Extreme-Scale Model-Based Time Series Management with ModelarDB (Invited Talk)

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To monitor critical industrial devices such as wind turbines, high quality sensors sampled at a high frequency are increasingly used. Current technology does not handle these extreme-scale time series well [Søren Kejser Jensen et al., 2017], so only simple aggregates are traditionally stored, removing outliers and fluctuations that could indicate problems. As a remedy, we present a model-based approach for managing extreme-scale time series that approximates the time series values using mathematical functions (models) and stores only model coefficients rather than data values. Compression is done both for individual time series and for correlated groups of time series. The keynote will present concepts, techniques, and algorithms from model-based time series management and our implementation of these in the open source Time Series Management System (TSMS) ModelarDB[Søren Kejser Jensen et al., 2018; Søren Kejser Jensen et al., 2019; Søren Kejser Jensen et al., 2021] . Furthermore, it will present our experimental evaluation of ModelarDB on extreme-scale real-world time series, which shows that that compared to widely used Big Data formats, ModelarDB provides up to 14× faster ingestion due to high compression, 113× better compression due to its adaptability, 573× faster aggregatation by using models, and close to linear scale-out scalability. ModelarDB is being commercialized by the spin-out company ModelarData.
Original languageEnglish
Title of host publication28th International Symposium on Temporal Representation and Reasoning, TIME 2021, September 27-29, 2021, Klagenfurt, Austria.
PublisherSchloss Dagstuhl. Leibniz-Zentrum für Informatik
Publication dateSept 2021
ISBN (Electronic)978-3-95977-206-8
Publication statusPublished - Sept 2021
Event28th International Symposium on Temporal Representation and Reasoning, TIME 2021 - Alpen-Adria University, Klagenfurt, Austria
Duration: 27 Sept 202129 Sept 2021
Conference number: 28


Conference28th International Symposium on Temporal Representation and Reasoning, TIME 2021
LocationAlpen-Adria University
SeriesLeibniz International Proceedings in Informatics

Bibliographical note

This work has been funded by Innovation Fund Denmark (the DiCyPS project), Independent Research Fund Denmark (the SEMIOTIC project) and Horizon 2020 (the MORE project).


  • Model-based storage
  • approximate query processing
  • time series management
  • extreme-scale data


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