Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Hammerspace innovatively leverages the local NVMe storage embedded within GPU servers, converting it into a high-performance, shared storage tier designed specifically for large-scale AI training and checkpointing workloads. This approach eliminates bottlenecks inherent in legacy storage systems that struggle to keep GPUs fully utilized, while significantly reducing power consumption and external storage expenses. The platform’s parallel file system architecture supports massive scalability, allowing data to be served simultaneously to thousands of GPU nodes with minimal latency. Hammerspace integrates seamlessly with existing Linux storage servers and supports hybrid cloud environments, enabling data orchestration between on-premises and cloud infrastructure. It delivers record-setting performance validated by MLPerf benchmarks, proving its efficiency for demanding machine learning workloads. Customers such as Meta and Los Alamos National Laboratory trust Hammerspace to optimize their AI data pipelines and infrastructure investments. With quick setup and intuitive management, Hammerspace helps organizations accelerate AI projects while reducing operational complexity. By transforming underutilized storage into a powerful resource, Hammerspace drives cost savings and faster innovation.
Description
UltiHash is a high-speed object storage solution tailored for AI, analytics, and demanding data workloads. Its design focuses on enhancing storage efficiency by incorporating built-in deduplication, all while ensuring the performance required by contemporary, data-heavy applications. UltiHash operates as a Kubernetes-native storage cluster on a team's infrastructure, ideally utilizing flash-based storage, and integrates seamlessly with existing workflows via its robust S3-compatible API. Teams can effortlessly upload their data, allowing UltiHash to handle redundant storage reduction automatically, while also providing high-throughput data access. This integration enables connections to a range of tools, including GenAI, analytics, machine learning, and lakehouse systems, without the need to alter their existing tech stack. The platform is specifically optimized for modern flash architecture, making it particularly effective for “write once, read many” scenarios where large datasets require frequent and rapid access. Furthermore, its user-friendly interface and powerful capabilities make it an attractive choice for organizations looking to streamline their data storage and retrieval processes.
API Access
Has API
API Access
Has API
Integrations
Amazon Web Services (AWS)
Amazon S3
Azure Marketplace
Google Cloud Platform
Hetzner
Kubernetes
Microsoft Azure
Integrations
Amazon Web Services (AWS)
Amazon S3
Azure Marketplace
Google Cloud Platform
Hetzner
Kubernetes
Microsoft Azure
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
€0.15 per month
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Hammerspace
Founded
2018
Country
United States
Website
hammerspace.com
Vendor Details
Company Name
UltiHash
Founded
2022
Country
United States
Website
www.ultihash.io
Product Features
Data Management
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge
Disaster Recovery
Administration Policies
Bare-Metal Recovery
Encryption
Failover Testing
Flexible Data Capture
Multi-Platform Support
Multiple Data Type Support
Offline Storage
Product Features
Alternatives
Alternatives
No Alternatives