History of Database Technology and Data Models Essay Example for Free

History of Database Technology and Data Models Essay Imagine that you own bank and along with that, you own your bank’s credibility to your 100,000 clients. Just writing down each client’s information in a piece of paper would not be very secure and practical nowadays. That’s how an electronic database system comes in the picture. In this fast growing world, a technology like a database system is very necessary for establishments that hold a huge amount of data. However, the development of the current database technology and database models underwent an intricate process before it comes to a full bloom. In 1964, the word â€Å"database† technically denoted collections of data shared by end-users of time sharing computer systems and was coined by workers in a military information system. In addition, around 1960s, private companies started to own computers because of their increasing storage capabilities. Two data models were introduced: network (CODASYL) and hierarchical (IMS) model. During that time, database management systems were unsystematic. There no actual theoretical model about data organization. There was more emphasis on the processing of the records rather than the overall structure of the database system. During the 1970s, many astonishing breakthroughs on databases were witnessed. It was about the 1970 that E. F. Codd proposed a relational model for databases. The presented a system that separates the logical organization (schema) of a database from the physical storages and since that, it has been a standard in the field of computing. The term Relational Database Management System (RDBMS) was coined during this period. Theories about databases had finally made its way to the mainstream research projects. Two main prototypes for RDBMS were created: Ingres that was developed at UCB and this system used QUEL as query language and System R that was developed at IBM San Jose and this system used SEQUEL as query language. Meanwhile, in 1976, P. Chen suggested the Entity-Relationship (ER) model for database design which was proved to be vital in conceptual data models. This proposal enabled the designers to focus more on the data usage rather than its logical table structure. Commercialization of database systems for businesses began during the 1980s as demands for computers boomed. In addition, Structured Query Language (SQL) became a standard for database systems during these periods. DB2 became IBM’s flagship and development of IBM PC paved the way for more database companies and products like Dbase III and IV, Database Manager, OS/2 and Watcom SQL. The network and hierarchical models for database also started to disappear in the background. When the 1990s came, only a few surviving companies began to offer complex products at higher prices. Developments on database systems were more focused on client tool applications such as PowerBuilder (Sybase), Oracle Developer and VB (Microsoft). Some personal productivity tools related to database management were also created such as Microsoft Access and Excel. Some prototypes of Object Database Management System (ODBMS) also arose in the 1990s. It was also during the 1990s that the World Wide Web appeared. Large investments were made by Internet-related companies on Web and database connectors. Examples of these connectors are Active Server Pages (ASP), Java Servlets, JDBC, ColdFusion, Dream Weaver and Oracle Developer 2000. A solid growth of database applications was still observed in the early 21st century. Three companies continually dominate the database market: Oracle, IBM and Microsoft. In the near future, it is generally seen that databases management will be more sophisticated since huge systems (systems with storage measured in terabytes) are currently existing today. Most of these systems are used by most projects with science databases (genome projects, space exploration data). However, the â€Å"next great thing† on is the usage of XML with Java and other emerging technologies as a way to store data.