How do common sorting algorithms compare?

The right sorting algorithm depends on constraints. Do you need stability? Is memory tight? Is the data nearly sorted? Is worst-case latency unacceptable? Interviewers usually want the trade-offs, not a memorised table.

The comparison

• Insertion sort: O(n^2) worst, O(n) on nearly sorted data, stable, in-place
• Merge sort: O(n log n) always, stable, O(n) extra space
• Quicksort: O(n log n) average, O(n^2) worst, in-place, not stable
• Heapsort: O(n log n) always, in-place, not stable
• Counting sort: O(n + k) for a bounded integer range, not comparison-based

const people = [
  { name: "Asha", age: 31 },
  { name: "Ravi", age: 25 },
  { name: "Meera", age: 31 },
];

people.sort((a, b) => a.age - b.age);

Stability means equal elements keep their original relative order. That matters when you sort by one field after sorting by another, or when the display order of ties is meaningful. The lower bound for comparison sorting is O(n log n) because there are n! possible orderings.