The SQL Language

In 1969, an IBM researcher named Edgar Frank Codd published a seemingly innocuous paper: “Derivability, Redundancy, and Consistency of Relations Stored in Large Data Banks”. No one suspected that this text would revolutionize the way we store and manipulate computer data. The following year, Codd followed up with a more ambitious paper in Communications of the ACM: “A Relational Model of Data for Large Shared Data Banks”. This time, the industry took notice.

Codd’s relational model broke with the hierarchical and network approaches dominant at the time. He proposed organizing data in simple tables, linked to each other through mathematical relationships. The idea seems almost trivial today, but it revolutionized computer science thinking. Academic and industrial communities embraced these theoretical concepts.

At IBM, Donald Chamberlin and his team wasted no time. In 1974, they developed System R, the first truly worthy relational database prototype. The associated query language was named SEQUEL, for Structured English QUEry Language. This choice revealed an ambition: to create a language close to natural English, accessible to non-specialist users. Gone were cryptic commands, replaced by instructions comprehensible to the masses.

The project progressed incrementally. SEQUEL-XRM emerged between 1974 and 1975, followed by a complete rewrite in 1976-1977. This new version, dubbed SEQUEL/2, introduced essential functionalities: multi-table queries, multi-user support, advanced data management. But an unexpected obstacle arose: the British company Hawker Siddeley Aircraft Company already owned the SEQUEL trademark. IBM had to rename its language with the acronym SQL.

The story took an unexpected turn in 1979. While IBM was perfecting its prototypes, a small California company named Relational Software commercialized the first relational database management system. In a stroke of marketing genius, this company numbered its product “Version 2”, thus avoiding the usual reluctance toward first versions. Relational Software would become Oracle Corporation, beating the IBM giant at its own game.

IBM caught up with SQL/DS in 1981, and DB2 in 1983. Meanwhile, customer tests conducted as early as 1978 had validated the approach: SQL won over users with its ease of use and power, allowing them to describe what they wanted to obtain without specifying how to obtain it. This declarative approach contrasted with traditional procedural languages and democratized database access.

Standardization naturally became necessary. In 1986, the American National Standards Institute certified SQL as an official standard. The International Organization for Standardization followed in 1987. These first standards, approximately 150 pages long, standardized the SQL dialect of IBM DB2. However, they suffered from gaps and imprecision, consequences of the divergent commercial interests of software vendors.

The SQL2 standard of 1992 corrected these flaws. This 500-page document eliminated some of the weaknesses of the previous version and standardized advanced conceptual functionalities, sometimes beyond acceptable technical capabilities. Three levels of compliance emerged: Entry for minor modifications, Intermediate for at least 50% of the standard, and Full for total compliance.

SQL99, or SQL3, marked a new evolution at the end of the 1990s. This 2000-page standard integrated object-relational models, calling interfaces, and advanced integrity management. It replaced the old compliance levels with two categories: Core SQL99 and Enhanced SQL99. The document was now structured into five specialized parts, testifying to the growing complexity of the language.

The 21st century saw the birth of SQL:2003, SQL:2008, and SQL:2011, each version enriching the language with new capabilities. But beyond this technical chronology, SQL owes its success to deeper qualities. Its syntax inspired by natural English makes it accessible to non-specialists. Its declarative nature frees users from procedural constraints. The underlying relational model structures data in a clear and coherent manner.

The concepts of primary and foreign keys, normalization, and referential integrity guarantee the consistency of stored data. This mathematical rigor, combined with flexibility of use, explains SQL’s massive adoption by the industry. Oracle, MySQL, PostgreSQL, Microsoft SQL Server, and so many other systems perpetuate this legacy, extending the language’s capabilities while preserving compatibility.