The Case for NLP-Enhanced Database Tuning: Towards Tuning Tools that "Read the Manual"
Summary: NLP-driven database tuning that reads manuals and literature to guide automated configuration. A prototype mines tuning hints from web documents and shows improved MySQL/PostgreSQL performance on TPC-H vs default settings. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
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Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,407 | DB-BERT: A Database Tuning Tool that "Reads the Manual" | 2022 | SIGMOD | 0.00012146739 |
| 3,995 | How Large Language Models Will Disrupt Data Management | 2023 | VLDB | 6.5513237e-05 |
| 5,509 | Can Large Language Models Predict Data Correlations from Column Names? | 2023 | VLDB | 5.4703368e-05 |
| 8,458 | Demonstrating DB-BERT: A Database Tuning Tool that "Reads" the Manual | 2022 | SIGMOD | 4.5066722e-05 |
| 9,605 | Waffle: In-memory Grid Index for Moving Objects with Reinforcement Learning-based Configuration Tuning System | 2022 | VLDB | 4.3177432e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 17 of 17 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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