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tsdb: A Compressed Database for Time Series

Large-scale network monitoring systems require efficient storage and consolidation of measurement data. Relational databases and popular tools such as the Round-Robin Database show their limitations when handling a large number of time series. This is because data access time greatly increases with the cardinality of data and number of measurements. The result is that monitor- ing systems are forced to store very few metrics at low frequency in order to grant data access within acceptable time boundaries.

This paper describes a novel compressed time series database named tsdb whose goal is to allow large time series to be stored and consolidated in real- time with limited disk space usage. The validation has demonstrated the advan- tage of tsdb over traditional approaches, and has shown that tsdb is suitable for handling a large number of time series. 

 


TMA 2012, Vienna, 2012

Autori esterni: Francesco Fusco (IBM Zürich Research Laboratory, Rüschlikon, Switzerland)
Autori IIT:

Simone Mainardi

Foto di Simone Mainardi

Tipo: Articolo in Atti di convegno internazionale
Area di disciplina: Computer Science & Engineering

File: tsdb.pdf