Synergies of Column Storage and Map Reduce for Big Data Analytics

Moderated by:
Jim Tommaney (InfiniDB)
Fernanda Foertter (Genus plc)
Sponsored Session, Ballroom G

Demands for real-time analytics to derive information, patterns, and revenue from Big Data have left legacy DBMS technologies in the dust. Two foundational technologies have proven to be critical to handle today’s data scale problems – 1) the tremendous parallelism delivered by today’s multi-core/distributed server, and 2) column storage to solve the I/O bottleneck when analyzing large data sets.

In this session, Jim Tommaney will provide an overview of column store databases, the benefits and where companies are implementing them in their organizations. He will also discuss specifics of the InfiniDB Map Reduce style distribution framework and how it helps provide linear scalability for SQL operations. Together, these have tremendous synergies to provide companies a new level of performance to attack big data analytics in a simplistic and scalable manner.

This session is sponsored by Calpont Corporation

Photo of Jim Tommaney

Jim Tommaney


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.

Photo of Fernanda Foertter

Fernanda Foertter

Genus plc

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.


  • EMC
  • Microsoft
  • HPCC Systems™ from LexisNexis® Risk Solutions
  • MarkLogic
  • Shared Learning Collaborative
  • Cloudera
  • Digital Reasoning Systems
  • Pentaho
  • Rackspace Hosting
  • Teradata Aster
  • VMware
  • IBM
  • NetApp
  • Oracle
  • 1010data
  • 10gen
  • Acxiom
  • Amazon Web Services
  • Calpont
  • Cisco
  • Couchbase
  • Cray
  • Datameer
  • DataSift
  • DataStax
  • Esri
  • Facebook
  • Feedzai
  • Hadapt
  • Hortonworks
  • Impetus
  • Jaspersoft
  • Karmasphere
  • Lucid Imagination
  • MapR Technologies
  • Pervasive
  • Platform Computing
  • Revolution Analytics
  • Scaleout Software
  • Skytree, Inc.
  • Splunk
  • Tableau Software
  • Talend

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