Brown University - Data Management Group » A Comparison of Approaches to Large-Scale Data Analysis: MapReduce vs. DBMS Benchmarks
Overview The following information is meant to provide documentation on how others can recreate the benchmark trials used in our SIGMOD 2009 paper. Our experiments were conducted on a 100-node cluster at the University of Wisconsin-Madison; each node had a single 2.40 GHz Intel Core 2 Duo processor running 64-bit Red Hat Enterprise Linux 5 (kernel version 2.6.18) with 4GB RAM and two 250GB SATA-I
HadoopDB Project
HadoopDB An Architectural Hybrid of MapReduce and DBMS Technologies for Analytical Workloads. HadoopDB is: A hybrid of DBMS and MapReduce technologies that targets analytical workloads Designed to run on a shared-nothing cluster of commodity machines, or in the cloud An attempt to fill the gap in the market for a free and open source parallel DBMS Much more scalable than currently available parall
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