mlsanityData to 7 Oct 2026

Database Meets Deep Learning: Challenges and Opportunities

arXiv 1906.08986 ↗First posted 21 Jun 2019cs.DB cs.DC cs.LGcited by 30

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Abstract (arXiv)

Deep learning has recently become very popular on account of its incredible success in many complex data-driven applications, such as image classification and speech recognition. The database community has worked on data-driven applications for many years, and therefore should be playing a lead role in supporting this new wave. However, databases and deep learning are different in terms of both techniques and applications. In this paper, we discuss research problems at the intersection of the two fields. In particular, we discuss possible improvements for deep learning systems from a database perspective, and analyze database applications that may benefit from deep learning techniques.

Key facts. Cited by 30 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Jun 2019.

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Citing papers per year: 2021: 10; 2022: 10; 2023: 3; 2024: 4; 2025: 2; 2026: 1.

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  1. 2021GitTables: A Large-Scale Corpus of Relational Tablescited by 44
  2. 2021AlphaEvolve: A Learning Framework to Discover Novel Alphas in Quantitative Investmentcited by 31
  3. 2021ARM-Net: Adaptive Relation Modeling Network for Structured Datacited by 24
  4. 2023THC: Accelerating Distributed Deep Learning Using Tensor Homomorphic Compressioncited by 15
  5. 2021A Survey on Deep Reinforcement Learning for Data Processing and Analyticscited by 10
  6. 2021CARMI: A Cache-Aware Learned Index with a Cost-based Construction Algorithmcited by 8
  7. 2025Apt-Serve: Adaptive Request Scheduling on Hybrid Cache for Scalable LLM Inference Servingcited by 6
  8. 2024NeurDB: An AI-powered Autonomous Data Systemcited by 5
  9. 2024NeurDB: On the Design and Implementation of an AI-powered Autonomous Databasecited by 5
  10. 2021Learned Sorted Table Search and Static Indexes in Small Model Spacecited by 4
  11. 2024A Survey of Learned Indexes for the Multi-dimensional Spacecited by 4
  12. 2021Serverless Data Science -- Are We There Yet? A Case Study of Model Servingcited by 3
18 more
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  2. 2024CohortNet: Empowering Cohort Discovery for Interpretable Healthcare Analyticscited by 3
  3. 2025Generative AI for Healthcare: Fundamentals, Challenges, and Perspectivescited by 3
  4. 2022Scalable Graph Convolutional Network Training on Distributed-Memory Systemscited by 2
  5. 2021SINGA-Easy: An Easy-to-Use Framework for MultiModal Analysiscited by 0
  6. 2021VisualTextRank: Unsupervised Graph-based Content Extraction for Automating Ad Text to Image Searchcited by 0
  7. 2021Text is NOT Enough: Integrating Visual Impressions into Open-domain Dialogue Generationcited by 0
  8. 2022Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectorscited by 0
  9. 2022Reinforced MOOCs Concept Recommendation in Heterogeneous Information Networkscited by 0
  10. 2022Effective Explanations for Entity Resolution Modelscited by 0
  11. 2022Explanation-Guided Fairness Testing through Genetic Algorithmcited by 0
  12. 2022Multi-agent Databases via Independent Learningcited by 0
  13. 2022The Metaverse Data Deluge: What Can We Do About It?cited by 0
  14. 2022Using Graph Neural Networks for Program Terminationcited by 0
  15. 2022TorchFL: A Performant Library for Bootstrapping Federated Learning Experimentscited by 0
  16. 2023From Plate to Prevention: A Dietary Nutrient-aided Platform for Health Promotion in Singaporecited by 0
  17. 2023Tribe or Not? Critical Inspection of Group Differences Using TribalGramcited by 0
  18. 2026MetaRTL: Meta-path Attention Enhanced Relational Table Learningcited by 0