Before my current career in data management, I had a previous life as a software developer, working on designing and implementing compilers for Fortran and C for massively parallel processing (MPP) computers, and while I have been working on data quality and BI for the past 13 years or so, I still have a great interest in the high performance computing space. Recently I have had the opportunity to indulge that interest with respect to learning about the distributed/parallel programming model that Google has championed called MapReduce, and its relationship to the use of analytical database management systems.

There are some similarities, some differences, and ultimately, the two paradigms are complementary when it comes to supporting end-user business needs. If you are interested in the thought processes, check out this analysis paper, funded by Vertica, which compares and contrasts both high performance approaches.