Since the 1970's, database systems have been "compute-centric".  When a computation needs the data, it requests the data, and the data are pulled through the system.  This is problematic for two reasons. First, requests for data naturally incur high latency as the data are pulled through the memory hierarchy, and second, it makes it difficult or impossible for multiple queries or operations that are interested in the same data to amortize the bandwidth and latency costs associated with their data access.

This talk describes a purely-push based, research prototype analytic database system called DataPath that is being developed at Rice University and the University of Florida.  DataPath is "data centric".  In DataPath, queries do not request data.  Instead, data are automatically pushed onto processors, where they are then processed by any interested computation.  The talk will describe a multi-terabyte benchmark of DataPath which argues that "data centric" design makes for a very lean and fast database system.

Chris Jermaine is an associate professor at Rice University where he studies statistical databases. Prior to coming to Rice in 2009, Chris was at the University of Florida.  Chris is the recipient of a 2008 Alfred P. Sloan Foundation Research Fellowship, a National Science Foundation CAREER award, and a 2007 ACM SIGMOD Best Paper Award. In his spare time, Chris enjoys running, gardening, and outdoor activities such as hiking, climbing, and whitewater boating. In one particular exploit, Chris and his wife floated a whitewater raft (home-made from scratch using a sewing machine, glue, and plastic) over 100 miles down the Nizina River (and beyond) in Alaska.