The Need for Speed: Taking Big Data Real-Time
Carl Wright
There is no denying the considerable value that Big Data can provide. Yet despite the hype, a recent Gartner survey found that only 42% of respondents had invested in Big Data technology or were planning to do so within a year. Behind this stunted adoption: costly, legacy solutions that have been too slow and inflexible to deliver on the promise of real-time Big Data analytics.
 
In-memory databases are emerging to solve the performance problem. With terabytes of addressable memory, in-memory solutions are allowing companies to seize the real-time opportunity by gaining insights quicker than their prehistoric counterparts. In-memory databases are providing faster and more predictable performance than disk – delivering unprecedented speed complemented by emerging technologies that combine structured, semi-structured and unstructured data into a unified interface.
 
In this class, we will discuss how in-memory technologies are changing the Big Data landscape, including customer anecdotes from organizations that have reaped the ROI of real-time Big Data analytics.

This class is sponsored by MemSQL.

Level : Overview