The growth of big-data sectors such as the Internet of Things (IoT) generates enormous volumes of data. As IoT devices generate a vast volume of time-series data, the Time Series Database (TSDB) popularity has grown alongside the rise of IoT. Time series databases are developed to manage and analyze huge amounts of time series data. However, it is not easy to choose the best one from them. The most popular benchmarks compare the performance of different databases to each other but use random or synthetic data that applies to only one domain. As a result, these benchmarks may not always accurately represent real-world performance. It is required to comprehensively compare the performance of time series databases with real datasets. The experiment shows significant performance differences for data injection time and query execution time when comparing real and synthetic datasets. The results are reported and analyzed.
翻译:诸如物联网(IoT)等大数据部门的增长产生了大量的数据。由于IoT设备生成了大量的时间序列数据,随着IoT的崛起,时间序列数据库的普及程度也有所提高。开发时间序列数据库是为了管理和分析大量的时间序列数据。然而,从中选择最佳数据并不容易。最受欢迎的基准是比较不同数据库的性能,但使用只适用于一个域的随机或合成数据。因此,这些基准可能并不总是准确地代表现实世界的性能。需要用真实数据集全面比较时间序列数据库的性能。实验显示数据注入时间和查询执行时间在比较真实和合成数据集时的性能差异很大。结果被报告和分析。