PerfEnforce Demonstration: Data Analytics with Performance Guarantees
Summary: PerfEnforce Demonstration presents a dynamic analytics-scaling engine minimizing cost while probabilistically meeting SLA runtimes. Three scaling families—feedback control, reinforcement learning, and online ML—enable tuning and workload-aware comparisons. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jennifer Ortiz (University of Washington)
- 2. Brendan Lee (University of Washington)
- 3. Magdalena Balazinska (University of Washington)
BibTeX Citation
@inproceedings{ortiz_sigmod16,
title = {{PerfEnforce Demonstration: Data Analytics with Performance Guarantees}},
author = {Ortiz, Jennifer and Lee, Brendan and Balazinska, Magdalena},
series = {{SIGMOD} '16},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2882903.2899402},
url = {https://dl.acm.org/doi/10.1145/2882903.2899402},
year = {2016}
}
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 |
|---|---|---|---|---|
| 2,796 | Demonstration of the Myria Big Data Management Service | 2014 | SIGMOD | 7.9971623e-05 |
| 3,693 | Changing the Face of Database Cloud Services with Personalized Service Level Agreements | 2015 | CIDR | 7.093442e-05 |
| 3,747 | TIRAMOLA: Elastic NoSQL Provisioning Through a Cloud Management Platform | 2012 | SIGMOD | 7.0552485e-05 |
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