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Many scientific fields routinely generate huge datasets. In many cases, these datasets are not static but rapidly grow in size. Handling these types of datasets, as well as allowing sophisticated queries necessitates efficient distributed database systems. This paper presents the architecture, implementation and performance analysis of a scalable, distributed database system built on software based virtualization environments. The system architecture makes use of software partitioning of the database based on data clustering, SQMD (Single Query Multiple Database) mechanism, a web service interface, and virtualization software technologies. The system allows uniform access to concurrently distributed databases, using the SQMD mechanism based on the publish/subscribe paradigm.
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