AZDBLab: A Laboratory Information System for Large-Scale Empirical DBMS Studies
Summary: AZDBLab, a DBMS-oriented laboratory for large-scale empirical studies across multiple DBMSs. Enables large-scale, cross-DBMS experiments on optimizer behavior with automated analysis of thousands to millions of queries, using Tucson Timing Protocol timing checks, via standalone and mobile apps. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
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Authors
- 1. Young-Kyoon Suh (University of Arizona)
- 2. Richard T. Snodgrass (University of Arizona)
- 3. Rui Zhang (Dataware Ventures)
BibTeX Citation
@article{suh_vldb14,
title = {{AZDBLab: A Laboratory Information System for Large-Scale Empirical DBMS Studies}},
author = {Suh, Young-Kyoon and Snodgrass, Richard T. and Zhang, Rui},
journal = {PVLDB},
series = {{VLDB} '14},
volume = {7},
number = {13},
pages = {1641--1644},
doi = {10.14778/2733004.2733050},
url = {https://doi.org/10.14778/2733004.2733050},
year = {2014}
}Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 984 | Analyzing Plan Diagrams of Database Query Optimizers | 2005 | VLDB | 0.00012825643 |
| 12,254 | DBMS Metrology: Measuring Query Time | 2013 | SIGMOD | 5.093636e-05 |
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