Artificial intelligence AND MACHINE LEARNING

Extreme performance for AI workloads

Unleash AI’s full potential with RING XP, the world’s fastest object storage

Introducing RING XP

20x faster than Amazon S3 One Zone

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Accelerate AI model training and fine-tuning for faster, smarter decisions

Companies globally have embarked on AI-centric projects to find business value. Data is central to delivering this value, and it must be accessed by applications with a range of capacity and performance requirements. For intensive performance needs of AI model training and fine-tuning, this may require billions of small objects to be accessible with ultra-low (microsecond) latencies.

The challenge has been the lack of commercial storage solutions that offer this level of performance and scalability and affordability and ease-of-use to make this practical and help deliver on the promise of AI.

Challenges

RING EXTREME PERFORMANCE

Why Scality for high-performance ai

High-performance storage for AI workloads: Key challenges

Scalability

Traditional storage systems struggle to scale capacity without bottlenecking performance, making it difficult to handle the data access AI workloads require for training, fine-tuning and inference on billions of data objects while not constantly encountering limits.

Durability + availability

The faster the system, the more challenging it becomes to ensure redundancy and fault tolerance without compromising speed. Any loss of data or system downtime can affect AI performance, or waste a costly training or fine-tuning session.

Heterogeneous data types

AI workloads will encounter multiple types of data for processing — structured, unstructured, and semi-structured — across a variety of complex formats. Efficiently doing so while maintaining speed and accessibility can be challenging.

Latency sensitivity

To process data in real-time, AI workloads require ultra-low latency access to small objects. Even millisecond-level delays in data access can lead to underutilized GPUs, slow inference times or incorrect predictions, resulting in poor model performance.

Throughput demands

Some AI workloads will require access to large data objects such as images. Without sufficient throughput, models spend more time waiting for data than training, which can slow development cycles and make real-time applications impossible.

Data localization + proximity

To minimize latency, AI workloads often require that data be stored close to where it’s processed. Data locality significantly impacts performance in AI workloads, particularly for real-time decision-making.

Inefficient file system access

New AI applications are being designed using container-based, cloud-native principles.
Stateless applications naturally leverage APIs for access to services, including data storage, and will encounter inefficiencies in legacy block and file storage.

Cost-efficiency

Organizations need to invest in high-performance storage, but doing so at scale can become prohibitively expensive. The ideal solution must optimize performance without drastically increasing costs, while also fully utilizing costly GPU resources.

Meet Scality RING XP: AI storage for extreme performance at scale

To meet the demands of AI model training and fine tuning, Scality RING XP is an AI-optimized, all-flash configuration of industry-leading Scality RING. It takes performance to the unheard of level of microsecond response-time latencies for small (4KB) object data, making it the world’s fastest object store.

RING XP is the ideal ultra-fast object storage target for AI tools, custom-developed applications, and performance-optimized file systems used for training AI models.

This provides application developers with a streamlined object storage solution that provides:

Fast object storage API-based access
Unbounded scale to billions of objects and beyond
Extreme performance for small object data with microsecond access latencies
Easy-to-manage and affordable solution with intuitive UI dashboard
Choice of AMD EPYC-based storage servers

WHY SCALITY RING XP FOR HIGH-PERFORMANCE AI APPLICATIONS

Extreme performance and scalability at a fraction of the cost

Grow without limits

Encounter zero limits in number of objects, storage capacity or performance. Tested and proven at massive scale with the world’s largest customers.

Ultra-low latency

Extreme performance for small object data with microsecond access latencies, making it the perfect solution for AI inferencing, real-time analytics, and other high-demand, transaction-heavy environments.

Choice of durability + availability

RING XP provides all the durability advantages of RING (erasure coding, replication, self-healing), or optional reduced durability policies for extreme storage performance.

API-based access

RING XP provides a simple, ultra-fast and streamlined object storage API for application developers. This fits naturally with the patterns of cloud-native and AI applications.

Support for all data types

AI data in a wide variety of forms are supported on RING XP, whether they are IoT event streams, logs, documents, images or other.

Scale-out throughput

For large object data, including images and videos, RING XP can be scaled out to provide ultra-high levels of throughputs beyond GB/sec.

Control + sovereignty

Deploy RING XP in the geography and data center of your choice to ensure sovereignty, enabling close proximity of apps to storage for optimal performance.

Low cost

Licensed via affordable, usable capacity-based subscription model, RING XP leverages commercial storage servers based on AMD EPYC processors and NVMe flash drives. Efficient use of hardware resources further drives down costs.

Data-rich organizations across industries trust Scality

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lower TCO with 366% ROI

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more productive end users

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faster IT agility to deploy new storage

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Achieve AI-driven success with RING XP.

By choosing Scality, you’re investing in a future-proof solution that meets the demands of AI/ML workloads and whatever comes next.

Its scalable architecture and extreme performance help you maintain a competitive edge by enabling seamless growth, faster insights, and improved productivity across applications — without hitting capacity or speed limits.