Quick Sort vs Merge Sort

Despite identical average complexity, Quick Sort typically runs 2-3x faster on in-memory arrays. It sorts in place with sequential memory access, so data stays in CPU cache, and its inner loop is tighter. Merge Sort's O(n) buffer causes cache misses and allocation overhead. Read the deep dive in why Quick Sort is faster.

Merge Sort wins when you need stability, a guaranteed O(n log n) worst case, or are sorting linked lists (which it handles with O(1) extra space). It is also the basis of external sorting for data too big for RAM, because it streams data sequentially. That reliability is why Java uses it for objects.

For general in-memory array sorting, Quick Sort (or its hybrid Introsort) is the practical winner. When stability or worst-case guarantees matter, choose Merge Sort (or its hybrid Tim Sort). Most standard libraries actually use these hybrids. Watch both run side by side in the visualizer.

Both algorithms are O(n log n) on average, so complexity alone cannot explain why Quick Sort is the one most standard libraries reach for on primitive arrays. Three practical factors do.

Cache locality. This is the big one. Quick Sort's partition step walks inwards from both ends of a contiguous block of memory, touching addresses that are near each other. Modern CPUs load memory in cache lines and aggressively prefetch sequential access, so almost every read Quick Sort makes is already in cache. Merge Sort, by contrast, streams between two source regions and a separate destination buffer, which means more cache misses and more memory traffic for the same number of comparisons.

No allocation. Quick Sort rearranges the array it was given. Merge Sort needs an O(n) buffer, and allocating it costs time, touches fresh pages, and doubles the memory footprint of the sort. For a large array that allocation alone can be a measurable fraction of the total runtime.

Smaller constant factors. The inner loop of partitioning is about as cheap as a loop gets: compare, maybe swap, move a pointer. Merging carries more bookkeeping per element — bounds checks on two runs, plus the copy back. Big-O deliberately discards these constants, but on real hardware they are what you actually wait for.

The caveat that matters. None of this makes Quick Sort the better default for every case. It is unstable and its worst case is O(n²), so if you are sorting objects by one field after another, or you cannot tolerate an unpredictable tail latency, Merge Sort's guarantees are worth more than Quick Sort's speed. That is precisely why Java uses dual-pivot Quick Sort for primitives and a Merge Sort derivative for objects — the same library making opposite choices for good reasons.