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 monitoring 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 realtime with limited disk space usage. The validation has demonstrated the advantage of tsdb over traditional approaches, and has shown that tsdb is suitable for handling a large number of time series.

tsdb: A Compressed Database for Time Series

Deri;Luca;
2012

Abstract

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 monitoring 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 realtime with limited disk space usage. The validation has demonstrated the advantage of tsdb over traditional approaches, and has shown that tsdb is suitable for handling a large number of time series.
2012
Istituto di informatica e telematica - IIT
Inglese
Traffic Monitoring and Analysis
4th International Workshop on Traffic Monitoring and Analysis, TMA 2012
143
156
14
Springer
Berlin
GERMANIA
Sì, ma tipo non specificato
12 March 2012
Vienna, Austria
web-based data visualisation
time series
ID_PUMA; /cnr.iit/2012-A2-057
6
none
Deri, Luca; Deri, Luca; Mainardi, ; Simone, ; Fusco, ; Francesco,
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/128346
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