Transparent Distribution in a Storage Manager

Scalable Distributed Data Structures (SDDSs) provide a self-managing and self-organizing data storage of potentially unbounded size. This stands in contrast to common distribution schemas deployed in conventional distributed DBMS. SDDSs, however, have mostly been used in synthetic scenarios to investigate their properties. In this paper we concentrate on the integration of the LH* SDDS into Monet, our efficient and extensible DBMS. We show that this merge provides high performance processing and scalable storage of very large sets of distributed data. In our implementation we extended the Monet language interpreters operators in such a way that access to data, whether it is distributed or locally stored, is transparent to the user. Performance measures show viability of our approach, querying using a number of operators on distributed data on a number of nodes.