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Blink: Not your father's database!

Blink: Not your father's database!
Barber, RonaldBarber, PeterCzech, MarcoDraese, OliverHo, FrederickHrle, NamikIdreos, StratosKim, Min-SooKoeth, OliverLee, Jae-GilLi, Tianchao TimLohman, GuyMorfonios, KonstantinosMueller, ReneMurthy, KeshavaPandis, IppokratisLin QiaoRaman, VijayshankarSzabo, SandorSidle, RichardStolze, Knut
DGIST Authors
Kim, Min-Soo
Issue Date
5th International Workshop on Enabling Real-Time Business Intelligence, BIRTE 2011, Held at the 37th International Conference on Very Large Databases, VLDB 2011, 126 LNBIP, 1-22
Article Type
Conference Paper
The Blink project's ambitious goals are to answer all Business Intelligence (BI) queries in mere seconds, regardless of the database size, with an extremely low total cost of ownership. It takes a very innovative and counter-intuitive approach to processing BI queries, one that exploits several disruptive hardware and software technology trends. Specifically, it is a new, workload-optimized DBMS aimed primarily at BI query processing, and 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. Ignoring the general wisdom of the last three decades that the only way to scalably search large databases is with indexes, Blink always performs simple, "brute force" scans of the entire 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 incorporated into two products: (1) an accelerator appliance product for DB2 for z/OS (on the "mainframe"), called the IBM Smart Analytics Optimizer for DB2 for z/OS, V1.1, which was generally available in November 2010; and (2) the Informix Warehouse Accelerator (IWA), a software-only version that was generally available in March 2011. We are now working on the next generation of Blink, called BLink Ultra, or BLU, which will significantly expand the "sweet spot" of Blink technology to much larger, disk-based warehouses and allow BLU to "own" the data, rather than copies of it. © 2012 Springer-Verlag.
Springer Verlag
Related Researcher
  • Author Kim, Min-Soo InfoLab
  • Research Interests Big Data Systems; Big Data Mining & Machine Learning; Big Data Bioinformatics; 데이터 마이닝 및 빅데이터 분석; 바이오인포메틱스 및 뉴로인포메틱스; 뇌-기계 인터페이스(BMI)
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Department of Information and Communication EngineeringInfoLab2. Conference Papers

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