Linear Vs Non-linear Data Structures: Key Differences
The data structure is a method of organizing and storing data and info in a way that a user can utilize them efficiently. In computer science, the data structure is composed in a way that it works with various algorithms. It has two broad categories:
- Linear Data Structure
- Non-Linear Data Structure
What is a Linear Data Structure?
It is a type of Data Structure where the data elements get linearly or sequentially arranged. The elements attach themselves to their next and previous adjacents. The structure involves only a single level- allowing a user to traverse all its components in a single run.
The linear data structure is very easy to understand and implement due to its linear arrangement, for example, stack, array, linked list, queue, etc.
What Is a Non-Linear Data Structure?
It is a form of data structure where the data elements don’t stay arranged linearly or sequentially. Since the data structure is non-linear, it does not involve a single level. Therefore, a user can’t traverse all of its elements in a single run.
The non-linear data structure is not very easy to implement as compared to the linear data structure. The utilization of computer memory is more efficient in this case, for example, graphs and trees.
Difference Between Linear and Non-linear Data Structures
| Parameter | Linear Data Structure | Non-Linear Data Structure |
| Arrangement of Data Element | In a linear data structure, the data elements connect to each other sequentially. A user can transverse each element through a single run. | In a non-linear data structure, the data elements connect to each other hierarchically. Thus, they are present at various levels. |
| Complexity of Implementation | The linear data structures are comparatively easier to implement. | The non-linear data structures are comparatively difficult to implement and understand as compared to the linear data structures. |
| Levels | A user can find all of the data elements at a single level in a linear data structure. | One can find all the data elements at multiple levels in a non-linear data structure. |
| Traversal | You can traverse a linear data structure in a single run. | It is not easy to traverse the non-linear data structures. The users need multiple runs to traverse them completely. |
| Utilization of Memory | It is not very memory-friendly. It means that the linear data structures can’t utilize memory very efficiently. | The data structure is memory-friendly. It means that it uses memory very efficiently. |
| Complexity of Time | The time complexity of this data structure is directly proportional to its size. It means that the time complexity increases with increasing input size. | Non-linear data structure’s time complexity often remains the same with an increase in its input size. |
| Applications | Linear data structures work well mainly in the development of application software. | Non-linear data structures work mainly well in image processing and Artificial Intelligence. |
| Examples | List, Array, Stack, Queue. | Map, Graph, Tree. |
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