DeepDB: Learn from Data, not from Queries!
Summary: Data-driven learned DBMS components bypass workload-driven training, enabling changes in workload or data without retraining. Empirically higher accuracy and better generalization to unseen queries than state-of-the-art learned components. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Benjamin Hilprecht (Technical University of Darmstadt)
- 2. Andreas Schmidt (Karlsruhe Institute of Technology; Karlsruhe University of Applied Sciences)
- 3. Moritz Kulessa (Technical University of Darmstadt)
- 4. Alejandro Molina (Technical University of Darmstadt)
- 5. Kristian Kersting (Technical University of Darmstadt)
- 6. Carsten Binnig (Technical University of Darmstadt)
BibTeX Citation
@article{hilprecht_vldb20,
title = {{DeepDB: Learn from Data, not from Queries!}},
author = {Hilprecht, Benjamin and Schmidt, Andreas and Kulessa, Moritz and Molina, Alejandro and Kersting, Kristian and Binnig, Carsten},
journal = {PVLDB},
series = {{VLDB} '20},
volume = {13},
number = {7},
pages = {992--1005},
doi = {10.14778/3384345.3384349},
url = {https://doi.org/10.14778/3384345.3384349},
year = {2020}
}Incoming Citations (Sorted by Pagerank)
Showing 50 of 124 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 25 of 25 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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