Scalable and Smart Storage Class Memory Layer for Big Data

Today, if events change the decision model, we wait until the next batch model build for new insights. By extending fast “time-to-decisions” into the world of Big Data Analytics to get fast “time-to-insights”, apps will get what used to be batch insights in near real time. Enabling this is technology such as smart in-memory data storage, new storage class memory, and products designed to do one or more parts of an analysis pipeline very well. In this talk we describe how Ampool is building on Apache Geode to allow Big Data analysis solutions to work together with a scalable smart storage class memory layer to allow fast and complex end to end pipelines to be built- closing the loop and providing dramatically lower time to critical insights.

Learning Objectives

Explain what SCM means in Big Data, its importance and why it matters
Explain the Big Data analysis loop & system properties needed at each phase
Review Big Data requirements for storage class memory
Demonstrate an in memory big data pipeline Provide benchmark numbers