时间序列数据库管理:技术、系统与展望

Management of Time Series Database:Technology,System and Prospect

传统时间序列数据库(时序数据库)存在数据吞吐量低、数据压缩率低、适用性不佳等局限性,提高海量数据写入效率、降低数据压缩成本、有效支持时序数据统计分析等成为重大挑战。探讨了利用时序数据库管理系统应对上述问题的关键技术。结合现有时序数据库管理系统在部分工业领域中的应用及关注度趋势,对其未来发展方向进行了展望:加强聚集计算能力,提高分布式架构柔性,研发参数自主调优技术,推进系统向新型存储设备和处理器移植。

Traditional time series database(TSDB)has some limitations,such as low data throughput,low data compression rate,poor applicability,etc.It becomes a major challenge to improve the writing efficiency of massive data,reduce the data compression cost,and effectively support the statistical analysis of time series data.The key technologies of using time series database management system to deal with the above problems were discussed.Combined with the application and attention trend of the existing time series database management system in some industrial fields,the future development directions of time series database were prospected:strengthening the ability of aggregation computing,improving the flexibility of distributed architecture,researching and developing the technology of parameter self-tuning,transplanting to new storage devices and processors,etc.