DDSketch: A Fast and Fully-Mergeable Quantile Sketch with Relative-Error Guarantees
Summary: DDSketch is the first fully mergeable quantile sketch with formal relative-error guarantees, avoiding rank-error failures on skewed data. Its logarithmic value mapping delivers fast, accurate summaries for distributed streams and production-scale use. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Charles Masson (Datadog)
- 2. Jee E. Rim (Datadog)
- 3. Homin K. Lee (Datadog)
BibTeX Citation
@article{masson_vldb19,
title = {{DDSketch: A Fast and Fully-Mergeable Quantile Sketch with Relative-Error Guarantees}},
author = {Masson, Charles and Rim, Jee E. and Lee, Homin K.},
journal = {PVLDB},
series = {{VLDB} '19},
volume = {12},
number = {12},
pages = {2195--2205},
doi = {10.14778/3352063.3352135},
url = {https://doi.org/10.14778/3352063.3352135},
year = {2019}
}
Incoming Citations (Sorted by Pagerank)
Showing 16 of 16 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 9 of 9 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 83 | Space-Efficient Online Computation of Quantile Summaries | 2001 | SIGMOD | 0.00035978046 |
| 240 | Gigascope: A Stream Database for Network Applications | 2003 | SIGMOD | 0.00023435436 |
| 275 | Optimal Histograms with Quality Guarantees | 1998 | VLDB | 0.00022413521 |
| 456 | Mergeable Summaries | 2012 | PODS | 0.0001791284 |
| 850 | The Design of an Acquisitional Query Processor For Sensor Networks | 2003 | SIGMOD | 0.00013488409 |
| 1,381 | Scuba: Diving into Data at Facebook | 2013 | VLDB | 0.00010860462 |
| 2,750 | Space- and Time-Efficient Deterministic Algorithms for Biased Quantiles over Data Streams | 2006 | PODS | 8.0573403e-05 |
| 2,798 | Moment-Based Quantile Sketches for Efficient High Cardinality Aggregation Queries | 2018 | VLDB | 7.9933329e-05 |
| 3,163 | REHIST: Relative Error Histogram Construction Algorithms | 2004 | VLDB | 7.5789852e-05 |
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|---|---|---|---|---|
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