MayBMS: A System for Managing Large Uncertain and Probabilistic Databases (2008)
| Venue: | Managing and Mining Uncertain Data, chapter 6 |
| Citations: | 12 - 4 self |
BibTeX
@INPROCEEDINGS{Koch08maybms:a,
author = {Christoph Koch and Lyublena Antova (cornell and Jiewen Huang (oxford and Goetz (cornell). Thomas Jansen and Ali Baran and Sari Maybms},
title = {MayBMS: A System for Managing Large Uncertain and Probabilistic Databases},
booktitle = {Managing and Mining Uncertain Data, chapter 6},
year = {2008},
publisher = {Springer-Verlag}
}
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Abstract
MayBMS is a state-of-the-art probabilistic database management system that has been built as an extension of Postgres, an open-source relational database management system. MayBMS follows a principled approach to leveraging the strengths of previous database research for achieving scalability. This article describes the main goals of this project, the design of query and update language, efficient exact and approximate query processing, and algorithmic and systems aspects.
