Synergies of Column Storage and Map Reduce for Big Data Analytics

Jim is the chief product architect for InfiniDB, and CTO at Calpont. InfiniDB’s map-reduce distribution of work enables linear scalability combined with SQL ease of use. A simple create table automatically implements horizontal and vertical partitioning of the data that can be analyzed with fully parallel and distributed execution of inner/outer hash joins, sub-query, correlated sub-query, multi-table hash joins, filters and expressions, group by, and user defined functions.

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Fernanda Foetter is a self described, “computer geek interested in Big Data analyses using High Performance Computing.” She has a background in Particle Physics simulations, Molecular Dynamics and Quantum Chemistry Simulations, and more recently Bioinformatics at Genus PLC. Other interests include application development, parallelization techniques and Big Data curation. At Genus she’s responsible for keeping the clusters running and helping scientists make full use available technology or bringing in new ones to reach their goals. She holds a BS in Physics from Florida International University and an MS in Materials Science Engineering from the University of Florida.

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