A comparative study between the capabilities of MySQL and ClickHouse in low-performance Linux environment

Abstract

Fast, reliable, and secure data processing is critical in the Information Technology (IT) sector as it is an indispensable requirement of all the growing technologies. Achieving this requires handling large amounts of data and massive computing power. Emerging technologies use devices under low-performance environments, such as raspberry-pi, which require highly efficient databases under low computing power. Inappropriate selection of databases leads to considerable resource wastage in numerous ways, such as waste of time, cost, and energy. The selection of a reliable, userfriendly database compatible with low-performance environments will downplay the energy requirement and cut down applications' carbon footprint. Thus, this study was conducted to compare the performance and query cost of using ClickHouse and MySQL databases as column-oriented and roworiented databases in a low-performance environment. The effectiveness of using column-oriented or row-oriented databases with large amounts of data at different platforms was analyzed. The study was conducted by running different queries using an automated PHP script and checking the execution time, processing power, disk I/O, and memory usage for each query. The study was conducted with a virtual Linux environment of 1024MB RAM, 1.8Ghz single processor, and 25Gb storage, representing very low computing power, even lesser than the recommended minimum requirement of ClickHouse and MySQL databases. Both databases performed well in the above mentioned environment. Our experimental results show that ClickHouse execution time and disk write speed is tremendously low compared to MySQL. To obtain this performance, ClickHouse used more CPU processing power and memory utilization than MySQL.