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Current Systems for Managing Massive High Frequency Time Series

par Abduvakhobov, Abduvoris ;Jensen, Søren Kejser;Thomsen, Christian;Zimanyi, Esteban
Référence Data Engineering for Data Science, Springer Nature, page (111-140)
Publication Publié, 2026-01

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Résumé :

Manufacturers and owners use high-frequency sensor data to optimize energy production. Data is collected on the edge (i.e., wind turbines) and transferred to the cloud for analytics. General-purpose RDBMSs are unable to handle the volume and velocity of sensor data. As a remedy, Time Series Management Systems (TSMSs) have been offered to manage sensor data across the entire pipeline efficiently. This chapter surveys TSMSs developed through academic or industrial research and doc-umented through peer-reviewed papers. The chapter uses classification criteria for surveying systems by architecture, year, primary purpose, deployment, maturity, scale shown, data processing engine, API, approximation, latency, data store and storage layout. A collection of open research problems is provided based on the surveyed systems.