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Storage built for AI workloads.

High performance to keep GPUs fed, high density to scale economically —
One platform that places data automatically where it belongs.
Let's Talk Storage
Start in Console

One platform, automatically tiered —
Fast for live workloads. Efficient at scale.

One AI Storage platform places data on the right media on its own — high-performance media keeps GPUs fed, high-density media holds everything else economically.

  • High-performance — parallel, GPU-tuned file systems that keep clusters fed during training and inference, built on the platforms your workloads already trust: Weka, DDN, GPFS, VAST.

  • High-density — capacity-optimized storage for data lakes, checkpoints, and archives, at the lowest cost and power per terabyte.

Idle GPUs are the most expensive thing in your data center.

Storage that can’t keep up stalls training and drags down inference.

Aurora AI Storage delivers predictable throughput under sustained load, then moves cold data to denser media automatically to control cost as datasets grow. A single namespace spans high-performance and high-density media, with lifecycle policies moving data between them — no manual migration, no second system to manage.

Aurora Gives You:

Single
Namespace

Automatic
Lifecycle

File, Block,
and Object

Managed &
Monitored

Use Case Examples:

AI Data Lake

Checkpoints

Inference
Memory & State

Backup & Archive

Keep your GPUs fed.

Let’s size the right storage for your workload.
Start in the Aurora Console
Let's Talk Storage