Trends That Will Transform Storage Industry in 2016

This article has been written by Jérôme Lecat, CEO of Scality, Inc.

Predictions for 2016: Trends that Will Transform the Storage Industry

In late 2014 I made some predictions about two trends that would shake up the storage industry over the next year and eventually phase out IT SAN and NAS storage as we know it.

SaaS Storage
More and more small- and medium-sized organizations would delegate not only software but storage to SaaS providers such as Microsoft Office 365, Salesforce and Box, and as a result wouldn’t be buying much traditional storage from then on. SaaS providers, too, would continue forgoing the EMC, NetApp SAN/NAS storage model for the hyperscale, software-defined, hardware independent, shared nothing architecture model of Facebook, Amazon and Google. The result: traditional storage industry players such as EMC and NetApp could wave goodbye to about $20 billion.

Performance and Scalable Storage
Larger enterprises and other data intensive organizations this year reached a fork in the storage road, which led many to run their own software-defined disk storage for scale and silicon in the form of flash arrays, hybrid storage and converged storage for performance-hungry, latency sensitive applications such as streaming video or financial modeling. The result: again, traditional storage players would see their market slashed by start-ups in these two emerging categories.

One year later, these trends are taking shape as the revenues and profitability of legacy enterprise storage giants continue to take big revenue hits. In the second quarter of 2015, EMC’s revenues declined 4% compared to last year; NetApp’s dropped 19.6%; and IBM’s fell a whopping 28.9%, according to IDC.

This year, two other emerging trends promise to accelerate the process:
 
Deep Learning
Big data analytics have been around for a few years, digging through huge volumes of information amassed in enterprise databases, as well as social media and consumer data, to recognize and exploit small and big hidden trends for competitive advantage, predictive maintenance, and other purposes. These and other strategies save organizations millions, enhance revenues, improve services, and advance the general quality of life.

Deep Learning takes off from big data, incorporating the artificial intelligence and neural network movements of yore to yield systems that can harness information, multilayered algorithms, and software to actually mimic human learning. These systems can teach themselves to, for example, understand spoken commands, sort through photos, recognize objects and faces, discover potential new drugs or a carry out a host of other breakthrough functions on their own, automatically. Today you can even find robots that can walk and learn any number of new things by example – after example, after example, after example.

Emerging Internet of Things
IoT promises to transform the Web from a medium of human and information interaction to interaction among appliances, machines, components, systems and humans – with humongous volumes of information produced daily. Just a single airline flight can produce 1TB or more of IoT information from scores of airplane component sensors. When you imagine one hundred thousand flying airplanes producing a daily total of 100PB of data, the volume of
information to be mined for trends, maintenance issues and other revelations large and small is almost unimaginable.

Deep learning, big data and IoT will save lives by preventing airplane and automobile crashes, diagnosing and treating patients, discovering powerful new drugs, and on and on.

In fact, in more and more industries the value of information and software has begun to outgrow the value of the traditional products that manufacturers and retailers have built and sold for years. Many new types of businesses have and will be created just to harness this information, while sharing information across industries and industry players in manufacturing, distribution and other sectors will lead to powerful new innovations.

In such a data- and information-hungry environment, in which every aspect of corporations’ and our lives is data driven, and all data past, present and future interactions are a potential gold mine of business and other insight, traditional limited scale storage models are doomed in favor of hyperscale and performance. Hyperscale is necessary to store and harness endless quantities of big data-, IoT- and Deep-learning-related information nearby for quick analysis, continuously. Performance is the goal when real time and low latency are required.

This level of scalability can only come from software-defined storage, just as compute and networks have moved to an intelligent, scale-out software-defined architecture.

In the traditional IT storage environment, scale leads inevitably to complexity, instability and performance issues.

However, the hyperscale, storage-defined, shared nothing model
is well on the way to achieving:

• Technical Scalability, in which systems become more stable and reliable as they grow.
• Operational Scalability, where systems become simpler, not more difficult, to manage.
• Performance Scalability, where system performance scales as the system scales.
• Cost Scalability, in which the system cost falls as the system scales.
• Time Scalability, wherein the duration that information is stored is relative to changing expectations. Today, a lifetime or more is the time frame for storing and accessing information, rather than a few weeks, months or years. I’ve met with people who want their Facebook posts to be conserved after they’ve passed.

This dynamic approach to scalability has already been achieved by the likes of Google, Amazon and Facebook, and represents the architecture that the Scality RING is providing to a host of organizations looking for a hyperscale storage solution. I can only remember one time I was unable to load my Facebook page – keeping in mind that Facebook recently surpassed 1 billion users daily. While we at Scality provide the software to store the data at a massive scale, others will continue to find new, breakthrough ways to harness it and present it to you.