IBM






In order to derive business value from Big Data, practitioners must have the means to quickly (as in  sub-milliseconds) analyze data, derive actionable insights from that analysis, and execute the recommended actions. While Hadoop is ideal for storing and processing large volumes of data affordably, it is less suited to this type of real-time operational analytics, or Inline Analytics. 

White Paper: In-Memory Databases Put the Action in Actionable Insights



This white paper discusses the concept of shared data scale-out clusters, as well as how they deliver continuous availability and why they are important for delivering scalable transaction processing support. It also contrasts this approach, taken in relational database contex, with clustering approaches employed by NoSQL databases and Hadoop applications, showing the importance.

IDC White Paper: Affordable, Scalable, Reliable OLTP in a Cloud ...