Let us start by introducing a simple term i.e. “**sort**”. We all are known to this term. Sorting means arranging the items or elements in either ascending or descending order based on the priority of the ordering relation. Sorting a bookshelf or the data elements both is time-consuming and a mundane task. Both need a proper strategy to sort.

**Contents**show

Sorting items is an essential task for data processing. This can be related to the words that are sorted and arranged in alphabetical order in the dictionary. What if it was not sorted. In such a case, no one had ever referred to dictionaries.

A sorting algorithm is a way of arranging elements in a specific order like ascending order, descending order, numerical order, alphabetical order, lower to higher, higher to lower, etc. there is a wide range of types of sorting algorithms. In this article, we will be discussing quick sort and merge sort. Let see the key differences between Quick Sort and Merge Sort

## Difference between Quick Sort and Merge Sort in tabular form

Quick sort |
Merge Sort |

Quick Sort is a sorting algorithm mostly preferred for arrays | Merge Sort is a sorting algorithm mostly preferred for linked list |

There no such need to divide the array of elements into two parts (n/2) | In merge sort, the array of elements are divided into two parts (n/2) |

Quicksort algorithm can work with a small size of datasets | Merge sort algorithm can work with any sizes of datasets, small or large |

This algorithm requires minimum space | This algorithm requires more space |

The worst-case complexity of quicksort is O(n^{2}) |
O(n log n) is the worst-case complexity of merge sort |

Quick Sort algorithm doesn’t require any extra storage | Merge sort requires extra storage space to store the auxiliary array |

It follows the internal sorting method in which the data to be sorted is placed at the same time in the main memory | It follows the external sorting method in which the data to be sorted is not placed at the same time and is stored in the auxiliary memory |

It can be said as an unstable algorithm yet it can be made stable by modifying some changes in the code itself | It is stable as the elements are divided into two equal parts and the value is the same in sorted array as it was in unsorted array before sorting |

It is inefficient for large size of arrays | It is more efficient for both sizes of arrays |

We have seen the differences between Quick Sort and Merge Sort, now let us discuss each one of them in detail.

## What is Quick Sort?

Partition exchange sort is another name for the quick sort algorithm. This algorithm was developed by a British scientist named, Tony H. in the year 1959 and was introduced in 1961. To date, it has held its place in the sorting techniques and is known as the most efficient algorithm so far. With the correct implementation, it is a couple of times faster than the merge sort and heap sort algorithms.

This algorithm works on the divide and conquers rule. It concentrates on the central element of the array and then compares the elements whether greater or less than the pivot element. This requires less space for sorting. There is no compulsion to divide the array into two equal parts.

It is based on comparisons, less than or greater than chronology. It is not a stable sort as the relative order of either side of the pivot element is not preserved. In simple words the count of elements changes. In the worst-case scenario, the algorithm will take O (n^{2}) comparisons for sorting.

Quicksort has good average-case behaviour. Faster and speed and having a good running time complexity make it more preferable over other sorting algorithms. Since it complex and recursive, it not suggested for large-size arrays.

Let us learn further about merge sort.

## What is Merge sort?

Merge sort is also an efficient algorithm that was invented by the scientist, John Von Neumann in the year 1945. It is a general-purpose sorting algorithm based on comparison and follows the divide and conquer rule. The elements are divided into n/2 arrays and repeatedly splits the arrays until a single element is left.

As we said above that this algorithm is based on the comparison that means it sorts the by applying the less-than relation. It is said to be a stable sort meaning if two like elements have the same value then they will hold the same position after sorting as they did in the input before it was unsorted.

Let us discuss its complexity. Sorting speed always matters when we are selecting among the different sorting techniques. Running time is important to consider. Merge sort runs on O (n log n) time which is undoubtedly better than average and worst-case time complexities of other sorting algorithms.

Merge sort requires additional storage space to store the auxiliary array. It performs the sorting in a precise manner irrespective of the number of elements involved in the array or list. It is suitable for sorting large datasets and therefore consumes more space in memory.

**Author**

*Shraddha Changune*

*SVKM’s Institute of Technology, Dhule*