DataBank’s Head of Sustainability Jenny Gerson offers commentary on nuclear energy’s evolving role in the data center. This article originally appeared in Insight Jam, an enterprise IT community that enables human conversation on AI.

The data center industry continues to grow, fueled by increased demand for AI, cloud computing, and digital products and services that have become an essential part of everyday life. However, this rapid growth also presents a real challenge since data centers already consume massive amounts of energy, placing immense pressure on power grids and raising serious sustainability concerns.

According to Goldman Sachs Research, power demand from data centers is projected to rise by more than 160 percent by 2030 as compared to 2023 levels. While renewable energy sources such as solar and wind can help meet some of the demand, they don’t produce power consistently enough to be the only energy source for data centers.

To address this scenario – and potentially future-proof their businesses – the entire industry is now exploring nuclear energy as a reliable, carbon-free power source to meet its escalating energy needs. For proof, consider these recent developments:

• Amazon Web Services (AWS) recently signed a contract for 960 megawatts (MW) of capacity from a nuclear power plant in Pennsylvania.

• Microsoft also signed a deal to secure electricity for its Mid-Atlantic region from the Three Mile Island nuclear power plant.

• Google announced its own deal where it will use small nuclear reactors to power its AI data centers. The company hopes to bring its first reactor online by 2030.

• Many European governments have already demonstrated their commitment to nuclear energy as part of sustainable operations.

These moves represent a larger shift in how the data center industry is thinking about its long-term energy strategy. As power demands continue to rise, nuclear energy is emerging as a viable solution to support future growth.

The Benefits of Nuclear Power Plants for the Data Center Industry

Unlike solar and wind, which depend on weather conditions as well as batteries and other storage options, nuclear power is capable of generating electricity around the clock, ensuring consistent energy availability. This is especially critical for data centers, which require uninterrupted power to maintain uptime, support AI workloads, meet customers’ SLAs, and provide seamless digital experiences.

In addition to benefits related to reliability, nuclear energy aligns with the industry’s sustainability goals by reducing the reliance on fossil fuels. Data center operators are under increasing pressure to minimize their carbon footprint – for example, DataBank has announced its commitment to net carbon neutrality by 2030 – and while renewable energy sources play a role, they still require backup from coal or natural gas plants. Nuclear power produces zero carbon emissions during operation, making it a viable option for any data center looking to reduce its reliance on fossil fuel-based energy and meet similar net-zero goals.

Small modular reactors (SMRs) are now gaining attention as a suitable nuclear option for data centers due to their smaller size, lower cost, and potential for faster development. When deployed near data center hubs, SMRs can reduce transmission losses and increase overall energy efficiency. Although the initial cost of building SMRs remains high, their long lifespan and ability to generate power at a predictable cost make them an attractive long-term solution for meeting data center’s energy demands.

Navigating the Challenges of Nuclear Power

Yet it’s safe to say that nuclear power also presents several real challenges that the data center industry must carefully consider.

One of the most significant is the high upfront costs and long development timeframes associated with building new nuclear plants and SMRs. Hyperscalers and data center operators must also contend with complex, time-consuming regulatory hurdles and permitting processes, which could delay or even derail potential projects.

Another key concern is nuclear waste. While nuclear energy itself produces no carbon emissions, it does create radioactive waste that must be stored safely for decades, if not centuries. Although modern advancements in waste recycling and storage have improved, the long-term disposal of spent fuel remains a contentious issue that may influence a “not-in-my-backyard” reaction from communities where the reactors may go.

Additionally, nuclear energy continues to face public skepticism, in part due to high-profile accidents that have left lasting concerns about safety and environmental risks. While newer reactor designs are significantly safer, overcoming public and political resistance may be a challenge for widespread adoption in the data center industry.

The Path Forward: Nuclear Energy in the Data Center Industry

With significant investments from the private sector in emerging technologies, the opportunity for more efficient, cost-effective nuclear power is becoming increasingly viable and is likely to be a significant source of energy in the future. For data center operators looking to access reliable, low-carbon energy, nuclear power can be a reliable, scalable option in a larger energy strategy to best meet the challenges of an increasingly energy-demanding industry.

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Continuity Software’s VP of Marketing Doron Youngerwood offers commentary on various exploitable storage and backup vulnerabilities. This article originally appeared in Insight Jam, an enterprise IT community that enables human conversation on AI.

On May 1^st, enterprise backup vendor, Commvault revealed that an unknown nation-state threat actor breached its Microsoft Azure environment by exploiting CVE-2025-3928.

That wasn’t the only vulnerability making headlines. A few days earlier, the U.S. Cybersecurity and Infrastructure Security Agency (CISA) officially added a significant security flaw affecting Broadcom’s Brocade Storage Fabric OS to its authoritative catalog, underscoring the urgent need for remediation across enterprise and government environments.

The vulnerability has the potential to allow local attackers with administrative privileges to execute arbitrary code with full root access.

This escalation of privilege could enable a complete compromise of the underlying storage network infrastructure, posing significant risks to data integrity and operational continuity.

Not Isolated Cases: A Growing List of Exploited Vulnerabilities

The exploitation of Commvault and Brocade is far from isolated incidents. In recent months, multiple vulnerabilities in storage and backup solutions have been discovered and actively exploited. Examples include:

Veeam Backup & Replication:

CVE-2022-26500 and CVE-2022-26501: These vulnerabilities allow remote, unauthenticated attackers to execute arbitrary code. They were actively exploited by ransomware groups like Monti and Yanluowang shortly after discovery, emphasizing the importance of timely patching.

MinIO:

CVE-2023-28432: This vulnerability in MinIO’s Multi-Cloud Object Storage framework allows attackers to return all environment variables, including sensitive information like MINIO_SECRET_KEY and MINIO_ROOT_PASSWORD.

Attackers were caught exploiting the above MinIO vulnerability, as reported by CISA.

Veritas Backup Exec:

CVE-2021-27876: This vulnerability allows unauthorized file access through the Backup Exec Agent.

This vulnerability had been actively exploited, highlighting the risks associated with unpatched backup solutions.

Oracle ZFS Storage Appliance:

CVE-2020-14871: Easy-to-use, actively exploited vulnerability that allows unauthenticated attacker to compromise the system, causing high impacts to confidentiality, integrity, and availability. 

Why Storage & Backup Security Matters More Than Ever

From ransomware to insider threats, if your primary storage is compromised, hundreds or thousands of workloads — databases, containers, VMs — can go down in a flash.

Worse still, if your backup systems are compromised, there’s no Plan B. No way to recover. You’re out of options.

On average, each enterprise storage or backup device has 10 vulnerabilities, including 5 critical or high-severity ones. Yet most organizations have limited visibility into these weaknesses.

Two Key Steps to Fortify Your Storage & Backup Systems

1. Build a Secure Configuration Baseline

Define secure settings per product (e.g. Dell, Pure, Hitachi Vantara, NetApp, Rubrik, Cohesity) – and ensure they’re reviewed and refreshed regularly. A secure baseline includes both system-level and security controls that reflect vendor guidance and real-world attack patterns.

2. Perform a Gap Assessment

Vulnerability and Patch Management

1 Ability to scan our Storage & Backup appliances?

2 Authenticated scan for vulnerabilities and missing patches ? Runs Platform-Specific APIs / Commands?

3 Automatic detection and remediation validation? (Patch / mitigating configuration)

4 Solid inventory of all Storage & Backup arrays, appliances, nodes & software?

Security Baseline, Configuration Compliance and Drift Management

5 Defined target system & security settings for Storage & Backup Platforms?

6 Repeatable way to assess security misconfigurations? Continuous drift detection?

Knowledge

7 Expertise in securing Storage & Backup technologies?

8 Researched security best practices & hardening instructions for Storage & Backup Platforms?

Gap assessments surface weak spots you didn’t know existed.

What a Complete Storage & Backup Security Program Looks Like

Storage and backup systems are your organization’s most critical — and ironically most overlooked — assets. They deserve the same security rigor as endpoints, networks, and apps.

A well-architected Security Posture Management plan for storage and backups includes:

• Vulnerability management tailored to the environment
• Secure configuration enforcement
• Real-time anomaly detection (block and file-level)
• Compliance mapping (PCI DSS, NIST, ISO, HIPAA, etc.)
• Integration with tools like ServiceNow, Qualys/Rapid7/Tenable, CyberArk, CyberSense, Varonis, and others

Solutions like StorageGuard addresses these gaps by continuously evaluating and enforcing best practices, ensuring that backup systems remain resilient against cyber threats. Organizations that implement StorageGuard for their backup environments significantly reduce the risk of ransomware attacks, data breaches, and compliance failures, ultimately strengthening their overall security posture.

The post Exploitable Storage and Backup Vulnerabilities appeared first on Best Enterprise Data Storage Software, Solutions, Vendors and Platforms.

Executive Editor Tim King highlights the overarching AI impact on data storage jobs, to help keep you on-trend during this AI moment.

In 2025, it’s increasingly clear that artificial intelligence (AI) is revolutionizing the data storage landscape—and not just in terms of the technology itself, but in how storage professionals do their jobs. As AI becomes deeply embedded in storage systems, operations that once relied on manual provisioning, tiering decisions, and performance tuning are now handled by intelligent software and self-optimizing hardware. While this brings undeniable gains in efficiency and scale, it’s also fundamentally reshaping the roles, responsibilities, and required skill sets of those who work in data storage.

To help you understand the shifting terrain, the Solutions Review editors have broken down the core ways AI is disrupting storage job functions, what storage pros must do to stay relevant, and how the future of this discipline is being redefined by automation, abstraction, and acceleration.

Note: These insights were informed through web research using advanced scraping techniques and generative AI tools. Solutions Review editors use a unique multi-prompt approach to extract targeted knowledge and optimize content for relevance and utility.

AI Impact on Data Storage Jobs: How Has AI Changed the Data Storage Workforce?

AI is making enterprise storage smarter and more self-sufficient than ever. Modern storage systems now leverage machine learning to predict capacity needs, detect anomalies, auto-tier data, and proactively remediate performance issues. As storage becomes increasingly software-defined and cloud-integrated, traditional tasks such as LUN creation, RAID configuration, and manual performance tuning are rapidly vanishing. But this isn’t just about efficiency gains—it’s about a new operational model that requires fewer hands-on tasks and more strategic oversight.

Intelligent Tiering and Storage Optimization

AI-driven storage systems like those from Pure Storage, NetApp, and Dell use real-time analytics to classify and move data across performance and archival tiers with zero manual input. These systems analyze usage patterns, predict hot and cold data trends, and automatically rebalance workloads to optimize performance and cost.

For storage admins, this means less time spent managing volumes and deciding what data lives where. The shift is clear: your value is no longer in making those decisions—but in setting the policies, defining the business logic, and ensuring that AI-driven automation aligns with compliance and organizational goals.

Predictive Failure Detection and Self-Healing

AI has dramatically improved the way hardware health and data durability are managed. Storage platforms now use telemetry and anomaly detection to identify impending drive failures, degraded IOPS, or latent bit errors—often remediating issues before they impact availability. Some systems even initiate preemptive migration or repair workflows automatically.

This is reducing the need for reactive firefighting, overnight support rotations, and routine hardware inspections. Storage pros are moving from being first responders to becoming strategic monitors—reviewing alerts, tuning models, and refining detection thresholds. The “break/fix” days are fading. Instead, expect to be more involved in auditing AI behavior and training systems to get better over time.

AI-Driven Data Lifecycle Management

Managing data lifecycles—archiving, retention, and deletion—has long been a compliance headache. AI is now stepping in to automate retention enforcement, monitor data access frequency, and suggest or initiate archival based on access patterns and legal requirements.

Storage roles tied to compliance are being reimagined. Instead of managing tape libraries or enforcing policies manually, professionals are being asked to oversee AI models that classify data types, flag anomalies, and manage end-of-life procedures. Fluency in data governance frameworks and storage-centric AI tools is quickly becoming table stakes.

Software-Defined and Cloud-Native Storage

With the rise of software-defined storage (SDS) and storage-as-a-service (STaaS), more organizations are abstracting away the hardware layer altogether. AI further accelerates this shift, enabling autonomous provisioning, intelligent data placement, and cloud tiering across hybrid environments.

Traditional storage admins who built careers managing SANs, NAS boxes, and physical arrays are feeling the pinch. The roles of tomorrow require comfort with APIs, orchestration tools, and hybrid cloud consoles. Expect to spend more time working with Infrastructure as Code (IaC), Kubernetes operators, and AI-tuned capacity planning tools than racking disks.

A 2024 ESG Research report found that 57% of enterprises using AI-augmented storage systems cut manual provisioning tasks by more than half, and 49% reduced unplanned downtime linked to storage failures. At the same time, 63% said they were struggling to find or train staff who could manage AI-assisted storage systems effectively.

The Rise of AI-Driven Storage Roles

As in other areas of data infrastructure, AI isn’t just eliminating tasks—it’s giving rise to new job categories. We’re seeing roles emerge such as “Autonomous Storage Engineer,” “Storage Observability Analyst,” and “Data Placement Strategist.” These professionals sit at the intersection of storage, automation, and business continuity—ensuring the systems making decisions can be trusted, optimized, and governed.

Another growing field is that of FinOps-aligned storage planners: professionals who combine AI-powered cost forecasting tools with deep knowledge of storage architecture to ensure optimal usage across hybrid environments. As AI continues to drive real-time optimization, human oversight becomes more about accountability, governance, and systemic thinking.

But be aware: even these roles may evolve quickly as AI platforms get better at generalizing storage patterns across environments. The professionals who will endure are those who can pivot from command-line mastery to business-centric problem-solving—those who understand how data supports real-world outcomes.

Upskilling for the AI-Storage Future

Storage professionals looking to stay ahead must rethink their value proposition. The era of managing hardware arrays and manually tuning performance is giving way to an era of policy-driven, intent-based operations. To thrive in this new model, invest in:

AI and analytics literacy: Learn how AI is applied to performance optimization, fault prediction, and tiering. Understand the algorithms behind your storage system’s behavior.

Storage orchestration and APIs: Get comfortable with RESTful APIs, orchestration platforms, and scripting tools that define the modern storage environment—especially in hybrid or multicloud setups.

Cloud-native architecture: Master storage in containerized and serverless ecosystems. Learn how object storage, block storage, and file systems are being reimagined in cloud-first environments.

Cost optimization and FinOps: The line between storage and finance is blurring. Learn how to interpret AI-powered cost forecasts and help your organization optimize spend while maintaining performance.

Compliance and lifecycle governance: Privacy laws and retention policies don’t disappear with automation. Storage professionals who understand governance frameworks and how AI intersects with compliance will remain indispensable.

For enterprise leaders, now is the time to re-skill your storage teams. Encourage cross-training in cloud services, automation tools, and AI platforms. Those who make the leap from maintenance to modernization will help your business not only keep up—but lead.

AI Will Redefine Storage Jobs—But Not Eliminate Them

If there’s a unifying theme to the AI impact on storage careers, it’s this: the physical is being abstracted, and the manual is being automated. But human judgment still matters. AI can tell you what’s happening and what might happen—but only you can decide why it matters and what to prioritize.

The storage pros of tomorrow won’t just manage volumes—they’ll manage velocity, visibility, and value. That means stepping back from the drive bay and stepping into the command center.

Bottom line: AI will auto-tier the data—but it won’t auto-prioritize the mission. To future-proof your data storage career, become a strategist, a translator, and a steward of smart infrastructure. The storage systems may be intelligent—but they still need someone with wisdom.

The post What the AI Impact on Data Storage Jobs Looks Like Right Now appeared first on Best Enterprise Data Storage Software, Solutions, Vendors and Platforms.

Solutions Review’s Executive Editor Tim King highlights the overarching AI impact on data center jobs, to help keep you on-trend during this AI moment.

It’s no secret in 2025 that artificial intelligence (AI) is reshaping the data center landscape. From how data centers are designed and run to the skills required to operate them, AI is rewriting the playbook. What’s less obvious—but critically important—is how this transformation is affecting the human roles inside these massive physical and virtual infrastructures. Automation, intelligent monitoring, and predictive maintenance are reducing the need for hands-on labor in many traditional tasks, while simultaneously elevating demand for a new breed of hybrid-skilled professionals who can manage both machines and models.

To help you understand these changes and stay ahead of the curve, the Solutions Review editors have analyzed how AI is disrupting data center jobs, what current professionals can do to remain essential, and how organizations can restructure their workforce strategies to future-proof their operations.

Note: These insights were informed through web research using advanced scraping techniques and generative AI tools. Solutions Review editors use a unique multi-prompt approach to extract targeted knowledge and optimize content for relevance and utility.

AI Impact on Data Center Jobs: How Has AI Changed the Data Center Workforce?

AI is revolutionizing the way data centers operate, making them smarter, leaner, and more autonomous. What was once a labor-intensive domain—filled with cable pulling, rack stacking, temperature monitoring, and routine diagnostics—is now increasingly defined by software, robotics, and intelligent decision-making. The impact on jobs is profound: repetitive roles are declining, while demand is soaring for AI-savvy technicians, automation engineers, and infrastructure strategists.

Predictive Maintenance and Intelligent Monitoring

AI-powered systems can now detect anomalies in power consumption, thermal patterns, and hardware health long before they turn into failures. Tools like Schneider Electric’s EcoStruxure and NVIDIA’s AI Infrastructure Management (AIM) use machine learning to predict and prevent downtime, automatically schedule component replacements, and optimize load balancing.

This dramatically reduces the need for reactive troubleshooting—a long-standing pillar of data center technician roles. Instead of hunting for faults, human workers are increasingly responsible for validating AI decisions, configuring predictive algorithms, and interpreting real-time dashboards. The break/fix model is giving way to a supervise/optimize model.

Autonomous Infrastructure and Zero-Touch Provisioning

Provisioning new resources—whether physical servers or virtual instances—used to require manual setup, cable management, BIOS configuration, and software installation. Now, AI-enabled orchestration platforms can provision entire workloads with zero-touch, using policy-based triggers and intent-driven design.

This shift threatens the traditional entry point into data center work: the hardware generalist. As rack-and-stack roles decline, the value moves to those who can build the automation logic, maintain provisioning templates, and ensure compliance in software-defined infrastructure (SDI). Infrastructure as Code (IaC) isn’t just a DevOps skill anymore—it’s part of the new baseline for physical infrastructure management.

AI-Augmented Energy and Cooling Optimization

Power and cooling have always been among the biggest cost centers in data center operations. Today, AI is optimizing airflow, temperature, and energy use at granular levels. Google famously used DeepMind to reduce data center cooling bills by 40%—a proof point that has since spurred a wave of similar AI deployments across hyperscalers and colocation providers.

This means fewer technicians doing routine thermal audits and HVAC checks—and more roles focused on integrating AI with building management systems (BMS), analyzing energy telemetry, and setting AI governance guardrails. Sustainability mandates are also giving rise to green infrastructure roles that combine AI insight with environmental impact assessments.

Robotic Automation and Remote Hands

From autonomous inventory drones to robotic arms handling physical swaps, AI-powered robotics are reducing the need for humans on the floor. In edge environments and remote facilities, these tools are becoming essential for managing distributed data centers at scale without full-time onsite staff.

This accelerates the need for hybrid roles—those who can manage robotic workflows, interpret sensor data, and interface with centralized AI monitoring systems. Field service techs must evolve into remote systems managers, capable of guiding or auditing robotic processes rather than executing them manually.

A 2024 Uptime Institute report revealed that 51% of data center operators using AI-driven predictive maintenance tools reduced unplanned downtime by more than 30%, while 47% planned to reduce their hands-on operational staff within five years. Yet 69% reported an acute shortage of talent capable of managing AI-driven infrastructure—highlighting the urgent need for upskilling.

The Emergence of AI-Era Data Center Roles

New roles are materializing fast. We’re seeing titles like “AI Infrastructure Operations Engineer,” “Data Center Automation Lead,” and “Digital Twin Technician.” These positions blend knowledge of physical infrastructure with expertise in AI systems, simulation modeling, and real-time optimization. Some roles are even moving into the realm of AI training support—where infrastructure engineers assist in building or maintaining the data center environments AI models rely on.

At the enterprise level, expect a shift from siloed NOC (Network Operations Center) and facilities teams toward integrated, software-defined operations squads. These teams use digital twins, real-time monitoring, and AI-enabled alerts to ensure uptime, security, and cost efficiency across hybrid and multi-cloud environments.

But caution is warranted: many of these new roles are transitional. As AI platforms get smarter and more user-friendly, even highly technical roles will require increasing business context and cross-functional fluency. The real long-term differentiator will be systems thinking—understanding how physical and digital infrastructure co-evolve and how to design environments that are resilient, scalable, and sustainable.

Upskilling for the AI-Enabled Data Center

If your career is rooted in data center operations, now is the time to modernize your toolbox. The classic skills—power calculations, hardware swaps, rack layout design—are not obsolete, but they’re no longer enough on their own. Instead, focus on:

AI and automation fluency: Understand how AI is used in monitoring, predictive maintenance, and provisioning. Learn to manage AI-driven systems and interpret their recommendations.

Software-defined everything (SDx): Master SDN, SDS, and SDI concepts. The future is programmable infrastructure, and your ability to script, automate, and orchestrate will be critical.

Infrastructure observability and digital twins: Learn how to work with telemetry systems, visual dashboards, and modeling environments that simulate infrastructure performance at scale.

Sustainability and energy governance: With regulatory and ESG pressures rising, roles that intersect energy efficiency, carbon tracking, and AI-optimized operations will only grow more important.

Cross-domain communication: Data center operations now touch everything from cloud cost optimization to security posture management. Success will come to those who can connect the dots across disciplines.

For organizations, AI demands a rethinking of talent pipelines. The next generation of data center pros must be as comfortable writing scripts as they are swapping drives. Smart teams are blending facilities, IT, and DevOps skill sets to create adaptive “site reliability for infrastructure” teams.

AI Won’t Eliminate Data Center Jobs—But It’s Rewriting the Job Description

If there’s a central theme to the AI impact on data center work, it’s this: AI isn’t replacing people—it’s replacing repetitive effort. Human insight is still needed to design architectures, enforce policies, ensure sustainability, and connect infrastructure to business strategy. But the baseline skill set is shifting fast.

Over the next three to five years, legacy-only job roles will fade, and hybrid-skilled professionals will dominate. The ideal data center operator will be part technician, part software engineer, and part strategist. It’s a challenging transition—but also a huge opportunity for those willing to reinvent themselves.

Bottom line: AI will automate the routine, but not the resilient. If you want to future-proof your data center career, become the connective tissue between infrastructure, intelligence, and impact. The machines may run themselves—but they still need architects.

The post What the AI Impact on Data Center Jobs Looks Like Right Now appeared first on Best Enterprise Data Storage Software, Solutions, Vendors and Platforms.

Backblaze’s SVP Cloud Operations Chris Opat offers commentary on what enterprise leaders need to know about the hidden economics of exabyte storage. This article originally appeared in Insight Jam, an enterprise IT community that enables human conversation on AI.

Your company could be overpaying for storage—not because you bought the wrong drives or chose the wrong vendor, but because the true economics of enterprise storage remain largely hidden from view.

As someone who manages over 300,000 hard drives holding three exabytes of customer data, I will share some of the hidden economics of exabyte storage that I have uncovered.

Bigger Isn’t Necessarily Better

As a company’s storage needs grow, you might think that drive sizes would also need to grow. Although it might seem that a larger drive makes the most economic sense, this isn’t always the case. While we’ve recently welcomed 20TB drives to our data centers, we deliberately maintain fleets of smaller capacity drives for many workloads.

Hard drives can only perform a set number of input/output operations per second (IOPS). As the size of drives increases, the more these IOPS become a contentious resource. This creates what I call the “triangle of tension” between storage capacity, reading performance, and writing speed.

You can store more data on a 20TB drive, but you can only read and write as fast as that one drive allows. Meanwhile, five 4TB drives offer the same capacity with five times the potential IOPS through concurrency.

This IOPS limitation can quickly become the dominant economic factor for businesses with real-time access requirements, far outweighing the apparent cost savings of higher-density drives.

Rebuild Costs Beyond Hardware Replacement

When hard drives fail, the cost of replacing the drive can go far beyond just replacing the hardware. For larger drives, the rebuild process can take hours and even days, thus increasing costs that rarely are taken into account when initially planning costs.

Due to the time it takes to rebuild, this hidden cost presents as reduced productivity and customer satisfaction rather than simply a line item on your storage budget. In addition, longer rebuild times create an extended window of vulnerability to additional failures. If the storage system is already under heavy use, this only increases the risk of failure.

To best protect data and avoid loss, I recommend implementing the 3-2-1 backup strategy. In this strategy, three copies of the data are kept to best protect against any sort of failures. Two of the copies are located on different types of media and the last copy is kept at an off-site location. This strategy best prepares enterprises for any drive failure risk, thus allowing businesses to save money in the event that one of the drives does fail.

How Egress Costs Are the Silent Killer

The most overlooked aspect of enterprise storage economics is what happens when you need to move your data. According to a Gartner analysis, egress costs can silently consume 10-15% of cloud bills, but I’ve even seen instances where it reaches 40%. For a media company with 22 million customers, simply changing their storage strategy saved $800,000 annually in egress fees alone.

These mobility costs don’t appear in your initial capacity planning but can quickly become one of your most significant operational expenses. The real value of your data isn’t just in storing it but in using it when and where you need it. Many enterprises optimize for the former while completely neglecting the latter.

For organizations building multi-cloud strategies, this often-overlooked economic factor can render an otherwise sound architecture financially unsustainable at scale. What appears as a minor line item in your initial planning becomes a significant budget constraint as your data volumes grow.

Navigating the Evolving Global Regulations

As data sovereignty requirements have evolved to a global mandate, it is vital for enterprises to stay on top of these changes. The United Nations Trade and Development reported that 71% of countries now have data protection legislation.

These regulatory requirements create a hidden economic burden that’s rarely factored into storage strategy. The penalties for non-compliance can be existential—Meta’s $1.3 billion fine for EU privacy violations illustrates the scale of risk. For enterprise leaders, this requires incorporating geographic dispersion costs into your storage economics from day one.

A Guidebook for Enterprise Storage Leaders: 3 Steps You Can Take Today

As a leader for an enterprise with data storage needs, I’ve shared a few changes you can make today to transform your storage economics.

• Profile before purchasing: Extensively document your actual workload patterns—IOPS requirements, read/write ratios, and access frequencies—before making major storage investments.

• Calculate your true data mobility costs: Most enterprises dramatically underestimate how often they’ll need to move data between systems. Map your data workflows end-to-end and identify potential movement patterns before selecting storage architectures or vendors.

• Build for geographic flexibility: Classify your data as low, medium, or high sensitivity, then map these classifications to geographic and architectural requirements. This approach not only prepares you for current regulations but also creates the flexibility to adapt as requirements inevitably evolve.

The enterprise storage landscape has fundamentally changed. Today’s enterprises need infrastructure that can accommodate workloads that didn’t exist five years ago while complying with regulations that didn’t exist three years ago.

Storage is no longer just an infrastructure cost—it’s a strategic asset that can either enable or constrain your organization’s future. The most successful enterprises are those that look beyond the spec sheet economics to understand the hidden factors that actually determine their total cost of ownership.

Don’t wait until you’re trapped in a poor architecture to reassess your storage economics—the time for action is now.

The post What Enterprise Leaders Need to Know About the Hidden Economics of Exabyte Storage appeared first on Best Enterprise Data Storage Software, Solutions, Vendors and Platforms.

As expected, AI is continuing  to dominate discussions in the storage industry in 2025. However, how we deal with the massive explosion in data storage needs is a much more expansive conversation that revolves around the disaggregation of storage.

The ability to scale and manage storage resources separately from memory and compute resources has been a key enabling technology of today’s AI-scale data centers. As workloads grow more powerful, data continues to explode and everyone is under pressure to do more with less, storage disaggregation has become important for both enterprises and hyperscalers. Storage disaggregation projects will grow in frequency and in importance as AI continues to push legacy storage to its limits.

 Here are five trends that are helping to push storage disaggregation in 2025:

1. Everyone is under pressure to increase data center utilization

Getting the most from your IT investments will continue to be a priority. Enormous resources are being spent to develop new artificial intelligence (AI) projects with the aim of driving business agility and creating operational efficiencies. Building an AI-scale data center – either in house or in the cloud – is hard. Millions of transactions are being run in a small window, putting intense pressure on infrastructure. When you are building a data center with 8,000 GPUs, server failure is a matter of when, not if – and downtime is expensive. The greater the number of GPUs, the greater the likelihood that a failure will occur. Starting the workflow over after a failure is time and cost prohibitive. Utilizing shared, disaggregated storage accommodates a series or multitude of checkpoints to minimize the impact of failure and avoid starting over.

2. Compute power is at a premium

AI applications are more powerful than ever and require more compute and memory resources than legacy applications. This is especially true for large language models (LLMs) that rely on lightning-fast latency to keep up with real-time interactions and decision making. These growing demands are reshaping how we think about server architecture. To free up prime real estate and optimize server performance and efficiency, storage is increasingly being separated into dedicated storage platforms. This allows components to scale independently to ensure all resources are utilized more efficiently without comprise while also helping to address challenges related to power, cooling, and networking.

3. Data capacity continues to go up… and up… and up

AI is only as good as the data you feed into it. Modern applications are huge consumers and creators of data storage. In fact, from training models to content outputs, there’s a huge need for more information across the entire AI data cycle. But not all this data needs to be accessed all the time. While some data may need to be made readily available instantly, the bulk of it can sit in large data lakes for more long-term purposes. Disaggregating storage from memory and compute resources allows organizations to meet varying storage requirements in the most efficient manner possible.

4. Keen to go green

Morgan Stanley estimates that data centers will produce 2.5 billion tons of carbon through 2030, which will make it hard for many advanced countries to meet their climate goals. The resulting sustainable data center initiatives will continue to push storage disaggregation projects in 2025. The ability to scale storage independently of memory and compute ensures that AI applications have fast access to the information they need in the moment without sacrificing lower-priority data or forcing organizations to over-provision resources across the entire data environment.

5. The electrical grid is under immense stress

Growing data centers are also straining the electrical grid. According to Bloomberg, data center electricity use will surge four to ten times by 2030 – much of it led by energy-hungry AI applications. Several of the largest hyperscalers are considering building their own nuclear power plants for their data centers as a way to keep up with the expected energy demand. Storage disaggregation, and its ability to improve data center utilization –  is a valuable complement.

Storage Disaggregation is the Thoughtful Alternative

There’s no doubt that storage disaggregation should dominate the water cooler talk in 2025. Too many trends – from exploding data storage needs to the development of more climate friendly data centers – are pushing the industry in that direction. Scaling storage separately from memory and compute lets data centers scale more efficiently.

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EchoStor Technologies’ Daniel Clydesdale-Cotter offers insights on data center evolution and the rise of sustainable computing and liquid cooling. This article originally appeared on Solutions Review’s Insight Jam, an enterprise IT community enabling the human conversation on AI.

The modern enterprise data center is undergoing a dramatic transformation, driven not just by the demands of artificial intelligence and high-performance computing but by a pressing need to optimize costs and improve environmental sustainability. As organizations grapple with compute demands within existing facilities, traditional air-cooled systems are proving insufficient for their needs. This challenge is particularly acute as organizations integrate more GPU-intensive workloads and high-density computing solutions into their environments.

The emergence of new open rack v3 specifications, coupled with innovations in liquid cooling technology, is revolutionizing how organizations approach data center design. This evolution isn’t merely about being “green” – it’s about enabling organizations to maximize their computing capabilities within existing infrastructure while managing costs effectively. The shift from traditional air-cooled layouts to liquid cooling represents a strategic power swap: less power for fans and air cooling, more power for GPUs and CPUs. This approach allows organizations to host increasingly powerful machines that would otherwise overwhelm traditional cooling systems, all while maintaining or even reducing their overall power footprint.

A Multi-Faceted Approach to Efficiency

Organizations are taking a comprehensive approach to data center efficiency, examining multiple factors:

Processor Architecture Optimization

Companies are conducting detailed comparisons between processor options, evaluating core density and wattage efficiencies to maximize processing power while minimizing energy consumption. The focus has shifted from raw performance metrics to performance-per-watt calculations, leading to more nuanced decisions about hardware deployment.

Advanced Monitoring Systems

Implementation of sophisticated DCIM software and sensor systems allows organizations to track and optimize power usage in real-time, identifying areas of inefficiency and opportunity. These systems provide granular insights into power usage effectiveness (PUE) and help organizations make data-driven decisions about infrastructure improvements.

Storage Density Improvements

The industry is seeing a significant shift towards high-density storage solutions, with QLC SSDs approaching 60 terabyte capacities. This enables organizations to dramatically increase storage density while reducing power consumption compared to traditional spinning disk arrays. The move away from hybrid storage systems to all-flash arrays represents another step toward improved power efficiency without sacrificing performance.

The AI and GPU Computing Challenge

The impact of AI and GPU computing adds another layer of complexity to this evolution. While GPU-intensive workloads can significantly increase power consumption, optimized applications can improve cost per operation, creating a dynamic balance between power consumption and computational efficiency. Organizations are finding that the parallel processing capabilities of GPUs can actually lead to better overall energy efficiency when applications are properly optimized for these architectures.

For many organizations, these changes aren’t just about environmental stewardship – they’re about practical necessity. Insurance companies, utilities, and other large enterprises face a choice: build new data centers at enormous expense or optimize existing facilities. The combination of liquid cooling, modern rack design, and efficient hardware choices is making the latter option increasingly viable. This approach allows organizations to extend the life of their existing data centers while simultaneously preparing for future computational demands.

The new open rack specifications are crucial in this evolution, providing a standardized approach to implementing modern cooling technologies. This is evidenced by major server manufacturers moving away from proprietary blade chassis designs in favor of open rack architectures, particularly for new high-performance computing deployments. The industry’s largest GPU compute installations have widely adopted these specifications, demonstrating their effectiveness for modern computing demands.

 This convergence of business necessity and environmental sustainability is accelerating, pushing organizations to build more resilient and cost-effective infrastructure. Early adopters of these technologies are already seeing significant improvements in their ability to handle high-density computing workloads without requiring facility expansion.

The transformation of data center design represents more than just a technical evolution – it’s a fundamental shift in how organizations think about computing infrastructure. By embracing these changes, companies can meet their immediate computing needs while positioning themselves for sustainable growth in an increasingly compute-intensive future. The successful data center of tomorrow will be one that efficiently balances performance, power consumption, and cooling capabilities while maintaining the flexibility to adapt to emerging technologies and computing demands.

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Solutions Review’s listing of the best block and file storage solutions is an annual mashup of products that best represent current market conditions, according to the crowd. Our editors selected the best block and file storage solutions based on each solution’s Authority Score; a meta-analysis of real user sentiment through the web’s most trusted business software review sites and our own proprietary five-point inclusion criteria.

The editors at Solutions Review have developed this resource to assist buyers in search of the best block and file storage solutions to fit the needs of their organization. Choosing the right vendor and solution can be a complicated process — one that requires in-depth research and often comes down to more than just the solution and its technical capabilities.

To make your search a little easier, we’ve profiled the best block and file storage solutions all in one place. We’ve also included platform and product line names and introductory software tutorials straight from the source so you can see each solution in action.

Note: The best block and file storage solutions are listed in alphabetical order.

The Best Block and File Storage Solutions

AWS

Platform: Elastic Block Store, Elastic File System

Description: The product line includes Amazon Elastic Block Store (EBS) for block storage, which offers persistent storage volumes for use with Amazon EC2 instances in the cloud. For file storage, AWS presents Amazon Elastic File System (EFS), a scalable file storage system for use with AWS Cloud services and on-premises resources. Both solutions are designed to support a wide range of performance-intensive and latency-sensitive use cases, such as database applications, enterprise applications, and big data analytics.

Cohesity

Platform: SmartFiles

Description: Cohesity offers innovative data management solutions that simplify the way enterprises handle their data across multiple locations, including data centers, edge environments, and the cloud. Their product line includes Cohesity SmartFiles, a software-defined, data-centric, multiprotocol file and object solution that consolidates files and objects in a single platform, optimizing efficiency and reducing complexity. SmartFiles is designed to support various enterprise workloads and applications, offering features like deduplication, compression, and file locking to enhance performance and security for block and file storage needs.

Dell EMC

Platform: Dell EMC Unity XT, Dell EMC PowerStore

Description: Dell EMC provides a diverse range of block and file storage solutions tailored to meet the needs of modern data centers. Their offerings include Dell EMC Unity XT for midrange data storage, offering both file and block storage capabilities, and Dell EMC PowerStore, designed to support any workload with a data-centric, intelligent, and adaptable infrastructure. These solutions enhance performance, efficiency, and scalability, making them suitable for a variety of applications from business-critical workloads to virtualized environments. Dell EMC’s storage solutions are recognized for their reliability, innovation, and comprehensive data services.

Hitachi

Platform: Hitachi Content Platform

Description: Hitachi Vantara offers robust storage solutions through its Hitachi Content Platform (HCP) which seamlessly integrates block and file storage. HCP is designed to handle large-scale, complex data environments efficiently, making it suitable for enterprise-level data management requirements. The platform supports high levels of scalability and reliability, providing secure, hybrid cloud storage options. Hitachi’s storage solutions are particularly noted for their advanced data governance, regulatory compliance, and intelligent data management capabilities, enabling businesses to optimize data mobility and protection across diverse IT infrastructures.

HPE

Platform: Nimble Storage, 3PAR StoreServ

Description: Hewlett Packard Enterprise (HPE) offers advanced block and file storage solutions through its Nimble Storage and 3PAR StoreServ product lines. HPE Nimble Storage provides flash-optimized arrays that offer predictive analytics to automatically identify and resolve issues, enhancing data availability and performance. HPE 3PAR StoreServ offers a highly scalable and efficient storage solution that provides rapid provisioning and multi-tenant capabilities, ideal for handling diverse and dynamic workloads across all file and block storage environments. These systems are designed to support both large enterprises and smaller organizations with complex storage needs.

IBM

Platform: FlashSystem, Spectrum Scale

Description: IBM provides comprehensive block and file storage solutions tailored for high performance and reliability across various industries. IBM’s storage portfolio includes IBM FlashSystem, which offers end-to-end NVMe-powered flash storage for enhanced data speed and efficiency, suitable for both block and file storage requirements. Additionally, IBM Spectrum Scale provides high-performance, scalable file storage capable of handling large data volumes across different environments, including cloud. These solutions are integrated with IBM’s enterprise-level data management software, ensuring robust data protection, disaster recovery, and operational flexibility.

Infinidat

Platform: InfiniBox

Description: Infinidat offers high-performance data storage solutions designed to meet the needs of large enterprises and data-intensive applications. Their flagship product, InfiniBox, provides petabyte-scale storage capacity and delivers high throughput and low latency for both block and file storage. InfiniBox supports multiple petabytes in a single rack, ensuring efficient data management and scalability. This platform is well-suited for organizations requiring robust disaster recovery, high availability, and seamless data migration capabilities across diverse IT environments.

Microsoft

Platform: Azure

Description: Microsoft Azure provides flexible and scalable storage solutions tailored for a variety of enterprise needs. Azure offers Azure Blob Storage for unstructured data, which can be used for block storage scenarios, and Azure Files for managed file storage that supports SMB and NFS protocols, ideal for migration of on-premises file shares to the cloud. Azure’s storage solutions are integrated within a comprehensive cloud ecosystem, supporting hybrid capabilities, advanced data protection, and seamless global deployment. These features make Azure suitable for businesses seeking robust, enterprise-grade storage solutions that support both traditional and cloud-native applications.

NetApp

Platform: ONTAP

Description: NetApp offers versatile and innovative storage solutions, notably through its NetApp ONTAP data management software, which provides unified storage for both block and file shares. This integration allows for scalable and flexible storage systems that support cloud integration and virtualization effectively. NetApp’s AFF (All Flash FAS) and FAS (Fabric-Attached Storage) systems deliver high performance and robust data protection features, ideal for enterprises that require efficient data management across hybrid cloud environments. These systems are designed to enhance data control, accessibility, and security, making them suitable for complex enterprise storage requirements.

Pure Storage

Platform: FlashArray, FlashBlade

Description: Pure Storage provides cutting-edge block and file storage solutions with its FlashArray and FlashBlade product lines. FlashArray delivers all-flash performance for block storage with a strong focus on simplicity and reliability, suitable for critical applications and databases. FlashBlade, on the other hand, is an all-flash storage solution optimized for file and object storage, designed to handle modern data analytics and artificial intelligence workloads with ease. Both systems offer significant advantages in terms of speed, scalability, and efficiency, supporting a seamless data experience across multiple environments.

Qumulo

Platform: Qumulo

Description: Qumulo offers a flexible and scalable file storage solution designed to manage billions of files with real-time visibility and control over data at a massive scale. Their platform supports both file and block storage needs and is engineered to run in the cloud, on-premises, or in hybrid environments. Qumulo’s file services are built to handle the intensive demands of data-driven industries such as media and entertainment, healthcare, and life sciences, providing users with continuous replication and snapshots for data protection and business continuity.

Scality

Platform: RING

Description: Scality is known for its RING software-defined storage that excels in handling large-scale data storage needs, supporting both file and object storage. This platform is engineered to provide durability, flexibility, and performance, which are crucial for data-intensive applications like media streaming, IoT, and cloud services. Scality’s storage solutions offer petabyte-level scalability and are designed to integrate seamlessly with existing applications and hardware, providing robust disaster recovery, native replication, and high availability features to ensure data security and accessibility across distributed environments.

SUSE

Platform: Enterprise Storage

Description: SUSE Enterprise Storage, powered by Ceph technology, is an open-source, software-defined storage solution designed to scale without limits. It supports block, file, and object storage, making it extremely versatile for handling data-intensive environments such as cloud computing, data analytics, and archival storage. SUSE’s platform is particularly noted for its cost-efficiency and scalability, allowing enterprises to manage exponential data growth by using commodity hardware and integrating seamlessly with existing software ecosystems. This makes it ideal for businesses looking to optimize their storage infrastructure for flexibility and cost-effectiveness.

WEKA

Platform: WEKA

Description: WEKA offers a data platform that optimizes storage for high-performance environments, supporting both file and block storage systems. Designed to excel in handling large-scale data sets, WEKA’s storage solutions are ideal for applications that require high throughput and low latency, such as AI, machine learning, and big data analytics. The system is engineered to work seamlessly in hybrid and multi-cloud environments, offering scalable data orchestration and management to maximize operational efficiency and data accessibility.

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Solutions Review’s listing of the best Object Storage solutions and Distributed File Systems is an annual mashup of products that best represent current market conditions, according to the crowd. Our editors selected the best Object Storage solutions and Distributed File Systems based on each solution’s Authority Score, a meta-analysis of real user sentiment through the web’s most trusted business software review sites, and our own proprietary five-point inclusion criteria.

Distributed file system storage utilizes a single parallel file system in order to cluster multiple storage nodes together. This system presents a single namespace and a storage pool to deliver high-bandwidth data access for multiple hosts in parallel. Data is then distributed over nodes in the cluster to provide data availability and resilience, and to scale capacity and throughput in a linear manner. Conversely, object storage references systems and software that store data in structures called “objects.”  These tools serve users data through RESTful HTTP APIs, which have, in effect, become the standard for accessing object storage.

Though they are separate methods of storage, the distributed file systems and object storage markets are steadily merging. Distributed file systems and object storage platforms are software and hardware-based on distributed design. These solutions support object and/or scale-out file technology as a means to address business needs resulting from unstructured data growth. The market for these platforms is based on distributed computing architecture where there is no single point of failure or contention across the system. To put a finer point on it, the solutions must have a fully distributed architecture where data and metadata are replicated, distributed, or erasure-coded over a network across multiple nodes in a cluster.

Selecting the Object Storage solutions and Distributed File Systems to use can be a daunting task, and we’re here to help. That’s why our editors have compiled this list of the Object Storage solutions and Distributed File Systems to consider if you’re looking for a new solution.

Check out our online data storage best practices section for even more guides, advice, and how-to content.

The Best Object Storage Solutions and Distributed File Systems

Cloudian is an independent provider of object storage systems, offering S3 compatibility along with a partnership ecosystem. The vendor’s flagship solution, HyperStore, is a scale-out object platform designed for high-throughput object storage workloads. It provides scalability, flexibility, and economics within the data center. HyperStore also delivers an add-on file gateway to manage file workloads. Additionally, Cloudian’s data fabric architecture allows enterprises to store, find, and protect object and file data across sites. These processes can take place both on-prem and in public clouds within a single, unified platform.

The Best Object Storage Solutions and Distributed File Systems

DataCore Software provides object-based technology for accessing, storing, and distributing unstructured or file-based data. Its flagship product, DataCore Swarm, delivers private cloud storage that enables users to deploy storage clusters without being locked into proprietary hardware. The provider delivers a scalable SDS solution with universal support for traditional file data, object storage APIs, and public cloud data. DataCore’s storage platform is offered in private, public, and hybrid cloud environments. Users also have the ability to scale on–premise with any mix of x86 hardware.

DataDirect Networks, also known as DDN, is a provider of scalable storage and processing solutions, as well as professional services. Organizations have the ability to use a range of DDN storage platforms to capture, store, process, analyze, collaborate, and distribute data, information, and content at a large scale. DDN’s solution, EXAScaler, is a distributed file system that runs on-prem and in the cloud.  EXAScaler is aimed at large-scale, high-throughput file workloads and WOS (DDN’s secondary platform) is positioned as a long-term repository and as a tier for EXAScaler. The vendor provides services to financial services firms, healthcare organizations, energy companies, government facilities, and cloud service providers.

Hitachi Vantara assists enterprises with storing, enriching, activating, and monetizing their data. The provider offers four solutions under the umbrella of object storage, namely, Hitachi Content Platform (HCP), HCP Anywhere, Hitachi Data Ingestor (HDI), and Hitachi Content Intelligence. Each provides object storage, file synchronization, sharing, end-user data protection; a cloud file gateway; and search and analytic insights. The HCP portfolio is a component of broader strategic initiatives for data management and analytics and offers an ecosystem that spans a range of verticals and solution domains. The vendor is a wholly–owned subsidiary of Hitachi, Ltd., and also offers backup and disaster recovery solutions.

Huawei Technologies is a telecom solutions provider that offers infrastructure application software and devices with wireline, wireless, and IP technologies. Regarding storage, Huawei provides all-flash storage, hybrid flash storage, cloud storage, Hyperconverged Infrastructure (HCI), and data management. The vendor offers OceanStor 9000 V5 as a file systems platform and OceanStor 100D (formerly FusionStorage) as a block and object storage solution. OceanStor 100D is a good fit for private cloud, archiving, and content distribution, whereas OceanStor 9000 is typically utilized for video surveillance, rich-media distribution, and commercial high-performance computing (HPC). In the coming years, Huawei will position OceanStor 100D as its flagship solution for all unstructured data needs.

IBM offers various technology and consulting services, including predictive analytics and software development. The provider offers a range of storage options, including flash storage, Software-Defined Storage (SDS), data protection software, hybrid storage arrays, Storage Area Networks (SAN), and tape storage. IBM Spectrum Scale is the vendor’s file system product, which runs on-prem and in public clouds. Its object storage offering, Cloud Object Storage (COS), also runs on-prem and in the IBM Cloud. Spectrum Scale is recommended for commercial HPC and analytics, while COS is a better fit for archive and private cloud storage. Spectrum Scale offers support for OpenShift containers and IBM COS recently added higher-performance appliances, as well as certified new third-party servers.

Inspur provides big data services, cloud data centers, cloud services, and smart enterprises. The provider’s Inspur AS13000G5 series platform delivers a unified software solution for both file and object storage. Inspur provides three AS13000G5 products for petabyte-scale applications for high-definition video, high performance, high reliability, and cloud-based deployments. The vendor’s storage platform is a good fit for commercial HPC, backup and archiving, analytics, and hybrid cloud. While Inspur provides many services, its storage business is the second-largest within the company, after its server business. 

While NetApp predominantly offers on-prem storage infrastructure, the provider also specializes in hybrid cloud data services that facilitate the management of applications and data across cloud and on-prem environments. The vendor’s object storage solution, StorageGRID, is a platform available as software and hardware appliances that can run in the public cloud and on-prem. NetApp also supports tiering of data from on-prem StorageGRID to the public cloud services, AWS and Azure. Additionally, the provider offers information life cycle management (ILM) at ingest, a per-node capacity increase to 2.8PB and 1 billion objects, active-active high-availability load-balancing software, and multi-factor authentication.

Pure Storage is an all-flash enterprise storage provider that enables the broad deployment of flash in data centers. FlashBlade is the provider’s purpose-built unified file and object product. Pure Storage provides a scale-out distributed file system that can handle tens of billions of files and objects for maximum throughput and parallelism by adding blades to scale capacity and performance. Additionally, the vendor offers support for scaling to 150 blades, as well as replication and file system rollback for its Purity//FB software. Pure Storage also enables users to adopt next-generation technologies, including artificial intelligence and machine learning, to maximize the value of their data. In 2020, Pure Storage acquired Portworx for $370 million.

Qumulo is an enterprise data storage provider whose solutions are available on Qumulo storage servers, on hardware from companies such as Dell and HPE, and natively on AWS in the public cloud.  Qumulo File System is a software-defined solution that runs on-prem and in the public cloud. The platform is designed for large-scale, high-throughput file workloads with capacity management and performance analytics. Qumulo also provides a mixed hardware node and enhanced SMBv3 support, as well as the capability to copy files from the Qumulo cluster into AWS S3. Additionally, the provider offers software that is available on AWS Marketplace, third-party hardware, and standard hardware that Qumulo sells directly to customers.

Red Hat is a software provider that offers open-source software products to the enterprise community. Red Hat provides Red Hat Ceph Storage and Gluster Storage. Ceph Storage supports block, object, and file storage access, whereas Gluster Storage is a file product. Ceph Storage also supports the underlying storage for Red Hat OpenShift Container Storage (OCS) and Red Hat Hyperconverged Infrastructure for Cloud. Ceph is recommended for content delivery and hybrid cloud, while Gluster is suited for backup, archiving, home directories, and rich media. The provider offers a multi-cloud gateway, automation, back-end storage, and installation utility.

Scality is a venture-backed software provider that delivers large-scale storage management and infrastructure solutions. The vendor’s flagship solution, RING, delivers integrated file and object storage for high-capacity unstructured data workloads, runs as software on commodity hardware, and makes x86 servers scale to hundreds of petabytes and billions of objects. Additionally, RING has an end-to-end parallel architecture and a patented object storage core that increases availability and durability. The platform integrates with applications through standard storage protocols such as NFS, S3, OpenStack Swift, and Cinder. Scality differentiates itself from other vendors through its integrated file and object architecture.

The post The 12 Best Object Storage Solutions and Distributed File Systems in 2025 appeared first on Best Enterprise Data Storage Software, Solutions, Vendors and Platforms.

Solutions Review’s listing of the best enterprise data storage solutions is an annual sneak peek of the solution providers included in our Buyer’s Guide and Solutions Directory. Information was gathered via online materials and reports, conversations with vendor representatives, and examinations of product demonstrations and free trials.

Enterprise data storage is a centralized repository for information, which commonly offers data management, protection, and sharing functions. Because enterprises handle massive amounts of business-critical data, storage systems that are highly scalable, offer unlimited connectivity, and support multiple platforms would benefit them the most. There are multiple approaches to data storage to choose from, including Storage Area Networks (SANs), Network-Attached Storage (NAS), Direct-Attached Storage (DAS), and cloud storage. The importance of data storage is underlined by the exponential generation of new data and the proliferation of Internet of Things (IoT) devices.

Newer approaches and technologies that are currently disrupting the market include hyperconverged storage and flash technologies such as Non-Volatile Memory Express (NVMe). This trend stems from the increased amount of horizontal scalability and reduced latency these methods offer. Storage for containers is also becoming a stronger selling point, as well as enterprise storage based on composable and disaggregated infrastructure concepts, which combine individual resources at the hardware level and then assemble them at the software level by using APIs.  

Selecting the best enterprise data storage solutions to work with can be a daunting task, and we’re here to help. That’s why our editors have compiled this list of the best enterprise data storage solutions to consider if you’re looking for a new solution.

Check out our online data storage best practices section for even more guides, advice, and how-to content.

The Best Enterprise Data Storage Solutions

Amazon Web Services (AWS) offers a range of IT infrastructure services to enterprises. In addition to storage, the provider’s solutions and products include cloud computing, compute, networking, content delivery, databases, analytics, application services, backup, and archive.  AWS provides a variety of cloud storage solutions, such as Amazon Elastic Block Store (Amazon EBS), Amazon Simple Storage Service (Amazon S3), and AWS Backup, among others. Users are enabled to select from object, block, and file storage services as well as cloud data migration options when selecting their solution. The vendor’s various platforms also support both application and archival compliance requirements.

Caringo is a provider of object-based technology for accessing, storing, and distributing unstructured or file-based data. Its flagship product, Caringo Swarm, provides private cloud storage that enables users to deploy storage clusters without being locked into proprietary hardware. In addition to data storage, the provider offers enterprise IT, medical, high-performance computing, and media and entertainment solutions. Caringo’s storage platform is offered in private, public, and hybrid cloud environments. Users also have the ability to scale on–premise with any mix of x86 hardware.

Cloudian is an independent provider of object storage systems, offering S3 compatibility along with a partnership ecosystem. The vendor’s flagship solution, HyperStore, provides scalability, flexibility, and economics within the data center. Additionally, Cloudian’s data fabric architecture allows enterprises to store, find, and protect object and file data across sites. These processes can take place both on-prem and in public clouds within a single, unified platform. In 2020, Cloudian HyperStore was recognized as a 2020 Gartner Peer Insights Customers’ Choice for Distributed File Systems and Object Storage.

Cohesity consolidates secondary storage silos onto a hyperconverged, web-scale data platform that supports both public and private clouds. The vendor’s storage solution enables users to streamline their backup and data protection and then converge file and object services, test/dev instance, and analytic functions to provide a global data store. Cohesity delivers a single platform, a single GUI, and an app ecosystem, as well as machine learning capabilities. The provider offers two hyperconverged platforms, C3000 and C4000, as well as its distributed file system solution, Cohesity SpanFS. In 2020, Cohesity raised $250 million in Series E funding. Additionally, it was named a ‘Leader” in the GigaOm Report on Unstructured Data Management Solutions.

DataDirect Networks (DDN) is a provider of scalable storage and processing solutions, as well as professional services.  Organizations have the ability to use a range of DDN storage platforms to capture, store, process, analyze, collaborate, and distribute data, information, and content at a large scale. The solution is offered in two appliance options and is also available as a software-only distribution. The vendor provides services to financial services firms, healthcare organizations, energy companies, government facilities, and cloud service providers.

Dell EMC enables digital transformation through hybrid cloud and big data solutions built on a data center infrastructure that brings together converged infrastructure, servers, storage, and cybersecurity technologies. The provider’s featured solution, Dell EMC Unity XT, offers multi-cloud enablement and an NVMe-ready design. Users are enabled to support virtualized applications, deploy unified storage, and address Remote-Office-Branch-Office requirements. The platform’s Unisphere management GUI also allows users to easily configure and manage storage. The vendor also offers file and object storage solutions. Dell EMC also recently released its PowerScale solution for unstructured data.

Fujitsu is a Japanese information and communication technology company that offers a range of technology products, solutions, and services. These services and solutions include consulting, systems integration, managed services, outsourcing and cloud services for infrastructure, platforms and applications, data center and field services, and server, storage software, and mobile technologies. Fujitsu provides all-flash and hybrid storage, hyper-scale storage, storage management software, and storage for backup and archive. 

Hedvig, a Commvault Venture, delivers enterprise storage for environments running at any scale. The provider’s platform is a software-defined storage solution with distributed systems DNA, unrestricted by existing architectures that are unable to keep pace with scale-out applications. Additionally, Hedvig accelerates data to value by collapsing disparate storage systems into a single platform, thereby creating a virtualized storage pool that easily provisions storage and runs in both public and private clouds.

Hitachi Vantara assists enterprises with storing, enriching, activating, and monetizing their data. The provider offers four solutions under the umbrella of object storage, namely, Hitachi Content Platform (HCP), HCP Anywhere, Hitachi Data Ingestor (HDI), and Hitachi Content Intelligence. Each provides object storage, file synchronization, sharing, end-user data protection; a cloud file gateway; and search and analytic insights. The vendor is a wholly–owned subsidiary of Hitachi, Ltd., and also offers backup and disaster recovery solutions.

HPE SimpliVity provides hyperconverged storage by converging the entire IT stack in each node, consolidation up to ten devices and apps in a building block for virtualized workloads. Before HPE acquired the company, SimpliVity delivered hyperconverged infrastructure on a range of industry-standard x86 platforms. Now, HPE SimpliVity provides its software-defined solutions that are built and supported by HPE. The vendor offers two platforms, HPE SimpliVity 380 and HPE SimpliVity 2600, which can both be integrated with the intelligent networking fabric, HPE Composable Fabric.

Huawei Technologies is a telecom solutions provider that offers infrastructure application software and devices with wireline, wireless, and IP technologies. The vendor has three divisions in the United States: enterprise (IP networking and router, wireless, storage, and data center security), carrier, and consumer devices (smartphones and tablets). Regarding storage, Huawei offers all-flash storage, hybrid flash storage, cloud storage, Hyperconverged Infrastructure (HCI), and data management. Its HCI platform, FusionCube for Cloud enables resource-on-demand provisioning and linear expansion.

IBM offers a wide range of technology and consulting services, including predictive analytics and software development. The provider offers a range of storage options, including flash storage, Software-Defined Storage (SDS), data protection software, hybrid storage arrays, Storage Area Networks (SAN), and tape storage. Through these products, IBM’s solutions support hybrid cloud storage, converged infrastructure, and virtual infrastructure. Additionally, the platforms allow for storage for blockchain, artificial intelligence, private cloud, and SAP. 

Infinidat helps enterprises and service providers empower their data-driven competitive advantage at scale. The company offers data storage software designed to store and protect petabytes of data. The provider specializes in storage, big data, cloud, NAS, SAN, and object storage. Infinidat’s primary storage portfolio is made up of InfiniBox, which offers high-capacity, performance capabilities and resilient storage architecture.

Inspur provides big data services, cloud data centers, cloud services, and smart enterprises. The provider offers Active Storage (AS) and the infrastructure SDS (AS13000) platform. Inspur AS13000 is delivered as a hardware appliance, but a software-only solution is also available for strategic customers and partners. While Inspur provides many services, its storage business is the second largest within the company, after its server business. The majority of Inspur’s storage dealings occur in China, with the government and transportation/logistics industry accounting for more than half of its revenue.

NetApp is a storage, cloud computing, information technology, and data management solution provider. In addition to predominantly offering on-prem storage infrastructure, the provider also specializes in hybrid cloud data services that facilitate the management of applications and data across cloud and on-prem environments in order to accelerate digital transformation. The vendor’s solution, StorageGRID, is an object storage platform whose primary access method is the Amazon S3 API. The tool offers hybrid cloud workflow and adheres to SEC and FINRA regulations.

Nutanix provides cloud software, compute and storage infrastructure, and hyperconverged infrastructure solutions for implementing enterprise virtualization without complex and expensive network storage, whether it is SAN or NAS. Nutanix Complete Cluster’s converged compute and storage architecture can scale to manage petabytes of data while running thousands of virtual machines.  Nutanix’s storage solution, Nutanix Acropolis, offers built-in AHV virtualization, networking services, platform services, and enterprise storage capabilities such as data protection and disaster recovery features. The provider recently raised $750 million from Bain Capital Private Equity.

Pure Storage is an all-flash enterprise storage provider that enables broad deployment of flash in data centers. Its technologies enable Software as a Service (SaaS) organizations, cloud service providers, and enterprise and public sector users to deliver secure data to power their DevOps and modern analytics environments in a multi-cloud environment. The vendor’s platforms accelerate random I/O-intensive applications such as server virtualization, desktop virtualization (VDI), database (OLTP, rich analytics/OLAP, SQL, and NoSQL), and cloud computing. Pure Storage also enables users to adopt next-generation technologies, including artificial intelligence and machine learning, to maximize the value of their data. In 2020, Pure Storage acquired Portworx for $370 million.

Qumulo is an enterprise data storage startup whose solutions are available on Qumulo storage servers, on hardware from companies such as Dell and HPE, and natively on AWS in the public cloud.  The provider was formed by professionals from Isilon Systems, Adobe, and Wily Technology. The vendor offers Qumulo File Fabric (QF2), a scale-out NAS tool that runs on-prem and in the public cloud, as well as preintegrated Qumulo Core appliances. Additionally, the provider offers software that is available on AWS Marketplace, third-party hardware, and standard hardware that Qumulo sells directly to customers.

Rackspace provides hybrid cloud-based services, Infrastructure as a Service (IaaS), and web hosting. The vendor is primarily a web hosting and managed service provider offering OpenStack-based public cloud services, but it has shifted its strategy to being a managed service provider across a range of public clouds, rather than focusing on its own native cloud storage services. In regards to storage, Rackspace offers Cloud Files and Cloud Block Storage. The vendor’s public cloud services are offered in data centers in the central and eastern U.S., the U.K., Australia, and Hong Kong.

Red Hat is a software provider that offers open-source software products to the enterprise community.  The vendor provides operating system platforms, along with middleware, applications, and management solutions, as well as support, training, and consulting services. Red Hat provides Red Hat Ceph Storage, an open-source software product supporting block, object storage access and file access, as well as the underlying storage for Red Hat’s data analytics infrastructure solution and Red Hat Hyperconverged Infrastructure for Cloud. The platform supports modern workloads like cloud infrastructure, data analytics, media repositories, and backup and restore systems.

Scality is a venture-backed software provider that delivers large-scale storage management and infrastructure solutions. The vendor’s flagship solution, RING, makes x86 servers scale to hundreds of petabytes and billions of objects. Additionally, RING has an end-to-end parallel architecture and a patented object storage core that increases availability and durability. The platform integrates with applications through standard storage protocols such as NFS, S3, OpenStack Swift, and Cinder. Scality offers its services to telecommunications and media companies throughout the United States, Europe, and Japan.

Silk, formerly Kaminario, provides all-flash storage and was founded by storage professionals from Dell EMC, NetApp, and IBM. The provider’s data platform delivers real-time analytics, data center automation, and assured data access, allowing users to protect their digital ecosystem. Silk’s flagship solution is now in its sixth generation. The platform provides scale-out and scale-up architecture, which enables organizations to grow in capacity based on their needs. The vendor works with a network of resellers and distributors on a global scale.

StorageCraft provides a converged primary and secondary scale-out storage platform with integrated data protection, which supports on-prem, cloud-based, or hybrid deployments. Additionally, the vendor offers data protection, data management, and business continuity solutions. The provider’s flagship platform, OneXafe, is a converged data platform that unifies enterprise data protection with scale-out storage in a configurable solution. OneXafe also offers reduced operational complexity and cost of ownership, in addition to business continuity and Disaster Recovery as a Service (DRaaS) capabilities.

SUSE is an open–source software provider that delivers software-defined infrastructure and application delivery solutions. The SUSE Enterprise Storage (SES) is based on Ceph and provides unified access for block, file, and object protocols for mainstream enterprises. Additionally, SUSE is one of the eight founding organizations on the Ceph Advisory Board and a contributor to the Ceph open-source community.  SES is delivered as software or as reference architecture through hardware OEMs with Dell EMC, Supermicro, HPE, Lenovo, Huawei, Fujitsu, and Cisco.  In 2020, SUSE acquired the Kubernetes management platform, Rancher Labs.

SwiftStack provides private cloud storage for enterprises, offering the benefits of public cloud on infrastructure IT controls. The vendor’s public cloud storage offerings come from Amazon, Google, and Microsoft. SwiftStack storage can be addressed over file services or via object APIs for use in content delivery, active archive, collaboration, and other data-centric workflows. Additionally, the provider is the main contributor to the OpenStack Swift project, as well as 1space and ProxyFS, which are dedicated to hybrid/multi–cloud and file access, respectively. SwiftStack has recently expanded its focus on Amazon S3 API support to adjacent areas such as hybrid cloud storage. In 2020, SwiftStack was acquired by NVIDIA.

Violin Systems, also known as Violin, is an enterprise storage solution provider that supports cloud, hybrid cloud, and on-prem environments. Violin storage platforms are powered by Concerto OS, an integrated storage operating system. In addition to storage, the vendor also provides a combination of data protection, business continuity, and data reduction services through its integrated data services. Violin also delivers CAPEX and OPEX savings. The provider offers server, desktop, private cloud, and hybrid cloud storage solutions, as well as a range of hardware. StorCentric recently acquired Violin Systems for an undisclosed amount.

Virtustream provides cloud computing management software and Infrastructure as a Service (IaaS) to enterprises, service providers, and governments. The provider is a subsidiary of Dell Technologies and was acquired by EMC in 2015. This resulted in EMC’s managed services and some cloud-related assets being combined with Virtustream’s offerings. The vendor’s solution, Virtustream Storage Cloud (VSC), delivers an archive-focused object storage service based on Dell EMC’s storage appliances. Additionally, the provider has multiple data centers in the U.S., as well as data centers in Germany, the Netherlands, and the U.K.

Western Digital (WD) provides data storage solutions to enable organizations to manage and preserve their digital content. The provider offers Hard Disk Drives (HDDs) and Solid-State Drives (SSDs) for desktop and notebook personal computers, as well as the performance enterprise and capacity enterprise markets. Additionally, Western Digital offers HDDs used in consumer electronics such as DVRs, security surveillance systems, and gaming consoles. The vendor’s storage technology offers two-site asynchronous replication and the ability to deploy selected Docker containers on the platform itself.

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