DBMS Fitting: Why should we learn what we already know?
Summary: Critiques end-to-end DNN replacements for DBMS components as data-hungry and opaque; proposes leveraging differentiable programming to fit components using known algorithmic structure rather than learning behavior from scratch. Case study: fitted cost model for query plans with initial promising results. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Benjamin Hilprecht
- 2. Tiemo Bang
- 3. Muhammad El-Hindi
- 4. Benjamin Hättasch
- 5. Aditya Khanna
- 6. Robin Rehrmann
- 7. Uwe Röhm
- 8. Andreas Schmidt
- 9. Lasse Thostrup
- 10. Tobias Ziegler
- 11. Carsten Binnig
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,828 | Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction | 2022 | VLDB | 6.7208524e-05 |
| 5,258 | One Model to Rule them All: Towards Zero-Shot Learning for Databases | 2022 | CIDR | 5.5998705e-05 |
| 8,956 | T3: Accurate and Fast Performance Prediction for Relational Database Systems With Compiled Decision Trees | 2025 | SIGMOD | 4.4214154e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 13 of 13 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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