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ModelarDB: Modular Model-Based Time Series Management with Spark and Cassandra
Summary: Introduces ModelarDB, a modular TSMS storing time series as models for fast ingestion, compression, and online queries. Provides adaptive multi-model compression within error bounds, predicate pushdown to a key-value store, and code-generated projections on Spark/Cassandra, with graceful degradation under outliers.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 11652
- Venue
- VLDB
- Year
- 2018
- Pagerank
- 9.1519895e-05
- Overall Rank
- 2,267 | 84.24%
- DOI
-
10.14778/3236187.3236215
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 15 of 15 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 2,064 |
Chimp: Efficient Lossless Floating Point Compression for Time Series Databases |
2022 |
VLDB |
9.6418929e-05 |
| 3,286 |
Monarch: Google’s Planet-Scale In-Memory Time Series Database |
2020 |
VLDB |
7.2740159e-05 |
| 3,798 |
Plato: Approximate Analytics over Compressed Time Series with Tight Deterministic Error Guarantees |
2020 |
VLDB |
6.7592302e-05 |
| 3,967 |
Apache IoTDB: A Time Series Database for IoT Applications |
2023 |
SIGMOD |
6.5796647e-05 |
| 4,392 |
Elf: Erasing-based Lossless Floating-Point Compression |
2023 |
VLDB |
6.2257087e-05 |
| 7,395 |
MOST: Model-Based Compression with Outlier Storage for Time Series Data |
2023 |
SIGMOD |
4.7420041e-05 |
| 9,149 |
Serf: Streaming Error-Bounded Floating-Point Compression |
2025 |
SIGMOD |
4.3849295e-05 |
| 9,915 |
Camel: Efficient Compression of Floating-Point Time Series |
2024 |
SIGMOD |
4.2561557e-05 |
| 10,381 |
LCP: Enhancing Scientific Data Management with Lossy Compression for Particles |
2025 |
SIGMOD |
4.1945683e-05 |
| 10,601 |
Less is More: Efficient Time Series Dataset Condensation via Two-fold Modal Matching |
2025 |
VLDB |
4.1945683e-05 |
| 10,614 |
QPET: A Versatile and Portable Quantity-of-Interest-Preservation Framework for Error-Bounded Lossy Compression |
2025 |
VLDB |
4.1945683e-05 |
| 10,674 |
Improving Time Series Data Compression in Apache IoTDB |
2025 |
VLDB |
4.1945683e-05 |
| 10,937 |
High-performance Effective Scientific Error-bounded Lossy Compression with Auto-tuned Multi-component Interpolation |
2024 |
SIGMOD |
4.1945683e-05 |
| 11,133 |
Scalable Model-Based Management of Massive High Frequency Wind Turbine Data with ModelarDB |
2024 |
VLDB |
4.1945683e-05 |
| 13,294 |
Demonstration of ModelarDB: Model-Based Management of Dimensional Time Series |
2019 |
SIGMOD |
- |
Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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| Overall Rank |
Paper |
Year |
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| 10,379 |
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4.5867812e-05 |
| 4,824 |
Managing Massive Time Series Streams with Multi-Scale Compressed Trickles |
2009 |
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5.8947137e-05 |
| 10,674 |
Improving Time Series Data Compression in Apache IoTDB |
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4.1945683e-05 |
| 8,985 |
TSM-Bench: Benchmarking Time Series Database Systems for Monitoring Applications |
2023 |
VLDB |
4.4156106e-05 |
| 9,682 |
Lindorm TSDB: A Cloud-native Time-series Database for Large-scale Monitoring Systems |
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VLDB |
4.3047774e-05 |
| 7,395 |
MOST: Model-Based Compression with Outlier Storage for Time Series Data |
2023 |
SIGMOD |
4.7420041e-05 |
| 11,133 |
Scalable Model-Based Management of Massive High Frequency Wind Turbine Data with ModelarDB |
2024 |
VLDB |
4.1945683e-05 |
| 10,793 |
Demonstration of ModelarDB: Model-Based Management of High-Frequency Time Series Across Edge, Cloud, and Client |
2025 |
VLDB |
4.1945683e-05 |
| 13,294 |
Demonstration of ModelarDB: Model-Based Management of Dimensional Time Series |
2019 |
SIGMOD |
- |