The landscape of high-performance computing (HPC) storage is undergoing significant change.
Traditional simulation and data engineering workloads are increasingly running alongside generative AI, machine learning pipelines and real-time deep learning.
Managing multi-petabyte datasets means research organisations need storage architectures that match their application portfolios in order to sustain throughput. Parallel file systems remain the default choice for many, but they now compete with all-flash scale-out systems, hybrid cloud frameworks and software-defined storage.
The shifting landscape of data architecture
Choosing an architecture requires understanding a broadening hardware landscape. Many organisations are moving away from proprietary hardware stacks toward software-defined, subscription-based layers that separate performance from the underlying media.
The focus has also shifted from raw capacity toward data management: storing data is no longer sufficient on its own, and researchers increasingly need to discover, classify and secure data at the source so it can feed computational pipelines without stalling clusters.
Next-generation parallel file systems and software-defined engines
Parallel file systems remain central to large-scale simulation work, though many have been redesigned for decentralised deployments.
- BeeGFS uses a distributed metadata architecture that allows independent scalability. The software is open source, with enterprise support available through ThinkParQ and its partners.
- IBM Storage Scale unifies parallel file and object access, aimed at exabyte-scale analytics, allowing organisations to run analytics and archiving in place rather than across separate storage silos.
- HPE Cray ClusterStor uses the Lustre file system and interfaces with HPE Slingshot, InfiniBand and other supercomputing fabrics.
- VDURA (formerly Panasas) has moved from proprietary hardware to a software-defined model, using a microservices core with load balancing and multi-level erasure coding across flash and disk under a single namespace.
- Quobyte is built for scale-out storage with linear performance scaling, designed to be managed by small administrative teams across large deployments.
- MooseFS combines storage and compute on commodity hardware, with configuration and implementation support available.
High-capacity object storage and the archival continuum
As unstructured data volumes grow, active archiving and object storage platforms are increasingly replacing traditional cold storage.
- DataCore Swarm (incorporating Caringo Swarm) offers immutable object storage with multi-attribute search, positioned as an active archive that reduces the need for periodic data migration.
- Scality RING, alongside its lightweight ARTESCA framework, spans cloud, core and edge deployments and includes connectors intended to let retrieval-augmented generation (RAG) tools access object data directly.
- Spectra Logic combines disk, object storage and tape libraries across tiers, aimed at organisations balancing environmental, cost and scaling requirements.
- Qualstar produces automated magnetic tape arrays for offline, energy-efficient data protection.
- NEC Storage HS Series uses distributed grid storage for long-term retention with independent scaling of performance and capacity.
All-flash acceleration and low-latency infrastructure
The I/O demands of modern GPUs have driven adoption of all-flash arrays designed for highly concurrent pipelines.
- DDN EXAScaler targets deep learning and AI workloads, with multi-terabyte-per-second throughput aimed at reducing I/O bottlenecks in petascale environments.
- Everpure FlashBlade (formerly Pure Storage) has moved from hardware appliances toward a broader enterprise data cloud offering, with automated data classification built in.
- WEKA coordinates memory and storage across a software fabric aimed at dense accelerator clusters, targeting microsecond latencies across cloud and on-premises deployments.
- Microsoft Azure offers managed Lustre, Azure NetApp Files and other high-performance cloud storage services for HPC and AI workloads.
Qumulo Core provides native file access across hybrid environments with visibility into unstructured data. - NetApp produces all-flash SAN and NAS arrays for enterprise applications including telemetry analytics and backup.
Turnkey appliances and system integration
For organisations that want pre-configured or purpose-built platforms, several vendors offer hardware appliances and integration services.
- Atipa Capella appliances combine metadata, management and object storage modules for enterprise deployment.
- ClusterVision designs storage frameworks connecting network-attached storage to parallel file systems or hybrid cloud, drawing on over two decades of systems deployment experience.
- QCT (Quanta Cloud Technology) pairs open-source orchestration tools with custom system architectures for HPC and deep learning deployments.
- Seagate produces mass-capacity storage arrays aimed at data-heavy workloads with space and power constraints.
- SoftIron HyperCloud offers modular compute, virtualisation and storage for private cloud deployments, positioned as avoiding vendor lock-in.
- Open-E JovianDSS is a ZFS-based storage operating system offering high-availability cluster failover and multi-protocol NAS/SAN support.
- QNAP produces network-attached storage systems used for high-volume file transfer and large-file workloads such as 3D scanning data.
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