EGUIDE:
In this e-guide, read about how Australian organisations are coping with the storage challenges of big data, why flash storage is still too expensive for some companies and how NetApp is evolving to keep up with changes in the industry.
EGUIDE:
In this infographic, we take a look at what the most popular primary and secondary storage initiatives are in 2019 as well as how much storage will be maintained on-premise across Europe. Survey results taken from the 2019 IT Priorities survey carried out by ComputerWeekly.com, ComputerWeekly.de and LeMagIT.fr.
EGUIDE:
In this e-guide we look at the basics of Docker storage and backup, key containers capabilities in storage vendors' offers and how containers can be incorporated into the private cloud environment.
EBOOK:
Find out how converged and hyper-converged solutions are delivering an increased level of consistency for today's IT infrastructures by packaging key features of the data center that are designed to go together and also learn how the cloud is being used to optimize these converged workloads.
WHITE PAPER:
This white paper highlights three top ways storage virtualization can help you cost-efficiently tackle some of your toughest challenges associated with data growth.
EGUIDE:
This eGuide introduces variations of cloud computing including using the cloud as a disaster recovery target, the benefits of flash storage, what you should look for in a system as well as the ways to take advantage of the strategies. Finally, analyze the flash storage arrays to help you target which systems are the best pick for storing your data.
EBOOK:
In this buyer's checklist, learn how hyper-converged systems differ from traditional storage systems and find insights into some of their unique features, as well as guidance for evaluating, purchasing and deploying these systems.
WEBCAST:
Evaluator Group Senior Strategist Randy Kearns and VP of Marketing at WekaIO Barbara Murphy dig into this question in this custom webcast; they also examine a high-performance storage system that provides the parallel data access, architecture for multiple data types, and flexible scalability that ML and DL workloads require.
