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MOST: Model-Based Compression with Outlier Storage for Time Series Data
Summary: MOST: model-based time-series compression with explicit outlier storage; segments fit linear models for smooth changes. Segment-outlier dual-mode query engine enables segment-wise processing; MOSTDB shows 9.45–15.04x compression and up to 11.68x IoTDB speedups.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 6753
- Venue
- SIGMOD
- Year
- 2023
- Pagerank
- 4.737456e-05
- Overall Rank
- 7,392 | 48.63%
- DOI
-
10.1145/3626737
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 22 of 22 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 14 |
Online Aggregation |
1997 |
SIGMOD |
0.0010813443 |
| 28 |
Accurate Estimation Of The Number Of Tuples Satisfying A Condition |
1984 |
SIGMOD |
0.00080571183 |
| 46 |
Simple Random Sampling from Relational Databases |
1986 |
VLDB |
0.00071588702 |
| 101 |
The Case for Learned Index Structures |
2018 |
SIGMOD |
0.00049778866 |
| 211 |
Gorilla: A Fast, Scalable, In-Memory Time Series Database |
2015 |
VLDB |
0.0003401421 |
| 328 |
Balancing Histogram Optimality and Practicality for Query Result Size Estimation |
1995 |
SIGMOD |
0.00027301497 |
| 468 |
MauveDB: Supporting Model-based User Views in Database Systems |
2006 |
SIGMOD |
0.00022407392 |
| 819 |
ALEX: An Updatable Adaptive Learned Index |
2020 |
SIGMOD |
0.00016237497 |
| 821 |
Dimensionality Reduction for Similarity Searching in Dynamic Databases |
1998 |
SIGMOD |
0.00016232579 |
| 1,365 |
FITing-Tree: A Data-aware Index Structure |
2019 |
SIGMOD |
0.00012379754 |
| 1,567 |
Querying Continuous Functions in a Database System |
2008 |
SIGMOD |
0.00011320794 |
| 1,925 |
Apache IoTDB: Time-series Database for Internet of Things |
2020 |
VLDB |
0.00010073156 |
| 2,032 |
SAND: Streaming Subsequence Anomaly Detection |
2021 |
VLDB |
9.7320795e-05 |
| 2,274 |
ModelarDB: Modular Model-Based Time Series Management with Spark and Cassandra |
2018 |
VLDB |
9.1432785e-05 |
| 2,583 |
Sample + Seek: Approximating Aggregates with Distribution Precision Guarantee |
2016 |
SIGMOD |
8.4973431e-05 |
| 2,619 |
Decomposed Bounded Floats for Fast Compression and Queries |
2021 |
VLDB |
8.4427442e-05 |
| 3,801 |
Plato: Approximate Analytics over Compressed Time Series with Tight Deterministic Error Guarantees |
2020 |
VLDB |
6.7528979e-05 |
| 3,971 |
Apache IoTDB: A Time Series Database for IoT Applications |
2023 |
SIGMOD |
6.5733348e-05 |
| 4,086 |
The Case for a Learned Sorting Algorithm |
2020 |
SIGMOD |
6.4579358e-05 |
| 4,253 |
Combining Databases and Signal Processing in Plato |
2015 |
CIDR |
6.3103785e-05 |
| 6,311 |
VergeDB: A Database for IoT Analytics on Edge Devices |
2021 |
CIDR |
5.1112212e-05 |
| 8,216 |
Mining Deviants in a Time Series Database |
1999 |
VLDB |
4.5522552e-05 |
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