamental language for engaging with relational databases.
• The SQL standard continues its evolution with periodic releases and updates, addressing contemporary challenges in data management.

Across its historical trajectory, SQL has played a pivotal role in shaping the landscape of database management systems, establishing itself as an indispensable component in diverse domains such as business, finance, healthcare, and more.

SQL's longevity and adaptability have made it a standard language for working with structured data, and its principles have influenced the design of other query languages and database systems.