High-performance data infrastructure
Storage Built for the Way You Work With Data
Parallel access. Unified storage. AI and HPC data platforms.
Applied Data Systems designs storage around the workload—not around a single vendor. From high-performance parallel file systems to open-source scale-out storage, ADS architects, integrates, validates, and supports the complete data platform.
Choose from IBM Storage Scale, Custom Ceph, VDURA, and BeeGFS — or let ADS determine the architecture that best fits your performance, capacity, protocol, and lifecycle requirements.
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Let’s Architect the Data Layer
Not Sure Which Storage Platform Fits?
Bring ADS your workload, data profile, performance targets, growth curve, and budget. We’ll help determine whether IBM Storage Scale, Ceph, VDURA, BeeGFS, or another architecture is the right fit.
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Applied Data Systems
©2026 Applied Data Systems
Storage Portfolio
Four Platforms. Different Strengths. One Integration Partner.
ADS helps match the storage architecture to the workload instead of forcing every environment onto the same platform.
Parallel File + Global Data
IBM Storage Scale
For large AI, HPC, analytics, and research environments that need sustained parallel performance and a global data platform.
IBM Storage Scale delivers high-performance access to unstructured data and is designed to scale across large, distributed environments.
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Open-Source Unified Storage
Ceph Storage Appliance
For organizations that want object, block, and file services from one software-defined platform without proprietary storage lock-in.
Ceph unifies object, block, and file storage in a distributed cluster built from widely available hardware. ADS sizes, tunes, integrates, and burns in the platform before deployment.
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AI + HPC Data Platform
VDURA Data Platform
For AI and HPC environments that need high parallel throughput, scale-out performance, hardware flexibility, and resilient data services.
VDURA combines a parallel file system with resilient object-based data services in a software-defined architecture designed to keep data moving across demanding AI and HPC pipelines.
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High-Performance Parallel File
BeeGFS
For AI, HPC, life sciences, and research workloads that need scalable parallel file performance with flexible server and storage hardware.
BeeGFS distributes metadata and file data across multiple services to scale throughput and capacity horizontally, with an RDMA-friendly architecture for performance-focused clusters.
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Workloads
Storage for Data-Intensive Computing
Designed for environments where storage performance directly affects compute utilization, research velocity, and time to insight.
AI Training & Inference
Feed GPU clusters with high-throughput data access while supporting checkpoints, datasets, models, and inference pipelines.
Scientific Computing
Support parallel applications, large MPI jobs, simulation output, and shared research datasets.
Life Sciences
Handle sequencing data, pipelines, image data, and rapidly growing research repositories.
Object & Data Lakes
Build scalable repositories for unstructured data, cloud-native applications, archives, and analytics.
Virtualization & Private Cloud
Deliver software-defined block and object services for flexible infrastructure and cloud-like operations.
Research & National Labs
Deploy shared, scalable storage for diverse technical workloads with demanding availability requirements.
The ADS Difference
More Than a Storage Reseller
ADS delivers storage as part of a balanced technical-computing platform, integrating compute, network, storage, and software as one system.
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Workload-Driven Architecture
Capacity, throughput, metadata behavior, client count, protocols, and growth targets drive the design.
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Complete System Integration
ADS validates storage alongside CPU/GPU compute, high-speed networking, rack design, and software dependencies.
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Performance Validation
Configuration, burn-in, and functional testing happen before the solution reaches your production environment.
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Single Point of Support
ADS helps coordinate issues across the stack so customers are not left troubleshooting between vendors.