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What is MayaScale?

Develop a comprehensive NVMe over Fabrics shared storage solution using MayaScale that facilitates the incorporation of directly attached NVMe resources into a cohesive storage pool. This system allows for dynamic allocation of NVMe namespaces to clients seeking superior performance with low latency. After their requirements are met, clients can easily return NVMe storage to the collective pool, effectively addressing the common challenges of over-provisioning and wasted NVMe resources often seen in direct-attached architectures. The architecture is network-agnostic, utilizing RDMA for on-premises setups and standard TCP for cloud-based environments, which enhances its adaptability. Clients are able to connect to genuine NVMe devices through a standard NVMe driver stack, eliminating the necessity for proprietary drivers. Configuring and deploying an NVMe over Fabrics SAN infrastructure at rack scale in a data center can be accomplished by integrating various NVMe devices through RDMA-compatible links, such as ROCE, iWARP, or Infiniband. Moreover, in public cloud scenarios, users can take advantage of NVMe over Fabrics via the conventional TCP/IP protocol, removing the need for specific RDMA hardware or SRIOV virtualization. This forward-thinking approach not only maximizes resource efficiency but also ensures consistent high performance across different deployment landscapes, making it a versatile choice for modern storage solutions. Ultimately, this innovative design paves the way for improved scalability and flexibility in data management strategies.

What is Hammerspace?

Hammerspace is an innovative storage solution that unlocks the vast amounts of fast local NVMe storage inside GPU servers, turning what was previously stranded capacity into a new ultra-fast storage tier that accelerates AI training and checkpointing. Designed to overcome the limitations of expensive and complex legacy storage systems, Hammerspace enables consistently high GPU utilization by providing low-latency, parallel access to data across thousands of servers simultaneously. The platform’s global data architecture is built on standard NFS protocols, eliminating the need for proprietary clients and simplifying integration with existing Linux storage servers and hybrid cloud environments. By orchestrating data movement between on-premises and cloud infrastructure, Hammerspace supports flexible AI workflows that maximize resource usage and minimize power consumption. Hammerspace has been proven through MLPerf benchmarks to deliver scalable, linear performance gains, dramatically speeding up checkpointing times by 10 to 100 times. Trusted by industry leaders like Meta and Los Alamos National Laboratory, it helps reduce external storage costs, power usage, and rack space requirements. The platform’s intuitive interface and rapid deployment allow organizations to bring petabytes of capacity online within days and start accelerating AI workloads immediately. Its hyperscale NAS architecture ensures consistent throughput and low latency at scale, critical for large machine learning projects. By transforming idle GPU server storage into a shared, protected resource, Hammerspace redefines cost efficiency and performance in AI infrastructure. This technology empowers data-driven organizations to innovate faster, reduce their energy footprint, and optimize their AI investment returns.

Media

Media

Integrations Supported

Google Cloud Platform
Microsoft Azure
AWS Marketplace
Amazon
Amazon RDS
MongoDB
MySQL Workbench
Oracle Cloud Infrastructure FastConnect
Red Hat CloudForms

Integrations Supported

Google Cloud Platform
Microsoft Azure
Amazon Web Services (AWS)
Azure Marketplace

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
On-Site Training

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

ZettaLane Systems

Date Founded

2018

Company Website

www.zettalane.com/maya-nvmeof-linux-rdma-tcp.html

Company Facts

Organization Name

Hammerspace

Date Founded

2018

Company Location

United States

Company Website

hammerspace.com

Categories and Features

Block Storage

Not specified

Categories and Features

Data Management

Not specified

Data Virtualization

Not specified

Disaster Recovery

Not specified

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