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A Database Grid Solution Increasing Ease of Use and Scalability of Large, Distributed, Heterogeneous Databases By Providing Implicit Queries to a Virtual Data Warehouse--PioCon Technologies, Inc., 1952 McDowell Road, Suite 300, Naperville, IL  60563-1123; 630-579-0800, www.piocon.com
Mr. Matthew G. Vranicar, Principal Investigator, vranicar@piocon.com 
Mr. Matthew G. Vranicar, Business Official, vranicar@piocon.com 
DOE Grant No. DE-FG02-02ER83434
Amount:  $750,000  

As high energy and nuclear physics data needs grow, so too do the scale, size, complexity, and cost of solutions for storing and querying large databases. This project will develop technology that will allow users to submit a single query that can be routed to multiple, distributed, heterogeneous databases.  By combining the various databases into a “virtual data warehouse”, this Database Grid Solution will provide a single result set, masking the complexities required to find the actual data sources.  Phase I extended the design of an existing  query mechanism, the Sequential Data Access via Meta-data (SAM) Database Server, to increase the robustness and scalability of the current implicit query capabilities.  The new designs included more robust grammar parsing and syntax checking of queries, integration of Grid security mechanisms, database resource usage monitoring and limiting, and extended user interface capabilities.  With software leveraged from other sources, Phase II will integrate these designs into the Grid framework, ensuring that the end solution readily adapts to existing Grid standards and emerging Grid specifications.  A working example will be produced by adapting the technology to the current SAM Database Server   

Commercial Applications and Other Benefits as described by awardee:  The Database Grid Solution could be applied to any ogranization that relies upon a complex, multi-database environment.  For example, large conglomerates attempting to leverage their existing worldwide data assets could do so without incurring the significant cost of combining them into one data source.  Local not-for-profit groups could pool their data resources, providing a stronger service for their user community.  Organizations involved in mergers and acquisitions need not spend a great deal of effort combining databases, but merely could deploy a virtually combined data warehouse.