Time Series Data Management for Database Autonomous Services

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Time series data plays a vital role in enabling efficient database operations and autonomous management. Applying time series management techniques such as storage optimization, anomaly detection, and forecasting to database-related time series data (e.g., performance metrics and SQL logs) can significantly enhance system automation and reduce labor costs. This presentation reviews recent research, providing theoretical foundations and practical guidance to advance time series data management for autonomous database systems.


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  • Contact Event Host

  • Tianyi Li

    tianyi@cs.aau.dk

  • Co-sponsored by Sean Bin Yang

  Speakers

Yuanyuan of Department of Computer Science, Aalborg University

Topic:

Time Series Data Management for Database Autonomous Services

Time series data plays a vital role in enabling efficient database operations and autonomous management. Applying time series management techniques such as storage optimization, anomaly detection, and forecasting to database-related time series data (e.g., performance metrics and SQL logs) can significantly enhance system automation and reduce labor costs. This presentation reviews recent research, providing theoretical foundations and practical guidance to advance time series data management for autonomous database systems.
 

Biography:

Yuanyuan is in the third year of her PhD. Her research focuses on time series data management. As the first author, she has published more than five papers in ICORE A* conferences and prestigious journals, including SIGMOD, PVLDB, ICDE, and ICML.

Email:

Address: 866 Yuhangtang Rd, Xihu, Hangzhou, , Zhejiang, China, 310027