Cloudy with High Chance of DBMS: A 10-year Prediction for Enterprise-Grade ML

Summary: Predicts enterprise adoption of DBMS-native ML that tightly integrates model lifecycle with rigorous data governance, privacy, and security at scale. Identifies unmet requirements and DB research challenges (provenance, auditing, access control, federated/secure training, deployment/auto-tuning) and sketches early system-building steps. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 387
Venue: CIDR
Year: 2020
Pagerank: 6.675257e-05
Overall Rank: 3,875 | 73.05%
DOI: -

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 17 of 17 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
2,642	Vertica-ML: Distributed Machine Learning in Vertica Database	2020	SIGMOD	8.3851878e-05
2,753	Complaint-driven Training Data Debugging for Query 2.0	2020	SIGMOD	8.1724339e-05
2,804	Extending Relational Query Processing with ML Inference	2020	CIDR	8.0935487e-05
3,407	End-to-end Optimization of Machine Learning Prediction Queries	2022	SIGMOD	7.1295646e-05
4,557	Distributed Deep Learning on Data Systems: A Comparative Analysis of Approaches	2021	VLDB	6.087611e-05
4,774	LIMA: Fine-grained Lineage Tracing and Reuse in Machine Learning Systems	2021	SIGMOD	5.9316087e-05
5,086	Improving Reproducibility of Data Science Pipelines through Transparent Provenance Capture	2020	VLDB	5.7078462e-05
5,567	Optimizing Data Pipelines for Machine Learning in Feature Stores	2023	VLDB	5.4305348e-05
6,261	The Cosmos Big Data Platform at Microsoft: Over a Decade of Progress and a Decade to Look Forward	2021	VLDB	5.1350714e-05
6,378	Mitigating the Impedance Mismatch between Prediction Query Execution and Database Engine	2025	SIGMOD	5.0909804e-05
8,416	Towards Building Autonomous Data Services on Azure	2023	SIGMOD	4.5196199e-05
8,854	Optimizing the cloud? Don't train models. Build oracles!	2024	CIDR	4.4349047e-05
9,436	Transforming ML Predictive Pipelines into SQL with MASQ	2021	SIGMOD	4.3430376e-05
9,695	Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem	2022	VLDB	4.3025567e-05
9,983	Does A Fish Need a Bicycle? The Case for On-Chip NPUs in DBMS	2026	CIDR	4.1945683e-05
11,149	Git is for Data	2023	CIDR	4.1945683e-05
11,313	Towards Observability for Machine Learning Pipelines	2022	CIDR	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
140	The MADlib Analytics Library or MAD Skills, the SQL	2012	VLDB	0.00042270404
1,084	Dhalion: Self-Regulating Stream Processing in Heron	2017	VLDB	0.00014209714
1,108	Froid: Optimization of Imperative Programs in a Relational Database	2018	VLDB	0.00013984276
2,083	Towards a Learning Optimizer for Shared Clouds	2019	VLDB	9.5834572e-05
2,350	An Intermediate Representation for Optimizing Machine Learning Pipelines	2019	VLDB	8.9788641e-05
2,804	Extending Relational Query Processing with ML Inference	2020	CIDR	8.0935487e-05
3,625	Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings	2020	SIGMOD	6.9055212e-05

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