Storage array vendors pivot towards unified data management and AI enablement

As storage vendors extend their product portfolios beyond traditional roles, the industry sees a shift towards unified data control and AI-centric features, aiming to simplify complex environments and enhance data utilisation across hybrid multicloud infrastructures.

One way to view the recent pivot by storage-array vendors is that storage is stepping out of the datacentre backroom and aiming for a central role in organisations’ efforts to extract value from data , mo...

st visibly for artificial intelligence but increasingly across broader business use cases. According to the original report, nearly all the major array makers have extended their product portfolios into data management, recasting storage as the foundation of data pipelines rather than merely a place to park bytes.

Vendors’ offerings differ in emphasis but converge on two themes: making data more discoverable and portable, and providing a unified control plane that reduces operational friction across on‑premises and cloud environments. Dell frames its play around the Dell AI Factory and a Data Lakehouse built on its storage, together with Project Lightning, a next‑generation parallel file system in development. HPE has refreshed its portfolio with all‑NVMe Alletra arrays and a cloud‑based Data Services Cloud Console intended to offer a SaaS control plane and AI‑driven optimisation via InfoSight. NetApp focuses on creating a “metadata fabric” , its NetApp Data Platform and MetaData Engine aim to make data timely and trustworthy for AI workloads. Pure Storage has moved towards a cloud operating model with Fusion and Enterprise Data Cloud to abstract provisioning from arrays. Smaller, AI‑first suppliers such as Vast Data promote an “AI operating system” from storage to application, with event streaming and planned agent management capabilities. Huawei positions a full‑stack approach around its Data Management Engine, offering data catalogue, lineage and vector database functions.

Industry data shows a particular emphasis on breaking down data silos and delivering unified management across block, file and object storage because customers increasingly run workloads across multiple datacentres and public clouds. According to the original report, that is a central selling point for several suppliers and a direct response to customers’ stated need to move data to where it is most useful.

Hitachi Vantara’s Virtual Storage Platform One (VSP One) exemplifies one way vendors are answering this need. Launched as a software‑defined architecture to provide a common data plane across storage types and hybrid‑multicloud environments, VSP One has been positioned by Hitachi as a platform to simplify large, distributed data estates and to harden data availability and resilience. The company claims VSP One delivers a unified management experience that spans block, file and object, together with integrated cloud tiering and ransomware protection. Hitachi says the platform offers a 100% data availability guarantee and is tuned to support AI workloads and sustainability goals.

External recognition has followed that positioning. VSP One was named in the 2025 CRN Products of the Year Awards for Excellence in Hybrid Cloud Storage, with judges citing its ability to simplify hybrid deployments and improve operational efficiency. Hitachi has also expanded the VSP One family with an object storage appliance and a quad‑level cell (QLC) flash array to increase dense capacity and public cloud replication options; the company says these additions tighten integration between object, file and block storage to serve AI and analytics workloads more effectively. Independent analyst coverage has further highlighted VSP One Object for rapid innovation, including industry‑first native support for Amazon S3 Tables and data‑intelligence services that permit SQL‑based analytics directly on open‑format unstructured data, reducing the need for costly data movement.

Hitachi is also pursuing ecosystem integration: the company said it has collaborated with Red Hat to combine Red Hat OpenShift Virtualisation with VSP One, aiming to ease virtual machine migrations, reduce dependency on proprietary hypervisors and accelerate hybrid‑cloud modernisation. The partnership is pitched at customers looking to modernise legacy virtualisation while retaining enterprise resilience and performance.

Those developments underline a broader market dynamic. Storage vendors are attempting to move up the stack by offering metadata services, data lineage, catalogues and control planes that appeal to AI teams and data engineers as much as to storage administrators. The company statements and product launches amount to a bet that control over data access, metadata and movement will be the key commercial differentiator as organisations scale AI initiatives.

But a friction remains between vendors’ ambitions and customers’ realities. Many enterprises still operate fragmented environments across multiple clouds and datacentres, and while vendors promise unified control planes and seamless data mobility, customers often cite integration complexity, legacy tooling and the cost of data egress as barriers. According to the original report, some suppliers foreground fleet and data management as the strategic core of their offering, while others package similar capabilities as accelerants for AI workloads , a distinction that reflects differing sales narratives rather than fundamentally different technical approaches.

As vendors extend feature sets, some important trade‑offs are emerging. Consolidating data management through a single vendor can simplify operations and speed AI pipelines, but it can also raise questions about portability and vendor lock‑in. Industry observers note that partnerships and open APIs will be critical to giving customers choice; Hitachi’s recent Red Hat collaboration is a signal that at least some vendors see hybrid openness as a competitive necessity.

In short, the storage market is evolving into a battleground for data management and AI enablement. Vendors are layering metadata fabrics, lakehouse concepts, object‑to‑table intelligence and cloud control planes on top of traditional arrays to claim a seat at the centre of the data stack. The outcome for customers will depend on how well those technologies interoperate with existing estates, the clarity of the vendors’ operational models, and whether promises of unified availability, resilience and analytics can be delivered across the heterogenous environments that most organisations still run.

Source: Noah Wire Services