CODASYL, pronounced /ˈkɒdəsɪl/, is a term that denotes an early data model for database management systems. It stands for Conference on Data Systems Languages, which organized the creation of the CODASYL Data Model in the late 1960s. The spelling of "CODASYL" is phonetically represented with four syllables with the primary stress on the second syllable. In the first syllable, "CO," it is pronounced like 'ka.' The second syllable "DA," is pronounced as 'duh' and the third syllable "SYL," is pronounced as 'sil'.
CODASYL (Committee on Data Systems Languages), also known as the CODASYL DBTG Report, is a committee formed in 1959 that developed a standard for database management systems in the early days of computer technology.
CODASYL's main objective was to create a high-level language to conveniently access and retrieve data stored in a database. The committee's work culminated in the publishing of the COBOL-based programming language in 1961, which became the de facto standard for data processing languages in the 1960s and 1970s.
The CODASYL standard provided a model for the organization, storage, and retrieval of data in a hierarchical structure, allowing efficient access to records through the use of pointers. This hierarchical structure was composed of sets and records, with relationships defined through a network-like approach using pointers. The standard also included mechanisms for data integrity and concurrency control.
While widely used in its time, the CODASYL approach eventually fell out of favor as more efficient and flexible database models, such as the relational model, emerged. However, the CODASYL DBTG Report played a significant role in the development of modern database management systems and laid the foundations for subsequent advancements in data processing technologies.
Today, the principles and concepts defined by the CODASYL standard are collectively referred to as the CODASYL approach or model, and its influence can still be seen in some legacy systems and database management systems that adhere to hierarchical or network models.