Managing Massive Time Series Streams with Multi-Scale Compressed Trickles
Summary: Cypress uses multi-scale decomposition to produce sparse time and frequency-domain representations for massive streams. Queries like trend and correlations run on compressed data, enabling analytics with storage savings; validated on data-center traces. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Galen Reeves (University of California Berkeley)
- 2. Jie Liu (Microsoft)
- 3. Suman Nath (Microsoft)
- 4. Feng Zhao (Microsoft)
BibTeX Citation
@article{reeves_vldb09,
title = {{Managing Massive Time Series Streams with Multi-Scale Compressed Trickles}},
author = {Reeves, Galen and Liu, Jie and Nath, Suman and Zhao, Feng},
journal = {PVLDB},
series = {{VLDB} '09},
doi = {10.14778/1687627.1687639},
url = {https://doi.org/10.14778/1687627.1687639},
year = {2009}
}Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,792 | Fast Approximate Correlation for Massive Time-series Data | 2010 | SIGMOD | 9.6238255e-05 |
| 3,434 | Finding Semantics in Time Series | 2011 | SIGMOD | 7.3027739e-05 |
| 3,879 | RobustPeriod: Robust Time-Frequency Mining for Multiple Periodicity Detection | 2021 | SIGMOD | 6.9511324e-05 |
| 7,890 | TSCache: An Efficient Flash-based Caching Scheme for Time-series Data Workloads | 2021 | VLDB | 5.4328058e-05 |
| 9,448 | DataGarage: Warehousing Massive Performance Data on Commodity Servers | 2010 | VLDB | 5.1754762e-05 |
| 11,315 | Improving Time Series Data Compression in Apache IoTDB | 2025 | VLDB | 4.9793485e-05 |
| 12,762 | Parsimonious Linear Fingerprinting for Time Series | 2010 | VLDB | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 10 of 10 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 127 | The Design of the Borealis Stream Processing Engine | 2005 | CIDR | 0.00030427614 |
| 678 | StatStream: Statistical Monitoring of Thousands of Data Streams in Real Time | 2002 | VLDB | 0.00014838454 |
| 742 | Dynamic Multidimensional Histograms | 2002 | SIGMOD | 0.0001431602 |
| 1,173 | Wavelet Synopses with Error Guarantees | 2002 | SIGMOD | 0.00011686985 |
| 1,278 | Streaming Pattern Discovery in Multiple Time-Series | 2005 | VLDB | 0.00011231952 |
| 1,456 | Querying Continuous Functions in a Database System | 2008 | SIGMOD | 0.00010589614 |
| 3,452 | BRAID: Stream Mining through Group Lag Correlations | 2005 | SIGMOD | 7.2907083e-05 |
| 3,702 | Identifying Representative Trends in Massive Time Series Data Sets Using Sketches | 2000 | VLDB | 7.0842822e-05 |
| 3,784 | Database-friendly Random Projections | 2001 | PODS | 7.0223112e-05 |
| 7,553 | GAMPS: Compressing Multi Sensor Data by Grouping and Amplitude Scaling | 2009 | SIGMOD | 5.4980306e-05 |
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| 1 | 13,994 | Theory of Data Stream Computing: Where to Go | 2011 | PODS |
| 2 | 11,315 | Improving Time Series Data Compression in Apache IoTDB | 2025 | VLDB |
| 3 | 3,702 | Identifying Representative Trends in Massive Time Series Data Sets Using Sketches | 2000 | VLDB |
| 4 | 6,694 | MOST: Model-Based Compression with Outlier Storage for Time Series Data | 2023 | SIGMOD |
| 5 | 4,662 | Time Series Compressibility and Privacy | 2007 | VLDB |
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| 7 | 2,208 | Multi-Dimensional Regression Analysis of Time-Series Data Streams | 2002 | VLDB |
| 8 | 928 | A Framework for Clustering Evolving Data Streams | 2003 | VLDB |
| 9 | 1,347 | Chimp: Efficient Lossless Floating Point Compression for Time Series Databases | 2022 | VLDB |
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