Sunday 23 June 2019

Data Models in DBMS

Data model can be defined as an integrated collection of concepts that can be used to describe the logical structure of the data base. Including data types, relationships between data and constraints that should be apply on the data.
Data models are classified into two ways: Conceptual data model and Physical data model. There are two types of conceptual data models namely object oriented and record based model.

Conceptual based data models

This Data Model defines WHAT the system contains. This model is typically created by Business stakeholders and Data Architects. The purpose is to organize, scope and define business concepts and rules. There are three types of conceptual based data model
1. Hierarchical data model

The hierarchical data model was developed in 1916 to manage large amount of data for complex manufacturing projects such as "Apollo rocket". 

In hierarchical data model data is represented by an upside down tree. Its hierarchical structure contains levels or segments. A segment is the equivalent of file system record type.
The hierarchical data model is based on the three data structures that is composed of root segment, parent segment and child segments.
  1. It provides data sharing 
  2. Parent-Child relationship promotes conceptual simplicity
  1. Complex implementation requires knowledge of physical storage characteristics.
  2. There are implementation limits.
  3. There is a lack of standards 

2. Network Data model

The network data model has developed 
  • To address  the need to represent complex data relationships more efficiently than in hierarchical data model.
  • To impose a data base standard 
  • To improve the data base performance
The data on the network model is represented by the collection of records and relationships among the elements are represented by links which can be viewed as pointers.

The main differences between hierarchical and network model is that a member or member record may have several owners in network model.

  1. It handles more relationship types, such as M:N and multi parent 
  2. Data access is more flexible then in hierarchical and file system models

  1. System complexity limits efficiently still the hierarchical model.
  2. Navigational system yields complex implementations, application development and management.
3. Relational Data model

This data model uses the collection of tables to represent both data and relationships. This model is implemented by sophisticated software known as RDBMS. The table is made up of rows and columns. This model is developed by E.F. CODD's in 1970. The tables in this model are related to each other by sharing common characteristics.

  1. Structural independence is promoted by the use of independent tables. Changes in a table structure do not effect data access or application programs.
  2. Table view improves conceptual simplicity.
  3. Adhoc query capability is based in SQL.
  1. The RDBMS requires minimum hardware and system software overhead 
  2. Conceptual simplicity gives relatively untrained people the tools to use a good system poorly.
4. Entity Relational Model

Peter chin first introduced the ER model in 1976, it was the graphical representation of entities and their relationships in a database structure that quickly become popular, because its complemented the relational data model concept.

ER models are normally represented on the following components: Entity, attributes, Relationships.

ER model uses three types of relationships: one-to-one, one-to-may, many-to-may


  1. Visual modeling yields exceptional conceptual simplicity 
  2. Visual representation makes it an effective communication tool


  1. There is limited constraints representation.
  2. There is limited relationship representation.

5. Object Oriented Data Model

In object oriented data model, both data and their relationships are contained in a single structure know as an object, in turn, the object oriented data model is the basis for the object oriented database management system.

A major advantage of their data model is that complex data types like graphics, video, and sound are supported easily as simpler data types.

An object is a abstraction of a real world entity. An object may be considered equivalent to ER model entity. Attributes describe the properties of an object.


  1. Semantic content is added
  2. Visual representation includes semantic content.
  3. Inheritance promotes data integrity.


  1. It is complex navigational system
  2. High system overhead slows transactions.


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