When to use different Sorting in Data Structures?

Introduction

Do you seek a better understanding of sorting algorithms in data structures? You’re at the right place! We’re here to introduce you to sorting in data structures, walk you through the various types of sorting algorithms there are, and discuss when to use them and the benefits of using them in data structures.

To understand how sorting is done, first we need to comprehend what data structures are all about.

What is Sorting in Data Structures?

Data Structures, the foundation of modern computing, are means of organizing data so it can be comfortably accessed everywhere from search engines to databases and banking systems and artificial intelligence.

Sorting is a crucial part of these data structures as it permits you to store and retrieve information effectively. To perform this, data must be sorted into a particular order such as numerically or alphabetically. Here, sorting algorithms come in.

Also Read: Data Engineering Preparation Strategies

Types of Sorting in Data Structures?

Sorting in data structures algorithms work as a vital part of your data structure toolbox when you are a programmer. To assist you, we have provided a brief guide to various sorting algorithms below - 

1. Bubble Sort

2. Selection Sort

3. Insertion Sort

4. Quick Sort

5. Merge Sort

6. Radix/Bucket Sort

7. Counting Sort

8. Heap Sort

When to Use Different Sorting in Data Structures?

There are multiple algorithms available to choose from when it comes to data sorting. So let’s understand each algorithm and when to use them.

When dealing with small datasets, selection sort serves as a great choice. 

Bubble Sort also poses a good choice for small datasets and it performs better than Selection Sort on smaller datasets. 

Insertion sort is particularly effective when dealing with almost sorted arrays and serves as another popular sorting method. 

Merge Sort works by dividing an array into two halves recursively until single elements are created and then building back to the original array by comparing each element to its adjacent element(s). 

We should consider, when dealing with sorting data, which algorithm suits best depending on our data size, efficiency requirements or memory constraints related to almost sorted arrays.

Source: https://www.datatrained.com/post/sorting-in-data-structures/