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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

IBM Storage Scale is an innovative software-defined solution for file and object storage, allowing organizations to create a comprehensive global data platform tailored for artificial intelligence (AI), high-performance computing (HPC), advanced analytics, and other resource-intensive tasks. In contrast to traditional applications that typically manage structured data, current high-performance AI and analytics operations are focused on unstructured data types, which can include a variety of formats such as documents, audio files, images, videos, and more. The software delivers global data abstraction services that efficiently unify various data sources across different geographic locations, even integrating non-IBM storage systems. It features a robust massively parallel file system and is compatible with a wide range of hardware platforms, comprising x86, IBM Power, IBM zSystem mainframes, ARM-based POSIX clients, virtual machines, and Kubernetes environments. This versatility enables organizations to adapt their storage solutions to meet diverse and evolving data management needs. Furthermore, IBM Storage Scale's ability to handle vast amounts of unstructured data positions it as a critical asset for enterprises aiming to leverage data for competitive advantage in today's digital landscape.

Description

Sangfor aStor represents an innovative software-defined storage solution that consolidates block, file, and object storage into a cohesive, elastically scalable resource pool, utilizing a fully symmetrical distributed architecture to facilitate on-demand provisioning of high-performance and cost-effective storage tiers tailored to various service needs. It can be deployed as either an integrated hardware-software system or as standalone software, with the ability to scale from a minimal setup of three commodity x86 nodes to expansive cloud-scale clusters comprising thousands of nodes, allowing for EB-level capacity growth. The system's multi-node parallel processing and intelligent caching mechanisms—including RDMA, SSD hot-data caching, and layering—achieve exceptional throughput, IOPS, and performance with small I/O operations, significantly enhancing cache hit rates to 90% and improving small I/O processing by as much as 65%. Additionally, its distributed metadata management ensures the seamless handling of billions of files without any significant latency, making it a robust solution for modern storage challenges. Overall, Sangfor aStor stands out as a versatile and powerful option for organizations looking to optimize their storage infrastructure.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amazon S3 No 
Azure Marketplace Yes 
IBM Fusion Yes 
Microsoft Hyper-V No 
OpenStack No 
Swift No 
VMware Cloud No 

Integrations

Amazon S3 Yes 
Azure Marketplace No 
IBM Fusion No 
Microsoft Hyper-V Yes 
OpenStack Yes 
Swift Yes 
VMware Cloud Yes 

Pricing Details

$19.10 per terabyte
Free Trial Yes 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

IBM

Founded

1911

Country

United States

Website

www.ibm.com/products/storage-scale

Vendor Details

Company Name

Sangfor

Founded

2000

Country

China

Website

www.sangfor.com/cloud-and-infrastructure/products/astor-enterprise-data-storage-solution

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