VergeDB: A Database for IoT Analytics on Edge Devices

Summary: VergeDB: an edge-focused DB that performs adaptive, task-aware compression of IoT time-series and exposes analytics/ML as first-class operations, enabling in-situ queries on raw or compressed data. Optimizes compute/storage/network tradeoffs to maximize throughput and downstream accuracy. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 409
Venue: CIDR
Year: 2021
Pagerank: 5.9910733e-05
Overall Rank: 6,061 | 58.42%
DOI: -

Incoming Non-self Citations Over Time

Authors

1. John Paparrizos (University of Chicago)
2. Chunwei Liu (University of Chicago)
3. Bruno Barbarioli (University of Chicago)
4. Johnny Hwang (University of Chicago)
5. Ikraduya Edian (Bandung Institute of Technology)
6. Aaron J. Elmore (University of Chicago)
7. Michael J. Franklin (University of Chicago)
8. Sanjay Krishnan (University of Chicago)

BibTeX Citation

@inproceedings{paparrizos_cidr21,
        address = {Amsterdam, Netherlands},
        series = {{CIDR} '21},
        title = {{VergeDB: A Database for IoT Analytics on Edge Devices}},
        booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
        author = {Paparrizos, John and Liu, Chunwei and Barbarioli, Bruno and Hwang, Johnny and Edian, Ikraduya and Elmore, Aaron J. and Franklin, Michael J. and Krishnan, Sanjay},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 26 of 26 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
1,805	SAND: Streaming Subsequence Anomaly Detection	2021	VLDB	9.7116108e-05
2,004	TSB-UAD: An End-to-End Benchmark Suite for Univariate Time-Series Anomaly Detection	2022	VLDB	9.3207067e-05
2,023	Decomposed Bounded Floats for Fast Compression and Queries	2021	VLDB	9.2950046e-05
3,447	Volume Under the Surface: A New Accuracy Evaluation Measure for Time-Series Anomaly Detection	2022	VLDB	7.4085215e-05
3,987	Choose Wisely: An Extensive Evaluation of Model Selection for Anomaly Detection in Time Series	2023	VLDB	6.9722766e-05
5,037	A Deep Dive into Common Open Formats for Analytical DBMSs	2023	VLDB	6.3914026e-05
5,622	Good to the Last Bit: Data-Driven Encoding with CodecDB	2021	SIGMOD	6.1461066e-05
6,556	Hierarchical Residual Encoding for Multiresolution Time Series Compression	2023	SIGMOD	5.8404094e-05
6,590	MOST: Model-Based Compression with Outlier Storage for Time Series Data	2023	SIGMOD	5.8316635e-05
8,622	Accelerating Product Quantization Query Execution Runtime	2021	SIGMOD	5.3985954e-05
9,448	Theseus: Navigating the Labyrinth of Time-Series Anomaly Detection	2022	VLDB	5.2665425e-05
9,477	Odyssey: An Engine Enabling The Time-Series Clustering Journey	2023	VLDB	5.2634238e-05
9,673	High-Ratio Compression for Machine-Generated Data	2023	SIGMOD	5.2383683e-05
9,733	SPARTAN: Data-Adaptive Symbolic Time-Series Approximation	2025	SIGMOD	5.227679e-05
10,256	HYDRA: A Multi-Level Hierarchy-Driven Approach for Robust Anomaly Detection in Time Series	2026	SIGMOD	5.093636e-05
10,271	MUFASA: Fast and Accurate Multivariate Time-Series Clustering	2026	SIGMOD	5.093636e-05
10,298	The Power of Anomaly Detection in Predictive Maintenance: [Experiments & Analysis]	2026	SIGMOD	5.093636e-05
10,747	A Structured Study of Multivariate Time-Series Distance Measures	2025	SIGMOD	5.093636e-05
10,796	Understanding the Black Box: A Deep Empirical Dive into Shapley Value Approximations for Tabular Data	2025	SIGMOD	5.093636e-05
10,977	TSB-AutoAD: Towards Automated Solutions for Time-Series Anomaly Detection	2025	VLDB	5.093636e-05
10,980	Beyond Compression: A Comprehensive Evaluation of Lossless Floating-Point Compression	2025	VLDB	5.093636e-05
11,119	The Tipping Point of Edge-Cloud Data Management	2024	CIDR	5.093636e-05
11,251	QCore: Data-Efficient, On-Device Continual Calibration for Quantized Models	2024	VLDB	5.093636e-05
11,300	Time-Series Anomaly Detection: Overview and New Trends	2024	VLDB	5.093636e-05
11,435	Accelerating Similarity Search for Elastic Measures: A Study and New Generalization of Lower Bounding Distances	2023	VLDB	5.093636e-05
13,463	SAND in Action: Subsequence Anomaly Detection for Streams	2021	VLDB	-

Outgoing Citations (Sorted by Pagerank)

Showing 20 of 20 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
35	Improved Histograms for Selectivity Estimation of Range Predicates	1996	SIGMOD	0.00048481081
36	Accurate Estimation Of The Number Of Tuples Satisfying A Condition	1984	SIGMOD	0.00048351457
41	Fast Subsequence Matching in Time-Series Databases	1994	SIGMOD	0.00046675394
82	Space-Efficient Online Computation of Quantile Summaries	2001	SIGMOD	0.00036378991
148	Gorilla: A Fast, Scalable, In-Memory Time Series Database	2015	VLDB	0.00029250767
190	Locally Adaptive Dimensionality Reduction for Indexing Large Time Series Databases	2001	SIGMOD	0.00026105472
274	Balancing Histogram Optimality and Practicality for Query Result Size Estimation	1995	SIGMOD	0.00022645621
468	Fast Time Sequence Indexing for Arbitrary Lp Norms	2000	VLDB	0.00017986163
569	BlazeIt: Optimizing Declarative Aggregation and Limit Queries for Neural Network-Based Video Analytics	2020	VLDB	0.00016348191
610	Efficiently Supporting Ad Hoc Queries in Large Datasets of Time Sequences	1997	SIGMOD	0.00015783259
765	Query Processing for Sensor Networks	2003	CIDR	0.00014217472
797	Dimensionality Reduction for Similarity Searching in Dynamic Databases	1998	SIGMOD	0.00013927251
1,009	Online Aggregation for Large MapReduce Jobs	2011	VLDB	0.00012684342
1,579	k-Shape: Efficient and Accurate Clustering of Time Series	2015	SIGMOD	0.00010305183
1,582	SciBORQ: Scientific data management with Bounds On Runtime and Quality	2011	CIDR	0.00010295367
3,595	Plato: Approximate Analytics over Compressed Time Series with Tight Deterministic Error Guarantees	2020	VLDB	7.2736195e-05
4,234	GRAIL: Efficient Time-Series Representation Learning	2019	VLDB	6.8171563e-05
4,604	Debunking Four Long-Standing Misconceptions of Time-Series Distance Measures	2020	SIGMOD	6.6104585e-05
5,215	The NebulaStream Platform: Data and Application Management for the Internet of Things	2020	CIDR	6.3124972e-05
8,000	PIDS: Attribute Decomposition for Improved Compression and Query Performance in Columnar Storage	2020	VLDB	5.5092344e-05

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