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Difference Between Linear and Non Linear Data Structure

Introduction

A data structure is a way of arranging and storing data so that it can be retrieved and used quickly. A linear data structure is one that arranges data components in sequential order. The arrangement of linear data structures is analogous to how computer memory is organized. Nonlinear data structures are created by connecting a data element to multiple other data elements in a manner that indicates a particular connection between them. Nonlinear data structures are organized differently than computer memory.

Difference Between Linear and Non Linear Data Structure

Linear Data Structures

The data elements in linear data structures are organized in a linear form, with each data member attaching one after the other. The data elements in linear data structures travel one after the other, and only one element may be accessible directly when traversing. Furthermore, since computer memory is organized in a linear form, linear data structures are particularly simple to create.

Arrays, linked lists, stacks, and queues are some of the most popular linear data structures. An array is, first and foremost, a collection of data pieces of the same kind. Each element in the array is identified by its index. A linked list, on the other hand, is a series of nodes, each of which contains a data element and a reference to the next node in the sequence. Finally, a stack is a linear data structure as well. Only data components at the top of the list may be added or removed. Finally, a queue is a kind of list. It permits data components to be added from one end of the list and removed from the other.

Non-Linear Data Structures

The data components of nonlinear data structures are not organized in a sequential order. A data item in a nonlinear data structure may be linked to numerous other data pieces to represent a particular connection between them. Furthermore, traversing through the goods in a single run is not conceivable.

Nonlinear data structures include data structures such as trees and graphs. To begin with, a tree is a data structure made up of a series of connected nodes. It permits a hierarchical connection between data pieces to be represented. A graph, on the other hand, is a data structure made up of a limited number of edges and vertices. The data pieces are kept in the vertices, while the edges reflect the connections or interactions between the vertices.

Comparison Table Between Linear Data Structure and Non Linear Data Structure

Linear Data Structure Non-Linear Data Structure
  • The pieces are attached in a sequential or linear order here.
  • Hierarchically or non-linearly, the elements are controlled here.
  • In a linear data structure, each data and data item is inextricably linked to the others.
  • Because the data item and data are not related due to their non-sequential existence, the application executes many times.
  • This data format allows for simple data implementation.
  • This data structure contains data that is difficult and complicated.
  • A linear data structure includes arrays, linked lists, and stacks.
  • A non-linear data structure is made up of trees and graphs.
  • Memory use and consumption is extensive.
  • Because of the free data selection, memory is used extremely efficiently.
  • Linear data structures are often utilized in software development.
  • Image processing and Artificial Intelligence both employ non-linear data structures.

Conclusion

The distinction between linear and nonlinear data structures is that in linear data structures, data components are organized sequentially, but in nonlinear data structures, data elements are not organized sequentially. In summary, linear data structures are easier to implement in computer memory than nonlinear data structures. The connection between the data items that need to be saved should be considered while choosing one data structure type over the other.



About the author:
Adarsh Kumar Singh is a technology writer with a passion for coding and programming. With years of experience in the technical field, he has established a reputation as a knowledgeable and insightful writer on a range of technical topics.