What is Data Model in DBMS with Example ?

Data Model

Data model give developers a clear picture of the data, data models in DBMS facilitate the creation of physical databases and aid in conceptual, physical, and logical understanding of the design. The storage, access, and updating of data in a database management system (DBMS) are described by data models. In order for every member of an organization to comprehend how the data is arranged, a set of symbols and language are employed to represent them. To depict the description of data, it offers a collection of conceptual tools that are widely utilized.

Type of Data Model in DBMS

There are four types of Data model in DBMS:

1. Relational Data Model

Relational data model arranges the data in a table's rows and columns. As a result, tables are used in relational models to describe data and relationships between them. Relationships are another name for tables. Edgar F. Codd first presented this model in 1969. The most popular model, which is mostly utilized by commercial data processing applications, is the relational data model.Now a days, Relational data model is widely used because it is very effective and helpful for arranging data.

2. Entity Relationship Data Model

Data represented logically as objects and their relationships is known as an ER model. Relationships are associations between entities, which are the names given to these items. Peter Chen created this model, and it was revealed in a 1976 publication. In database design, it was widely utilized. The entities have a set of attributes.

The'student' entity, for instance, is described by student_name, student_id. A collection of entities of the same kind is called a "Entity set," and a collection of relationships of the same kind is called a "relationship set."Entity relationship model is also known as ER model.

3. Object-based Data Model

A further development of the ER model that incorporates concepts of object identification, encapsulation, and functions. A rich type system, comprising collection and structural types, is supported by this architecture. Thus, a variety of object-oriented database systems were created in the 1980s. The objects are nothing more than the data that contains their attributes.

4. Semi-structured  Data Model

The other three types of data models (described above) are not the same as this one. In situations when multiple data objects of the same kind may have distinct sets of attributes, the semistructured data model permits the data specifications. One popular tool for encoding semistructured data is XML, or Extensible Markup Language. While XML was originally intended to be used for adding markup information to text documents, its use in data sharing has made it more significant.