Chapter 3In-Memory Analytics

Data are a strategic asset, and organizations are collecting more data than ever before. The availability of so much data creates big opportunities but also bigger challenges on how to analyze all the data in a timely manner. Trends in analytics and data management, along with heightened regulatory and governance requirements, demand new, innovative approaches that can quickly transform massive volumes of data into meaningful and actionable insights. In-memory analytics help to overcome these challenges and enable organizations to analyze extremely large volumes of data very quickly and efficiently. This latest technological innovation provides an entirely new approach to tackle big data by using an in-memory analytics engine to deliver super-fast responses to complex analytical problems. Similar to in-database analytics, this technology eliminates the need to copy and replicate data and offers more superior benefits such as near real-time analyses.

BACKGROUND

Traditionally, computers have two types of data storage mechanisms— physical disk (hard drive) and RAM (random access memory). I can recall owning a computer with a floppy disk, 128MB of disk space and 4 MB of RAM; however those days are long gone. Now, I have the luxury of owning a laptop with a CD ROM drive, 500GB disk storage, and 8GB of RAM. The megabyte has transformed to gigabyte and beyond. In today's world, computers have much more available disk storage than RAM, but reading data ...

Get Leaders and Innovators now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.