What are the different Data Models in DBMS ?

Hierarchical Model The hierarchical data model organizes data in a tree structure. There is a hierarchy of parent and child data segments. This structure implies that a record can have repeating information, generally in the child data segments. Hierarchical DBMSs were popular from the late 1960s, with the introduction of IBM's Information Management System (IMS) DBMS, through the 1970s. Network Model The popularity of the network data model coincided with the popularity of the hierarchical data model. Some data were more naturally modeled with more than one parent per child. Relational Model (RDBMS - relational database management system) A database based on the relational model developed by E.F. Codd. A relational database allows the definition of data structures, storage and retrieval operations and integrity constraints. In such a database the data and relations between them are organised in tables. A table is a collection of records and each record in a table contains the same fields. Properties of Relational Tables: # Values Are Atomic # Each Row is Unique # Column Values Are of the Same Kind # The Sequence of Columns is Insignificant # The Sequence of Rows is Insignificant # Each Column Has a Unique Name The RELATIONAL database model is based on the Relational Algebra. Object/Relational Model Object/relational database management systems (ORDBMSs) add new object storage capabilities to the relational systems at the core of modern information systems. nd other complex objects. Object-Oriented Model Object DBMSs add database functionality to object programming languages. They bring much more than persistent storage of programming language objects. Object DBMSs extend the semantics of the C++, Smalltalk and Java object programming languages to provide full-featured database programming capability, while retaining native language compatibility. A major benefit of this approach is the unification of the application and database development into a seamless data model and language environment. Semistructured Model In semistructured data model, the information that is normally associated with a schema is contained within the data, which is sometimes called ``self-describing''. In such database there is no clear separation between the data and the schema, and the degree to which it is structured depends on the application. There are couple more models but you don't have to know them unless you are into Database background.