nsDB: Architecting the Next Generation Database by Integrating Neural and Symbolic Systems
Summary: nsDB proposes a native neuro-symbolic DB integrating neural models with symbolic data management for multimodal analytics, learning, and complex queries. It frames open systems challenges including in-database training, multi-objective optimization, and database agents. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Ye Yuan (Beijing Institute of Technology)
- 2. Bo Tang (Southern University of Science and Technology)
- 3. Tianfei Zhou (Beijing Institute of Technology)
- 4. Zhiwei Zhang (Beijing Institute of Technology)
- 5. Jianbin Qin (Shenzhen University)
BibTeX Citation
@article{yuan_vldb24,
title = {{nsDB: Architecting the Next Generation Database by Integrating Neural and Symbolic Systems}},
author = {Yuan, Ye and Tang, Bo and Zhou, Tianfei and Zhang, Zhiwei and Qin, Jianbin},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {11},
pages = {3283--3289},
doi = {10.14778/3681954.3682000},
url = {https://doi.org/10.14778/3681954.3682000},
year = {2024}
}
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,221 | NeurDB: On the Design and Implementation of an AI-powered Autonomous Database | 2025 | CIDR | 5.4640314e-05 |
| 10,120 | KathDB: Explainable Multimodal Database Management System with Human-AI Collaboration | 2026 | CIDR | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 20 of 20 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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