The modern workload set has fundamentally changed the nature of and also how we handle data sets. Previously, critical business applications were typically driven by the processing of large, monolithic databases that were comprised of large files. Today, more and…
The data center is a series of networks. There are networks that connect servers to users and networks that connect storage to servers. Even within servers and storage there are networks to connect CPU to IO devices like flash drives…
Modern workloads such as Hadoop, Kafka and machine learning are demanding in terms of the volume of data that must be processed, the speed at which that data much be processed, and the fact that their capacity and performance requirements…
NVMe (Non-Volatile Memory Express) flash drives thrust storage media from the position of the worst performing component of the data center to the best. The technology’s low latency however, exposes other bottlenecks that went previously undetected. The new storage performance…
Hyperscale architectures typically sacrifice resource efficiency for performance by using direct attached storage instead of a shared storage solution. That lost efficiency though, means the organization is spending money on excess compute, graphics processing units (GPUs) and storage capacity that…
Data intensive workloads like Elastic, Hadoop, Kafka and Splunk, are unpredictable, making it very difficult to design flexible storage architectures to support them. In most cases, scale-out architectures utilize direct attached storage (DAS). While DAS delivers excellent performance to the…
Hyperscale applications like Elastic, Hadoop, Kafka and Cassandra typically use a shared nothing design where each node in the compute cluster operates on its data. Hyperscale architectures, to maximize storage IO performance, keep data local to the compute node processing…
In today’s insights economy, much can be gleaned from the hyperscale cloud (Amazon, Google, Azure) providers’ ability to deliver an infrastructure that provides strong degrees of data resiliency and protection, agility, and performance – with minimal intervention from storage administrators.…
A smart and holistic data management platform is the linchpin to enterprise competitiveness, but at this point in time, it remains largely a nirvana that storage managers are chasing. In this article, Storage Switzerland explains what constitutes data management, how…
When the CPU needs data, the role of the storage system is to transfer information into main memory so the CPU can process it. The memory channels between the CPU and main memory is very fast and the number of…
