Vertica-ML: Distributed Machine Learning in Vertica Database

Summary: Vertica-ML is a distributed ML subsystem embedded in the Vertica database, exposing a SQL-based data science workflow and model management. Models are first-class objects (like tables/views) for versioning and governance; the paper details architecture and performance experiments. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: hd14510f4a41294a8
Venue: SIGMOD
Year: 2020
Pagerank: 8.5070634e-05
Overall Rank: 2,398 | 83.93%
DOI: 10.1145/3318464.3386137

Incoming Non-self Citations Over Time

Authors

1. Arash Fard (Vertica)
2. Anh Le (Vertica)
3. George Larionov (Vertica)
4. Waqas Dhillon (Vertica)
5. Chuck Bear (Vertica)

BibTeX Citation

@inproceedings{fard_sigmod20,
        title = {{Vertica-ML: Distributed Machine Learning in Vertica Database}},
        author = {Fard, Arash and Le, Anh and Larionov, George and Dhillon, Waqas and Bear, Chuck},
        series = {{SIGMOD} '20},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3318464.3386137},
        url = {https://dl.acm.org/doi/10.1145/3318464.3386137},
        year = {2020}
}

Incoming Citations (Sorted by Pagerank)

Showing 14 of 14 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
3,256	Towards Demystifying Serverless Machine Learning Training	2021	SIGMOD	7.4732677e-05
4,117	Distributed Deep Learning on Data Systems: A Comparative Analysis of Approaches	2021	VLDB	6.784003e-05
4,961	Heterogeneity-Aware Distributed Machine Learning Training via Partial Reduce	2021	SIGMOD	6.3246342e-05
5,697	SmartLite: A DBMS-based Serving System for DNN Inference in Resource-constrained Environments	2024	VLDB	6.0151439e-05
6,011	BAGUA: Scaling up Distributed Learning with System Relaxations	2022	VLDB	5.8975241e-05
6,474	In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle	2022	SIGMOD	5.7555547e-05
6,765	Mitigating the Impedance Mismatch between Prediction Query Execution and Database Engine	2025	SIGMOD	5.6695399e-05
8,255	Adda: Towards Efficient in-Database Feature Generation via LLM-based Agents	2025	SIGMOD	5.3520689e-05
10,655	NeurStore: Efficient In-database Deep Learning Model Management System	2026	SIGMOD	4.9605343e-05
10,674	TranSQL+: Serving Large Language Models with SQL on Low-Resource Hardware	2026	SIGMOD	4.9605343e-05
11,587	StarfishDB: a Query Execution Engine for Relational Probabilistic Programming	2024	SIGMOD	4.9605343e-05
11,604	Database Native Model Selection: Harnessing Deep Neural Networks in Database Systems	2024	VLDB	4.9605343e-05
11,784	F3 KM: Federated, Fair, and Fast k-means	2023	SIGMOD	4.9605343e-05
11,846	AQUA: Automatic Collaborative Query Processing in Analytical Database	2023	VLDB	4.9605343e-05

Outgoing Citations (Sorted by Pagerank)

Showing 10 of 10 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
12	C-Store: A Column-oriented DBMS	2005	VLDB	0.00068985264
105	The MADlib Analytics Library or MAD Skills, the SQL	2012	VLDB	0.00033605348
142	Neo: A Learned Query Optimizer	2019	VLDB	0.00029114937
177	The Vertica Analytic Database: C-Store 7 Years Later	2012	VLDB	0.00026571747
2,138	Scalable K-Means++	2012	VLDB	8.9755133e-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
2,615	PLANET: Massively Parallel Learning of Tree Ensembles with MapReduce	2009	VLDB	8.2019215e-05
3,691	Cloudy with High Chance of DBMS: A 10-year Prediction for Enterprise-Grade ML	2020	CIDR	7.0771037e-05
3,724	Machine Learning and Databases: The Sound of Things to Come or a Cacophony of Hype?	2015	SIGMOD	7.0482307e-05
7,508	Building the Enterprise Fabric for Big Data with Vertica and Spark Integration	2016	SIGMOD	5.4919012e-05

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