Abstract
The current exponential growth of data calls for massive-scale capabilities of storage and processing. Such large volumes of data tend to disallow their centralized storage and processing making extensive and flexible data partitioning unavoidable. This is being acknowledged by several major Internet players embracing the Cloud computing model and offering first generation remote storage services with simple processing capabilities. In this position paper we present preliminary ideas for the architecture of a flexible, efficient and dependable fully decentralized object store able to manage very large sets of variable size objects and to coordinate in place processing. Our target are local area large computing facilities composed of tens of thousands of nodes under the same administrative domain. The system should be capable of leveraging massive replication of data to balance read scalability and fault tolerance. Copyright 2009 ACM.

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The Database Management System ( DBMS) used to be a commodity software component, with well known standard interfaces and semantics. However, the performance and reliability expectations being placed on DBMSs have increased the demand for a variety add-ons, that augment the functionality of the database in a wide range of deployment scenarios, offering support for features such as clustering, replication, and self-management, among others. A well known software engineering approach to systems with such requirements is reflection. Unfortunately, standard reflective interfaces in DBMSs are very limited. Some of these limitations may be circumvented by implementing reflective features as a wrapper to the DBMS server. Unfortunately, these solutions comes at the expense of a large development effort and significant performance penalty.

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