HPE reveals a modular in-memory computing platform

Hewlett Packard Enterprise (HPE) has revealed the HPE Superdome Flex, a scalable and modular in-memory computing platform that enables enterprises of any size to process and analyze massive amounts of data and turn it into real-time business insights.

In a world transformed by exponential data growth, customers face a complex dilemma – how to handle unprecedented data flows while maintaining business continuity and agility to quickly respond to business changes. One way companies are tackling this challenge is by leveraging in-memory databases, such as SAP HANA, Oracle Database In-Memory and Microsoft SQL Server. HPE is the global leader for SAP HANA as approximately 50 per cent of SAP HANA server deployments are on HPE systems. 

In order to harness the full value of in-memory computing, the underlying infrastructure must be capable of addressing large data sets and process analytics without slowing transactions to achieve real-time insights. HPE Superdome Flex has a modular design that scales so enterprises can keep pace with evolving data demands, while unmatched reliability capabilities provide a resilient platform that safeguards critical workloads.

“Customers want to harness all of their data to derive actionable insights in real-time to make more impactful business decisions,” said Randy Meyer, vice president and general manager, Synergy & Mission Critical Servers, Hewlett Packard Enterprise. “With HPE Superdome Flex, customers can capitalize on in-memory data analytics for their most critical workloads and scale seamlessly as data volumes grow.”

Designed with Memory-Driven Computing principles, HPE Superdome Flex provides a shared pool of memory over an ultra-fast fabric that’s capable of scaling from 768GB to 48TB in a single system, delivering unmatched compute power for the most demanding applications.

The platform has a modular design that scales from four to 32 sockets in four-socket increments. This equips customer environments of all sizes with in-memory computing that can expand seamlessly and cost-efficiently as needs increase.