Sorting algorithms have strengths and weaknesses: memory usage, number of comparisons, varying performance in edge cases, multithreading capability, ease of implementation, etc. This means that there is usually some algorithm or a variation of one that fits your specific use case and available resources better than most or all other algorithms. An algorithm that performs marginally better than another can save minutes, hours, or days of data processing on ginormous amounts of data.
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