Abstract
The last few years have been exciting for data management system designers. The explosion in user and enterprise data coupled with the availability of newer, cheaper, and more capable hardware have lead system designers and researchers to rethink and, in some cases, reinvent the traditional DBMS architecture. In the space of data warehousing and analytics alone, more than a dozen new database product offerings have recently appeared, and dozens of research system papers are routinely published each year. Among these efforts, one school of thought promotes research on exploiting and anticipating new hardware (many-core CPUs [4, 7, 8], GPUs [3], FPGAs [5, 11], flash SSDs [6], other non-volatile storage technologies). Another school of thought focuses on software and algorithmic issues (column and hybrid stores [1, 10, 13], scale out architectures using commodity hardware [2, 9, 10, 13], optimizations in network and OS software stack [9]). And, at the same time, there are approaches that combine hardware-specific optimizations with from-scratch database software design [12].