Companies are challenged with using unprecedented volumes of data to achieve real business impact. Taking advantage of data is often easier said than done. New applications such as artificial intelligence, machine learning, deep learning, real-time analytics, and Internet of Things (IoT), all of which are memory hungry and fueled by massive datasets, compound this challenge. By using a promising new memory tier, NetApp helps customers put their data to work without having to rearchitect their critical applications. MAX Data gives customers the tools to unlock the value of enormous datasets and extend a Data Fabric strategy all the way into their servers with applications and data that are critical to their business.
“With NetApp MAX Data now supporting Intel Optane DC persistent memory, organizations can accelerate data pipelines across an entire enterprise to power applications such as Oracle and MongoDB with the simplicity, choice, and scale necessary for real business impact,” said Joel Reich, executive vice president, Storage Systems and Software, NetApp. “With the volume of data generated and managed across on-premises data centers, IoT devices and sensors, as well as in hybrid cloud environments, having a Data Fabric strategy that spans edge, core, and cloud is essential to business success.”
“Customers can unlock the value of their data stockpiles with the powerful combination of 2nd generation Intel Xeon Scalable processors and Intel Optane DC persistent memory,” said Jennifer Huffstetler, vice president and general manager, Datacenter Product Management and Storage at Intel. “Working with innovators like NetApp will help us move, store and process more data than ever before.”
MAX Data is the industry’s first enterprise storage solution using Intel Optane DC persistent memory in servers to store persistent data delivering affordable, memory-like low latency and flash-like capacity, without any rewrites required to application code, allowing companies to take full advantage of the benefits of real-time apps.