Data plays an enormous role in how businesses work, and that role is only growing. As it does, storage management continues to be a top priority for all enterprises. They manage enormous volumes of data across multiple storage environments, including hybrid cloud infrastructure, software-defined storage (SDS), and container-native storage, and need to use storage management strategies that can scale, keep data secured, and enable analysis.
Here are seven trends experts see driving the storage management market in 2023.
Top Trends in Data Storage Management
3) The Unstructured Data Deluge (by Michael Jack, CRO and co-founder of Datadobi)
4) Balancing Performance, Resilience, Efficiency and Simplicity (by Andrew Russell, CRO of Nyriad)
5) Automated Data Management (by David Liberman, founder and CTO of productscience.ai)
6) NVMe-oF (by Peter Corbett, a senior distinguished engineer at Dell)
1. Multicloud and Hybrid Cloud (by Ben Gitenstein, VP of product at storage management company Qumulo, Greg Schulz, an analyst at StorageIO Group)
When companies engage in a major shift to hybrid and multicloud architectures, they are forced to move data first from the data center to the cloud, and then across clouds.
“More businesses will continue to leverage multi-platform, multi-cloud, and hybrid-cloud architectures to get the best of all worlds and serve the many consumers of data in their organizations,” said Ben Gitenstein, VP of product at storage management company Qumulo.
Greg Schulz, an analyst at StorageIO Group, concurred. “Multi-cloud and hybrid cloud remain among the top trends in storage management,” he said. “Companies will be deploying and managing them for many years to come.”
Schulz added that, as enterprises optimize their storage assets from the edge to the core, they are not housing everything in the cloud—much of the data belongs there, but not all. On-premises storage is regaining ground, and some enterprises are moving workloads back to on-premises systems from the cloud.
2. A Better Approach to Data Silos (by Steve Wallo, CTO at Vcinity and Kumar Goswami, co-founder and CEO of data management company Komprise)
Organizations have been struggling with data silos for decades, and it’s costing them time, money, and efficiency.
“Businesses often experience delays in outcomes, sub-optimal processes and high associated costs due to silos,” said Vcinity CTO Steve Wallo. “You’re forced to move or copy your data to be near an application to optimize its performance.”
The ultimate cost of managing data silos reaches far beyond the need to reorganize. The solution? Finding a quicker way to move or remotely access data to centralize it in one location while still retaining the ability to access and use it from anywhere.
“Whether data sits on-prem, in the cloud, or at the edge, there are ways to allow businesses to completely eliminate data silos altogether, ultimately enhancing cost efficiencies, workflows, and security,” Wallo said.
Seeking to eliminate silos takes too much time and energy, and it’s unlikely a business can fully get rid of them, said Kumar Goswami, co-founder and CEO of data management company Komprise.
“The answer is solutions that look across the data—search, classify, secure, visualize it in place—without forcing you to put all your data into one location or technology,” he said.
3. The Unstructured Data Deluge (by Michael Jack, CRO and co-founder of Datadobi)
The growth of unstructured data continues to be a storage management trend. As organizations generate and collect more data, they are challenged to keep control over cost, manage risk, and to report on and address the impact on sustainability of accumulating data—all while continuing to find ways to extract the maximum value from it. This trend is driving the adoption of intelligent and automated data management solutions that can handle massive data sets, provide real-time insights, and optimize data workflows.
“The exponential growth of unstructured data is driving the need for efficient data management solutions,” said Michael Jack, CRO and co-founder of Datadobi. “Rampant data growth coupled with the adoption of cloud computing, advancements in AI and the emphasis on data privacy and security are the key trends shaping the future of data storage management.”
Data management platforms must become more intelligent, must be cloud-enabled, must have more intelligence built in, and must be able to cope with ever larger data sets. Gaining insight and proactively managing huge amounts of unstructured data will allow organizations to address the complex mixture of cost control, management of risk, and operationally sustainability—all while extracting maximum value from rapidly accumulating data.
4. Balancing Performance, Resilience, Efficiency, and Simplicity (by Andrew Russell, CRO of Nyriad)
Digital business processes are becoming more prevalent. And more so than ever, data has become the driver of competitive advantage, compelling organizations to adopt innovative storage solutions to meet business objectives.
As unstructured object and file data continues to grow at a breakneck pace driven by demanding applications and workloads, companies are looking for data storage options that deliver the optimal balance of performance, resilience, efficiency, and simplicity, said Andrew Russell, CRO of Nyriad.
To truly leverage data as a strategic asset, businesses require that their underlying storage systems provide a high, yet consistent performance experience. If data is unavailable for even a short period of time, it is disruptive to their applications, so resilience is of equal importance.
“With the growth in the amount of data being produced, storage systems that efficiently handle all data types seamlessly will simplify the operational environment by reducing complexity,” Russell said. “Ensuring the right balance between performance, resilience, efficiency, and simplicity will allow organizations to achieve better decision-making capabilities in the digital business era.”
5. Automated Data Management (by David Liberman, founder and CTO of productscience.ai)
David Liberman, founder and CTO of productscience.ai, sees automation in data collection and storage optimization as a major trend in data management. With the recent surge in artificial intelligence (AI) and growing interest in the practical applications of machine learning (ML), breakthroughs in data storage management practices are anticipated, particularly in front-end applications.
“By leveraging modern ML algorithms, organizations can identify opportunities for optimizing data collection and traffic at the client level of the application,” Liberman said. “ML and AI automation enable in-depth code analysis that was previously unattainable.”
Liberman said it is now possible to automatically analyze the code of each event and detect issues such as:
- Suboptimal production of events by different modules within the application
- Lack of compression in frequently occurring events
- Presence of unoptimized formats, such as using a string format for a Universal Unique Identifier (UUID), which negatively impacts the cost of storing and processing events in Google Cloud Bigtable
The initial beneficiaries of this trend might be major data storage consumers that are among the biggest spenders, such as Netflix, Twitch, LinkedIn, Bytedance, and Apple. However, any organization that operates popular apps that transmit data to and from cloud environments or third-party hosted infrastructures stands to gain from these advancements. Moreover, companies offering SaaS services integrated into the production of other apps that exchange data with cloud, edge, or hosted environments will also benefit.
6. NVMe-oF (by Peter Corbett, a senior distinguished engineer at Dell)
Non-Volatile Memory Expess (NVMe) and NVMe over Fabrics (NVMe-oF) provide speed and automation for data management while reducing complexity and resolving storage bottlenecks. Complexity is a major challenge for storage personnel that inhibits digital transformation, according to Peter Corbett, a senior distinguished engineer at Dell.
Corbett touts NVMe-oF as a way to:
- Rapidly scale infrastructure, without having to proportionally add skilled administrators.
- Speed delivery of services to end users, reducing friction and latency in the business workflows.
- Reduce errors, which are costly to identify, diagnose, and resolve.
“NVMe-oF is an enabler for flexible provisioning of software-defined storage, allowing richer connectivity with good security,” he said. “Combining smarter management software with intelligent infrastructure allows businesses to free themselves from the monotony of storage management and focus more on driving outcomes that impact their bottom line.”
Greg Schulz said he believes that NVMe-oF as well as NVMe-over-TCP are no-brainers in modern storage management, given their flexibility, performance, interoperability, and deployment capabilities.
7. Storage-as-a-Service Model (by David Friend, co-founder and CEO at the storage provider Wasabi Technologies)
All of these trends have given rise to the growing popularity of storage provided as-a-service. The benefits noted above such as reduced complexity, simplicity, resilience, automation, performance, efficiency, and being able to do more with less are part of the value proposition of storage-as-a-service.
That market is dividing into a couple of areas, according to David Friend, co-founder and CEO at the storage provider Wasabi Technologies. Hyperscalers like Amazon, Microsoft, and Google will gain the bulk of business due to the extent of their platforms and the sheer number of functions and integrations. However, plenty of organizations want easy, quick and inexpensive access to data as well as a more personalized approach to as-a-service infrastructures.
“This will leave room for niche cloud vendors offering best-of-breed services,” Friend said, “and we will see the cloud market continue to diversify with more flexible, personalized, and cost-effective cloud storage solutions.”
