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George Crump

The Impact Of High-Availability Flash Appliances

High-availability flash appliances used with software-defined storage can prolong the life of your current storage system while meeting performance demands.

Solid state disk (SSD) storage comes in many forms. It can be placed in the server, in the storage system and on the network. 2012 saw the maturation of one of the oldest categories in solid state: the flash memory storage appliance. Thanks to high-availability hardware and the maturation of storage software, these appliances may now move from niche use to broad adoption.

As I discussed in a recent article, the memory-based storage appliance has evolved into a system that is designed to accept flash in its most optimal form: a memory module instead of a disk drive form factor SSD. These appliances allow flash memory to achieve its maximum potential without supporting legacy hard drive technology. While they often sacrifice data service features, the devices focus on high-performance data movement into and through the appliance. They often also deliver very dense form factors that consume less overall space and power, therefore reducing costs.

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Last year's key addition to these hardware designs was high availability, meaning that the systems no longer have a single point of failure. Previously, flash appliances had to be bought in pairs and mirrored or used only for temporal data.

[ For more on software-defined storage, see What Is Software-Defined Storage? ]

Mirroring a flash appliance has its own issues. First, flash appliances are priced at a premium -- buying two can be painful. Second, many operating systems, hypervisors and databases don't have built-in mirroring capability.

Enter high availability (HA). Companies like Astute Networks, Violin Memory Systems and Texas Memory Systems (now owned by IBM) created devices or configurations designed with no single points of failure, just like their enterprise storage brethren. For only a slightly higher cost, you can buy one unit and get all the availability you need.

HA positions these devices to be more than just solutions to niche problems -- they can become the location for the active primary storage dataset. However, they lack the data services provided by most enterprise storage systems, which flash array vendors claim as the differentiation point.

Enter software-defined storage. The fact that most flash appliance vendors do not offer data services like thin provisioning, snapshots and cloning has become less of a problem as these services increasingly become available through software. In fact, a hypervisor like VMware can even help facilitate the movement of active data to these appliances by way of Storage vMotion.

The combination of HA flash appliances and the maturation of the software-defined storage market has opened up new opportunities for these vendors, making them a viable alternative for users considering a system upgrade. Now users can install these systems as a complement to their current storage system, changing its role to delivering capacity and letting the flash appliance handle performance. The result is a longer life for legacy storage hardware that still keeps up with performance demands.

Our 2012 State Of Servers report takes a look at three major technology trends emerging from our latest survey. Also in the new issue of IT Trends: Performance and endurance gains plus lower cost give multilevel cell flash the edge over expensive single-level cell. (Free registration required.)



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By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



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