Building the Enterprise Fabric for Big Data with Vertica and Spark Integration

Summary: Proposes a Vertica–Spark integration that provides fast, reliable data movement between the engine and Spark and enables deploying Spark ML models into Vertica for analytics on Vertica data. The fabric blends Vertica’s SQL analytics with Spark MLlib, letting Spark serve as an advanced ETL layer under Vertica’s guarantees. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 5203
Venue: SIGMOD
Year: 2016
Pagerank: 4.8559744e-05
Overall Rank: 7,032 | 51.09%
DOI: 10.1145/2882903.2903744

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
2,642	Vertica-ML: Distributed Machine Learning in Vertica Database	2020	SIGMOD	8.3851878e-05
8,758	Hyperspace: The Indexing Subsystem of Azure Synapse	2021	VLDB	4.456315e-05

Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
21	C-Store: A Column-oriented DBMS	2005	VLDB	0.00086087497
310	The Vertica Analytic Database: C-Store 7 Years Later	2012	VLDB	0.00028132402
5,395	Large-scale Predictive Analytics in Vertica: Fast Data Transfer, Distributed Model Creation, and In-database Prediction	2015	SIGMOD	5.5318806e-05

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