Similarity-based queries for time series data
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Time series: data analysis and theory
Time series: data analysis and theory
Data Compression: The Complete Reference
Data Compression: The Complete Reference
Time Series Analysis: Forecasting and Control
Time Series Analysis: Forecasting and Control
Inverted Index Compression Using Word-Aligned Binary Codes
Information Retrieval
Super-Scalar RAM-CPU Cache Compression
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Integrating compression and execution in column-oriented database systems
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Performance tradeoffs in read-optimized databases
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
High performance algorithms for multiple streaming time series
High performance algorithms for multiple streaming time series
ATEC '99 Proceedings of the annual conference on USENIX Annual Technical Conference
iSAX: indexing and mining terabyte sized time series
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Optimal distance bounds for fast search on compressed time-series query logs
ACM Transactions on the Web (TWEB)
Specialized storage for big numeric time series
HotStorage'13 Proceedings of the 5th USENIX conference on Hot Topics in Storage and File Systems
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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.