Database management systems can be classified based on several criteria, such as the data model, user numbers and database distribution, all described below.
One of the original scopes of computer applications was storing large amounts of data on mass storage devices and retrieving them at a later point in time. Over time user requirements increased to include not only sequential access but also random access to data records, concurrent access by parallel (writing) processes, recovery after hardware and software failures, high performance, scalability, etc. In the 1970s and 1980s, the science and computer industries developed techniques to fulfill those requests.
Database systems have become an essential component of every software applications. Database systems emerged in 1960s and took 10 years to gain widespread usage. More and more organizations began to adopt database technology to manage their corporate data during the mid 1970s Generalized Update Access Method (GUAM) was a hierarchical database system developed in early 1960s by Rockwell International. Rockwell developed this software to manage the data usually associated with manufacturing operations. IBM introduced Information Management System (IMS) as a hierarchical database management system soon after that. The 1970s were the dawn of relational database technology. Dr. Edgar F. Codd's paper on the [[w:Relational model|relational model\\ revolutionized the thinking on data systems. The industry quickly responded to the superiority of the relational model by adapting their products to that model. During the 1980s, database systems gained a lot of ground and a large percentage of businesses made the transition from file-oriented data systems to database systems. Some of the leading products like ORACLE, DB2, SQL Server, Informix and Sybase started ruling the database world with their flagship relational database management systems (RDBMS). The relational model matured and became the leading data model in the 1990s. Towards the end of the '90s, object-oriented databases gained popularity; however, older applications that were already developed using the relational model were reluctant to move to the object-oriented model. The late 2000s saw the rise of the NoSQL movement, which moved towards more application-specific data models than the relational model. The object-oriented model is one of the alternative data models being used. Most leading database management systems support the object-oriented model. Many of them offer object-to-relational mapping to achieve object model support. For example, DB2 is Relational, Hierarchical (XML), Object oriented Database Management system.