A Timeline of Database History.


Ancient Times: Human beings began to store information very long ago. In the ancient times, elaborate database systems were developed by government offices, libraries, hospitals, and business organizations, and some of the basic principles of these systems are still being used today.

1960s: Computerized database started in the 1960s, when the use of computers became a more cost-effective option for private organizations. There were two popular data models in this decade: a network model called CODASYL and a hierarchical model called IMS. One database system that proved to be a commercial success was the SABRE system that was used by IBM to help American Airlines manage its reservations data.

1970 to 1972: E.F. Codd published an important paper to propose the use of a relational database model, and his ideas changed the way people thought about databases. In his model, the database’s schema, or logical organization, is disconnected from physical information storage, and this became the standard principle for database systems.

1970s: Two major relational database system prototypes were created between the years 1974 and 1977, and they were the Ingres, which was developed at UBC, and System R, created at IBM San Jose. Ingres used a query language known as QUEL, and it led to the creation of systems such as Ingres Corp., MS SQL Server, Sybase, Wang’s PACE, and Britton-Lee. On the other hand, System R used the SEQUEL query language, and it contributed to the development of SQL/DS, DB2, Allbase, Oracle, and Non-Stop SQL. It was also in this decade that Relational Database Management System, or RDBMS, became a recognized term.

1976: A new database model called Entity-Relationship, or ER, was proposed by P. Chen this year. This model made it possible for designers to focus on data application, instead of logical table structure.

1980s: Structured Query Language, or SQL, became the standard query language.

Relational database systems became a commercial success as the rapid increase in computer sales boosted the database market, and this caused a major decline in the popularity of network and hierarchical database models. DB2 became the flagship database product for IBM, and the introduction of the IBM PC resulted in the establishments of many new database companies and the development of products such as PARADOX, RBASE 5000, RIM, Dbase III and IV, OS/2 Database Manager, and Watcom SQL.

Early 1990s: After a database industry shakeout, most of the surviving companies sold complex database products at high prices. Around this time, new client tools for application development were released, and these included the Oracle Developer, PowerBuilder, VB, and others. A number of tools for personal productivity, such as ODBC and Excel/Access, were also developed. Prototypes for Object Database Management Systems, or ODBMS, were created in the early 1990s.

Mid 1990s: The advent of the Internet led to exponential growth of the database industry. Average desktop users began to use client-server database systems to access computer systems that contained legacy data.

Late 1990s: Increased investment in online businesses resulted in a rise in demand for Internet database connectors, such as Front Page, Active Server Pages, Java Servelets, Dream Weaver, ColdFusion, Enterprise Java Beans, and Oracle Developer 2000. The use of cgi, gcc, MySQL, Apache, and other systems brought open source solution to the Internet. With the increased use of point-of-sale technology, online transaction processing and online analytic processing began to come of age.

2000s: Although the Internet industry experienced a decline in the early 2000s, database applications continue to grow. New interactive applications were developed for PDAs, point-of-sale transactions, and consolidation of vendors. Presently, the three leading database companies in the western world are Microsoft, IBM, and Oracle.

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Microsoft Access - is the database application from the Microsoft Office Suite of applications. It is a powerful personal database and data manipulation tool that is also widely used in many small businesses.