论文标题
时间序列数据库的绩效研究
Performance Study of Time Series Databases
论文作者
论文摘要
大数据领域（例如物联网）的增长会产生大量数据。当物联网设备生成大量的时间序列数据时，时间序列数据库（TSDB）的受欢迎程度随着物联网的兴起而增长。时间序列数据库是为了管理和分析大量时间序列数据的开发。但是，从他们那里选择最好的选择并不容易。最受欢迎的基准测试结果将不同数据库的性能相互比较，但使用仅适用于一个域的随机或合成数据。结果，这些基准可能并不总是准确地代表现实世界的性能。需要将时间序列数据库的性能与真实数据集进行全面比较。该实验显示了比较实际和合成数据集时数据注入时间和查询执行时间的显着性能差异。报告并分析结果。
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.
