NeurDB: On the Design and Implementation of an AI-powered Autonomous Database
Summary: NeurDB is an AI-powered autonomous database that embeds end-to-end AI workflows inside the engine to enable efficient in‑database analytics and learned components. Novelty: fast‑adaptive learned components and an in‑DB AI ecosystem that handles data and workload drift, yielding substantial empirical gains. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zhanhao Zhao (National University of Singapore)
- 2. Shaofeng Cai (National University of Singapore)
- 3. Haotian Gao (National University of Singapore)
- 4. Hexiang Pan (National University of Singapore)
- 5. Siqi Xiang (National University of Singapore)
- 6. Naili Xing (National University of Singapore)
- 7. Gang Chen (Zhejiang University)
- 8. Beng Chin Ooi (National University of Singapore)
- 9. Yanyan Shen (Shanghai Jiao Tong University)
- 10. Yuncheng Wu (Renmin University of China)
- 11. Meihui Zhang (Beijing Institute of Technology)
BibTeX Citation
@inproceedings{zhao_cidr25,
address = {Amsterdam, Netherlands},
series = {{CIDR} '25},
title = {{NeurDB: On the Design and Implementation of an AI-powered Autonomous Database}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Zhao, Zhanhao and Cai, Shaofeng and Gao, Haotian and Pan, Hexiang and Xiang, Siqi and Xing, Naili and Chen, Gang and Ooi, Beng Chin and Shen, Yanyan and Wu, Yuncheng and Zhang, Meihui},
year = {2025}
}
Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
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