The Software In Silicon Data Analytic Accelerator (SWiS DAX) APIs released by Oracle this week signify a sea change for big data and fast data analytic processing. Natively accelerated common analytic functions usable in C, Python, and Java have already shown a 6x lift for a Spark cube building application. Apache Flink and Apache Drill completely eclipse Spark performance so it will be very interesting to see upcoming benchmarks of these higher performing frameworks on SWiS DAX. There is nothing to keep any vendor or group from bench marking with these APIs as they will work with any C, Python, or Java application.
I’m also looking forward to testing performance of SWiS DAX on non-partitionable data sets in a big memory SMP architecture as well. The easy problems are partitionable, and true data discovery should allow any-to-any relations without injecting a-priori partitioning assumptions.
It seems that Oracle’s long standing commitment to developing Sun’s Sparc processors is about to pay off in a very big way for big data and fast data analysts.