Big Data Automation with In-Memory Computing

The future belongs to organizations that develop their competitive edge. Leveraging information in real-time provides this competitive difference. Today’s enterprises are dealing with massive amounts of data, and that data is expanding fast. Mobile and Cloud Computing require even faster paradigms. Risk must be evaluated in real-time. Welcome to the value of in-memory computing.

At this Meetup we'll review the powerful uses of the open source Apache 2.0 licensed in-memory computing solution that provides distributed, clustered, high performance capabilities for OLTP and data analytics. The presentation will address deployments leveraging streaming data, big data and other velocity and volume challenges. From applying HDFS to terabytes of data to SQL-enabled data in-memory, you will learn to architect real-time applications that leverage your existing hardware, frameworks and data.

If you need to gain real-time performance from Hadoop, process 1 Billion TPS, analyze streaming data sources or achieve your application’s performance SLAs—in-memory is the fastest and most cost effective way to do it!

Dmitriy Setrakyan, co-founder and EVP Engineering of the leading open source In-Memory solutions Platform from GridGain Systems will show us how to quickly leverage the 1000x gains that in-memory computing can deliver. He will review the facts and myths of in-memory computing and clarify what’s possible with this increasingly popular technology. His presentation will concentrate on the core capabilities of in-memory computing like clustering and high performance computing, in-memory data grid, streaming and complex event processing (CEP), and Hadoop acceleration.

Refreshments

We will provide pizza and soft drinks during the networking time between 6:30 - 7:00. The presentation will begin at 7:00 PM.