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In-Database Processing and In-Memory Analytics

  • Pethuru Raj
  • Anupama Raman
  • Dhivya Nagaraj
  • Siddhartha Duggirala
Part of the Computer Communications and Networks book series (CCN)

Abstract

With the ever increasing data and high dependence of digital services for day-to-day jobs, there is a huge opportunity for enterprises and huge risk for security of users. This is why organizations and governments are in dire need to analyze and understand data. Sometimes analyzing data is not just enough, but the speed of arrival at that insight is also extremely important. This is where the in-database processing and in-memory analytics come into picture. Data is huge in size making it suboptimal to move data from corporate SANs to processing servers. Instead of moving the data, moving the processing to the data is the principle advocated by in-database processing, while the in memory focuses on keeping the data completely in memory to increase the processing speed. In this chapter, we will learn and analyze these two and study some use case to improve our understanding.

Keywords

Performance Performance Data Warehouse Complex Event Processing NoSQL Database Analytical Appliance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Pethuru Raj
    • 1
  • Anupama Raman
    • 1
  • Dhivya Nagaraj
    • 1
  • Siddhartha Duggirala
    • 2
  1. 1.IBM IndiaBangaloreIndia
  2. 2.Indian Institute of TechnologyIndoreIndia

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