A Comparison of Time Series Databases for Storing Water Quality Data. Fadhel, M., Sekerinski, E., & Yao, S. In Auer, M. & Tsiatsos, T., editors, Mobile Technologies and Applications for the Internet of Things, IMCL 2018, volume 909, of Advances in Intelligent Systems and Computing, pages 302–313, April, 2019. Springer.
A Comparison of Time Series Databases for Storing Water Quality Data [pdf]Paper  doi  abstract   bibtex   4 downloads  
Water quality is an ongoing concern and wireless water qual- ity sensing promises societal benefits. Our goal is to contribute to a low- cost water quality sensing system. The particular focus of this work is the selection of a database for storing water quality data. Recently, time series databases have gained popularity. This paper formulates criteria for comparison, measures selected databases and makes a recommendation for a specific database. A low-cost low-power server, such as a Raspberry Pi, can handle as many as 450 sensors’ data at the same time by using the InfluxDB time series database.

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