Abstract
In the era of digitization, where data is collected in ever-increasing quantities, efficient processing is required. The article analyzes the performance of SQL and HiveQL, for scenarios of varying complexity, focusing on the execution time of individual queries. The tools used in the study are also discussed. The results of the study for each language are summarized and compared, highlighting their strengths and weaknesses, as well as identifying their possible areas of application.
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