VLDB 2026 Research / reviewers in the wild / expert

Vamsi Ponnekanti

dblp:131/4099 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2013
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Performance modeling and evaluation · 100%
Databases, data mining, and information retrieval
1 paper
Graph data management · 77% Web and social media mining · 23%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Performance modeling and evaluation
benchmarking		 0.212013
LinkBench: a database benchmark based on the Facebook social graph · SIGMOD Conference 2013
Performance modeling and evaluation › benchmarking
database system benchmarking		 0.212013
LinkBench: a database benchmark based on the Facebook social graph · SIGMOD Conference 2013
Web and social media mining
social network analysis		 0.012013
LinkBench: a database benchmark based on the Facebook social graph · SIGMOD Conference 2013
YearPublicationVenuePosition
2013 LinkBench: a database benchmark based on the Facebook social graph
abstract
Database benchmarks are an important tool for database researchers and practitioners that ease the process of making informed comparisons between different database hardware, software and configurations. Large scale web services such as social networks are a major and growing database application area, but currently there are few benchmarks that accurately model web service workloads.
Timothy G. Armstrong, Vamsi Ponnekanti, Dhruba Borthakur, Mark Callaghan
 SIGMOD Conference2