A sorting algorithm is a mathematical or logarithmic equation that organizes data structures in a computer program so that the system searches and finds data more efficiently. Many different sorting algorithms exist, and they’re based on different conditions and categories. Some sorting algorithms, due to what they prioritize, are better for different data arrays and situations than others. For instance, one algorithm may be much faster at sorting than another, but it’s also less stable, meaning that it will not keep a structure closest to its relative location to another structure. A slower algorithm (one that takes more time to sort through data) wouldn’t find things as quickly, but it might be more stable.
In sorting, time complexity is based on how many operations or actions (how much time) it takes to locate or arrange data structures in a search. Some types of algorithms are more efficient than others for searching. The letter O is used to indicate the time complexity component of sorting. The number of operations required to sort a data array does make a difference in search efficiency, especially if the system is searching through a large data pool.
Space complexity, on the other hand, is the amount of system power or memory an algorithm requires to run on the computer. This is also sometimes represented by O. There are mathematical ways to calculate the amount of computational memory required for a specific sorting algorithm.
Types of sorting algorithms
A wealth of sorting algorithms are available to database users. We’ve listed just a few:
- Quick sort divides data into shorter arrays and sorts through them faster than going through just one list
- Merge sort first splits the data array into two distinct arrays and sorts each half, then merges the data structures back into a single organized array
- Insertion sort checks each structure (or item) one by one and moves it into position in the new order by comparing it to each other sequential structure