Database Paper Browser

Back to papers

Machine Learning and Databases: The Sound of Things to Come or a Cacophony of Hype?

Summary: Examines ML–DB frontier, outlining concrete opportunities for data management, learned query processing, and ML integration, and assesses substance versus hype. Discusses pitfalls, hype risks, and guidance for database researchers pursuing ML. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5026
Venue
SIGMOD
Year
2015
Pagerank
6.6691196e-05
Overall Rank
3,881 | 73.01%
DOI
10.1145/2723372.2742911

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

Rank Citing Paper Year Venue Pagerank
834 Learning Linear Regression Models over Factorized Joins 2016 SIGMOD 0.00016135159
2,642 Vertica-ML: Distributed Machine Learning in Vertica Database 2020 SIGMOD 8.3851878e-05
2,934 AIDA - Abstraction for Advanced In-Database Analytics 2018 VLDB 7.8595778e-05
3,473 AI Meets Database: AI4DB and DB4AI 2021 SIGMOD 7.062864e-05
4,748 Rafiki: Machine Learning as an Analytics Service System 2019 VLDB 5.9526539e-05
5,861 Machine Learning for Databases 2021 VLDB 5.298883e-05
8,688 NeurDB: On the Design and Implementation of an AI-powered Autonomous Database 2025 CIDR 4.4673127e-05
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 0 of 0 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
Previous Page 1 / 1 Next

Semantically Similar Papers