ChatQPT: Towards Conversing with Relational Query Engines
Summary: ChatQPT combines an LLM conversational interface with specialized tools to let users query and inspect PostgreSQL’s processing and optimization via messaging platforms. Aims at accurate database education and administration, overcoming limitations of standalone LLMs and RDBMSs. (summarized by gpt-5.6-luna on Aug 28 2026)
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Authors
- 1. Hui Li (Xidian University)
- 2. Sourav S Bhowmick (Nanyang Technological University)
- 3. Baochao Xu (Xidian University)
- 4. Zhenning Shi (Xidian University)
- 5. Xiyue Gao (Xidian University)
- 6. Jingjing Li (Chinese University of Hong Kong)
BibTeX Citation
@article{li_vldb26,
title = {{ChatQPT: Towards Conversing with Relational Query Engines}},
author = {Li, Hui and Bhowmick, Sourav S and Xu, Baochao and Shi, Zhenning and Gao, Xiyue and Li, Jingjing},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {12},
pages = {4758--4761},
doi = {10.14778/3827998.3828115},
url = {https://doi.org/10.14778/3827998.3828115},
year = {2026}
}Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,913 | DataChat: An Intuitive and Collaborative Data Analytics Platform | 2023 | SIGMOD | 6.9295933e-05 |
| 6,003 | MOCHA: A Tool for Visualizing Impact of Operator Choices in Query Execution Plans for Database Education | 2022 | VLDB | 5.9172558e-05 |
| 11,856 | LANTERN: Boredom-conscious Natural Language Description Generation of Query Execution Plans for Database Education | 2022 | SIGMOD | 4.9793485e-05 |
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