Business Analytics in (a) Blink
Ronald Barber, Peter Bendel, Marco Czech, Oliver Draese, Frederick Ho, Namik Hrle, Stratos Idreos, Minsoo Kim, Oliver Koeth, Jae-Gil Lee, Tianchao Tim Li, Guy M. Lohman, Konstantinos Morfonios, René Müller, Keshava Murthy, Ippokratis Pandis, Lin Qiao, Vijayshankar Raman, Richard Sidle, Knut Stolze · Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands · 2012
The Blink project’s ambitious goal is to answer all Business Intelligence (BI) queries in mere seconds, regardless of the database size, with an extremely low total cost of ownership. Blink is a new DBMS aimed primarily at read-mostly BI query processing that exploits scale-out of commodity multi-core processors and cheap DRAM to retain a (copy of a) data mart completely in main memory. Additionally, it exploits proprietary compression technology and cache-conscious algorithms that reduce memory bandwidth consumption and allow most SQL query processing to be performed on the compressed data. Blink always scans (portions of) the data mart in parallel on all nodes, without using any indexes or materialized views, and without any query optimizer to choose among them. The Blink technology has thus far been incorpo