We used the latest release of DBMS-X, a parallel SQL
DBMS from a major relational database vendor that stores data in
a row-based format. The system is installed on each node and configured to use 4GB shared memory segments for the buffer pool
and other temporary space. Each table is hash partitioned across
all nodes on the salient attribute for that particular table, and then
sorted and indexed on different attributes (see Sections 4.2.1 and
4.3.1). Like the Hadoop experiments, we deleted the tables in DBMSX and reloaded the data for each trial to ensure that the tuples was
uniformly distributed in the cluster.