In-memory data grids (IMDGs) have seen rapid adoption over the last several years driven by the need to help applications scale their performance as workloads grow. Because IMDGs host fast-changing (“operational”) data in memory across a cluster of servers, they also offer the ability to perform real-time analytics on this data as it flows through the grid. Recent advances in IMDG technology now enable Hadoop MapReduce-style analytics to be integrated into the IMDG’s architecture, performing parallel analysis even while operational data is changing. This exciting new capability creates the opportunity for real-time analysis in financial trading systems, credit card fraud detection, power systems monitoring, and many other applications.
This session will explain how to use an IMDG to perform real-time analytics and will describe recent benchmark results that demonstrate its power to deliver fast results for operational systems.