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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)

Paper ID
h6d77a2da0a138870
Venue
VLDB
Year
2024
Pagerank
5.2245336e-05
Overall Rank
9,009 | 39.62%
DOI
10.14778/3681954.3682000
PDF
Download (CC BY-NC-ND 4.0)

Incoming Non-self Citations Over Time

Authors

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)

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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.

Rank Cited Paper Year Venue Pagerank
33 Consistent Query Answers in Inconsistent Databases 1999 PODS 0.00049435337
100 HoloClean: Holistic Data Repairs with Probabilistic Inference 2017 VLDB 0.00033951027
1,358 Symphony: Towards Natural Language Query Answering over Multi-modal Data Lakes 2023 CIDR 0.00010902306
2,199 Extending Relational Query Processing with ML Inference 2020 CIDR 8.8664379e-05
2,407 Declarative Recursive Computation on an RDBMS or, Why You Should Use a Database For Distributed Machine Learning 2019 VLDB 8.4928721e-05
2,672 End-to-end Optimization of Machine Learning Prediction Queries 2022 SIGMOD 8.1301225e-05
3,775 Hardware-conscious Query Processing in GPU-accelerated Analytical Engines 2019 CIDR 7.0079979e-05
3,868 GaccO - A GPU-accelerated OLTP DBMS 2022 SIGMOD 6.9436655e-05
3,997 Designing an Open Framework for Query Optimization and Compilation 2022 VLDB 6.850379e-05
4,284 VIVA: An End-to-End System for Interactive Video Analytics 2022 CIDR 6.6710929e-05
4,762 Tensor Relational Algebra for Distributed Machine Learning System Design 2021 VLDB 6.4190861e-05
5,193 CGgraph: An Ultra-fast Graph Processing System on Modern Commodity CPU-GPU Co-processor 2024 VLDB 6.2203717e-05
5,795 The Tensor Data Platform: Towards an AI-centric Database System 2023 CIDR 5.9755414e-05
6,672 Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation 2023 SIGMOD 5.6975871e-05
7,018 Integration of Data Mining and Relational Databases 2000 VLDB 5.6041712e-05
7,892 Rock: Cleaning Data by Embedding ML in Logic Rules 2024 SIGMOD 5.4156936e-05
8,979 Tao: Improving Resource Utilization while Guaranteeing SLO in Multi-tenant Relational Database-as-a-Service 2024 SIGMOD 5.2330911e-05
9,867 AMNES: Accelerating the computation of data correlation using FPGAs 2023 VLDB 5.1056602e-05
9,868 Transforming ML Predictive Pipelines into SQL with MASQ 2021 SIGMOD 5.1056602e-05
10,147 TVM: A Tile-based Video Management Framework 2024 VLDB 5.0597449e-05
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