@inproceedings{b6eb61e87781443eb4dfee868d1828c1,
title = "A Comparison of Relational, NoSQL and NewSQL Database Management Systems for the Persistence of Time Series Data",
abstract = "Time series data is created in a variety of application areas such as sensors in cars, smartwatches or IoT devices. This kind of data is often characterized by high resource demand due to the frequency the information is measured, with data points once a day, hour and even down to milliseconds. While real-time processing of such data is often sufficient, there are also many use cases, where batch processing and consequently the storage and managed access of measurements is required. For this reason, this work evaluates different database management systems in the context of storing time related data using different data models such as classical relational models, non-relational models using NoSQL database systems and the recently upcoming group of NewSQL databases. The evaluation shows that a highly optimized time series databases such as InfluxDB is able to outperform the other tested systems regarding write-throughput and RAM as well as disk utilization in a single server setup.",
keywords = "Big Data, Database, SQL, Time Series",
author = "Christoph Praschl and Sebastian Pritz and Oliver Krauss and Martin Harrer",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2022 ; Conference date: 16-11-2022 Through 18-11-2022",
year = "2022",
doi = "10.1109/ICECCME55909.2022.9988333",
language = "English",
series = "International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2022",
address = "United States",
}
