GridGain for z/OS Drives Real-Time Business Processes

GridGain for z/OS is a mainframe-optimized version of the GridGain in-memory computing platform for use on the IBM® z/OS operating system. GridGain for z/OS enables businesses to quickly, seamlessly create solutions for efficient digital transformation of core systems as well as running analytics across their entire data estate to power real-time business processes. The IBM z/OS runs on IBM mainframes and, when using IBM z Integrated Information Processors (zIIPs), runs Java-based applications including the GridGain in-memory computing platform.

The IBM Z platform is used by 44 of the top 50 global banks, 4 of the top 5 airlines, and two-thirds of the Fortune 100. Across the world, IBM Z powers the most critical business systems for top enterprises with 4.1 million core business transactions per second run on IBM Z.

GridGain for z/OS

GridGain for z/OS Editions

GridGain for z/OS is available as a z/OS-enabled version of the GridGain Enterprise Edition or the GridGain Ultimate Edition. Working closely with IBM, the GridGain for z/OS in-memory computing platform has been benchmarked, optimized, and field tested to run seamlessly on the Z Platform.

GridGain for z/OS can be run as an in-memory data grid or an in-memory database. It can also function as a high performance, SQL-driven data cache for analytics data hub use cases.

Use Cases

GridGain for z/OS is a high performance, SQL-driven data access layer which runs on the IBM Z Platform. It is used to connect to data sources including operational databases running on z/OS and data lakes. Real-time analytics can be run on the combined, complete data set held in GridGain and the results can drive real-time business processes. For example, a financial institution can now have a 360-degree customer view based on analyzing all of the data for a particular customer stored in the firm's data lake and transactional database to drive real-time customer interactions for upselling or cross selling additional products. A related use case is driving a successful omnichannel customer experience by using such real-time analytics to drive a seamless customer interaction across all potential touch points with a company.