Merge sort is the best sorting algorithm to use for arrays with more than 1 million elements.

Introduction:
Sorting algorithms are an essential part of computer science and are used to arrange elements in a specific order. When dealing with large arrays, the choice of sorting algorithm becomes crucial as it can significantly impact the performance and efficiency of the sorting process.

Comparison of Sorting Algorithms:
To determine the best sorting algorithm for arrays with more than 1 million elements, let's compare some popular sorting algorithms:

1. Bubble Sort:
- Bubble sort is a simple and inefficient algorithm.
- It has a time complexity of O(n^2), making it highly inefficient for large arrays.
- It compares adjacent elements and swaps them if they are in the wrong order.
- Bubble sort is not suitable for large arrays as it takes a long time to complete.

2. Insertion Sort:
- Insertion sort is an efficient algorithm for small arrays but not suitable for large arrays.
- It has a time complexity of O(n^2) in the worst case.
- It builds the final sorted array one element at a time by inserting each element into its proper position.
- Insertion sort performs well for small arrays but becomes slower as the array size increases.

3. Quick Sort:
- Quick sort is a popular sorting algorithm known for its efficiency and average-case performance.
- It has an average-case time complexity of O(n log n).
- Quick sort follows the divide-and-conquer approach, partitioning the array into smaller sub-arrays and recursively sorting them.
- However, quick sort's worst-case time complexity is O(n^2), which can occur when the pivot selection is inefficient.
- In practice, quick sort is usually efficient and widely used.

Merge Sort:
- Merge sort is a divide-and-conquer algorithm known for its stability, efficiency, and consistent performance.
- It has a time complexity of O(n log n), making it efficient for large arrays.
- Merge sort divides the array into two halves, recursively sorts them, and then merges the sorted halves to obtain the final sorted array.
- It guarantees both stability and a consistent time complexity, regardless of the input distribution.
- Merge sort is suitable for large arrays as it performs well even with a large number of elements.
- The only drawback of merge sort is its space complexity, as it requires additional memory for merging sub-arrays.

Conclusion:
Considering the efficiency, consistency, and stability, merge sort is the best sorting algorithm to use for arrays with more than 1 million elements. It provides a consistent time complexity of O(n log n) and is well-suited for large arrays. While other sorting algorithms like quick sort may also be efficient in practice, merge sort guarantees consistent performance and stability.