Difference between Network and Relational data model

Last Updated : 12 Sep, 2024

Data models specify the organization, archiving, and manipulation of data in database management systems (DBMSs). The Network Data Model and the Relational Data Model are two popular forms of data models. Each of these models has distinct characteristics, benefits, and uses for organizing and managing data in a variety of ways. To assist you in comprehending the distinctive qualities of the network and relational data models, we’ll examine the main distinctions between them in this post.

What is a Network Data Model?

It is the advanced version of the hierarchical data model. To organize data it uses directed graphs instead of tree-structure. In this, a child can have more than one parent. It uses the concept of two data structures i.e., Records and Sets.

Characteristics of the Network Data Model

Graph Structure: Uses directed graphs to organize data, allowing multiple relationships between records.
Many Parent Nodes: Having more than one parent allows for more intricate ties to exist amongst children.
Physical Representation: Pointers or linked lists are used to physically represent the relationships between data.
Data Structures: Data structures are defined using sets (relationships) and records (nodes).

Advantages of the Network Data Model

Flexible Relationships: Supports many-to-many relationships, allowing complex data connections.
Effective Searching: Finding a data item via many access pathways is an efficient way to search.
No Inconsistency in Updates: Issues with consistency are avoided via single-instance child records.

Disadvantages of the Network Data Model

Complex Design: Increases complexity for database design and data manipulation.
Limited Querying Capabilities: In contrast to contemporary models, there are no declarative querying options.
Provides only a limited degree of data independence since modifications to the physical structure might have an impact on the application.

Network data model

In the above figure, Project is root node which has two children i.e. Project 1 and Project 2. Project 1 has 3 children and Project 2 has 2 children. Total there are 5 children i.e Department A, Department B and Department C, they are network related children as we said that this model can have more than one parent. So, for Department B and Department C have two parents i.e. Project 1 and Project 2.

What is a Relational Data Model?

The relational data model was developed by E.F. Codd in 1970. There are no physical links as they are in hierarchical data model. Following are properties of relational data model :

Data is represented in form of table only.
It deals only with data not with physical structure.
It provides information regarding metadata.
At the intersection of row and column there will be only one value for tuple.
It provides a way to handle queries with ease.

Characteristics of the Relational Data Model

Tabular Structure: Organizes data in tables, making it easy to understand and manage.
Declarative Querying: Provides strong SQL query capabilities.
Logical Representation: Tables and keys are used to logically express relationships between records.
High degree of data independence is provided by this method, which keeps the logical schema and the physical storage apart.

Advantages of the Relational Data Model

Simple Create: The tabular structure makes it simple to create and comprehend.
Declarative Querying: Offers powerful SQL querying features.
Data Independence: The logical data model remains unaffected by changes made to the physical data storage.
Normalizing: By reducing duplication, normalizing enhances data integrity.

Disadvantages of the Relational Data Model

Performance Overhead: Normalization may result in performance overhead.
The Ability to Scale Limits: For best results, large-scale applications would need more fine-tuning.

Relational Data model

Differences Between Network Data Model and Relational Data Model

Network Data Model	Relational Data Model
It organizes records to one another through links or pointers.	It organizes records in form of table and relationship between tables are set using common fields.
It organizes records in form of directed graphs.	It organizes records in form of tables.
In this relationship between various records is represented physically via linked list.	In this relationship between various records is represented logically via tables.
There is lack of declarative querying facilities.	It provides declarative query facility using SQL.
Complexity increases burden on programmer for database design as well as data manipulation.	As physical level details are hidden from end users so this model is very simple to understand.
Retrieval algorithms are complex but symmetric.	Retrieval algorithms are simple and symmetric.
There is partial data independence in this model.	This model provides data independence.
There is no inconsistency problem in updating the records because of the single instance of the child records.	The updating of records is quite easy because of the normalization which is used to remove the redundancy in the relations.
Searching for a record is easy in the network model as there are multiple access paths to reach data item.	In the relational model, a unique, indexed key serves the purpose of searching a record.
Here, is the physical existence of record relations in this model.	It maintains logical organization of records using rows and columns and stored in relation.
VAX-DBMS, DMS-1100 of UNIVAC and SUPRADBMS’s use this model.	It is mostly used in real world applications. Oracle, SQL.

Conclusion

The Relational Data Model and the Network Data Model provide several approaches to managing and arranging data. The network model, which uses directed graphs and physical pointers, is ideal for complex many-to-many interactions, although being more complex to construct and query. However, because of its tabular form and SQL-based querying, the relational model—which is often used in modern applications—offers simplicity, data independence, and strong querying capabilities. Which model is optimal depends on the specific requirements of the database system and its use case.

Difference between Hierarchical and Network Data Model

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