Record-Based Data Model

Data Model is the model that organizes elements of the data and tell how they relate to one-another and with the properties of real-world entities. The basic purpose of the data model is to make sure that the data stored in the data model is understood fully.

Further, it has three types-

1. Physical Data Model, 
2. Record-Based Data Model,
3. Object-Oriented Data Model 

Physical Data Model is not used much nowadays. In this, we will study about the Record-Based Data Model in detail.

Record-Based Data Model :
When the database is organized in some fixed format of records of several than the model is known as Record-Based Data Model. It has a fixed number of fields or attributes in each record type and each field is usually of a fixed length.

Further, it is classified into three types-

1. Hierarchical Data Model :
   In hierarchical type, the model data are represented by collection of records. In this, relationships among the data are represented by links. In this model, tree data structure is used.

   It was developed in 1960s by IBM, to manage large amount of data for complex manufacturing projects. The basic logic structure of hierarchical data model is upside-down “tree”.

   

   Advantages –
   Simplicity, Data Integrity, Data security, Efficiency, Easy availability of expertise.

   Disadvantages –
   Complexity, Inflexibility, Lack of Data Independence, Lack of querying facility, Data Manipulation Language, Lack Of standards.

2. Network Data Model :
   In network type, the model data are represented by collection of records. In this, relationships among the data are represented by links. Graph data structures are used in this model. It permits a record to have more than one parent.

   For Example- Social Media sites like Facebook, Instagram etc.

   

   Advantages –
   Simplicity, Data Integrity, Data Independence, Database standards.

   Disadvantages –
   System Complexity, Lack of structural Independence.

3. Relational Data Model :
   Relational Data Model uses tables to represent the data and the relationship among these data. Each table has multiple columns and each column is identified by a unique name. It is a low-level model.

   

   Advantages –
   Structural Independence, Simplicity, Ease of designing, Implementation, Ad-Hoc query capability.

   Disadvantages –
   Hardware Overheads, Ease of design can result in bad design.