HGST SSD 0TS1743 2.5 inch SFF U.2 4096GB Memdrv NVMe SSD MLC 15NM Omaha-MD Bare
At a Glance
Enables scaling of system memory, typically up to 24TiB per 1U server and 96TiB in 4U servers
Delivers DRAM-like performance for keyenterprise applications and workloads
Transparent to existing OS and applications
Promotes server consolidation
Fits most industry-standard server models
Overview
Memory Expansion for the Data Center
The digital economy has created significant demands for both real-time and batch processing of large data sets. IT organizations across the world are leveraging in-memory computing to drive superior application performance and obtain meaningful insights through the use of advanced business analytics.
However, in-memory computing can become bottlenecked by set limitations on the amount of memory available to the server, as well as prohibitive DRAM pricing.
Ultrastar® DC ME200 Memory Extension Drive can be used to scale existing system memory, promote server consolidation, and reduce the complexity of splitting large multi-TB data sets across multiple servers. Ultrastar memory drive provides applications with large amounts of system memory at a fraction of the cost of DRAM. Advanced software algorithms work to maintain near DRAM-like performance across a variety of applications, especially targeting highly parallel workloads with high numbers of transactions. Once installed, the solution is transparent, requiring no changes to the existing OS and application stacks.
Dramatically Scale System Memory
Web application caching in particular requires large amounts of system memory to quickly ingest and analyze vast streams of data from Internet users, transaction events, and IoT devices. High concurrency environments, such as virtualized servers and container-based applications, are prime examples where memory usage can quickly outpace processing capabilities, requiring expensive additional scale-out servers to house the extra memory and virtual machines.
Ultrastar memory drive allows for the transparent expansion of system memory, enabling larger data sets to be used for analytics computations, more data to be stored in front-end web caches, and overall more work that can be accomplished within each server.