Despite slight changes in market share over the past few quarters, Amazon Web Services continues to keep its crown as the winner of the cloud wars. The Seattle-based company in the second quarter of ...

Amazon Web Services (AWS) pioneered mass market, large-scale and cost-effective cloud storage when it entered the market back in 2006. The hyperscaler’s Simple Storage Service (S3) set out to make ...

Amazon Web Services can feel overwhelming, with dozens of tools and products covering everything from computing and storage ...

Amazon Web Services (AWS) S3 storage offering is now available via AWS Dedicated Local Zones, one of its on-premise cloud offerings. AWS has launched two storage classes for Dedicated Local Zones - ...

In the current macroeconomic environment, cost optimization is increasingly a focal point of businesses. But can cost be effectively saved without giving up convenience and simplicity? Amazon Web ...

From the new AWS Mountpoint for Amazon S3 to expanding support for copying data to and from other clouds like Oracle and NetApp, here’s seven new AWS cloud storage offerings just launched. Some of the ...

Tigris has raised $25 million to expand its growing network of localized data storage centers — the storage layer for ...

Working in both on-site servers and Amazon Web Services Inc. object stores, the new Amazon File Cache allows for quick access to current data sets for faster processing, according to Edward Naim, ...

All-flash storage vendor Pure Storage made its cloud move with new services that run on Amazon Web Services (AWS). The Pure Storage Cloud Data Services run Pure Storage software on AWS. They include: ...

SOFIA, Bulgaria--(BUSINESS WIRE)--StorPool Storage today announced a full-featured solution on Amazon Web Services (AWS) metal instances that enables the deployment of performance-intensive enterprise ...

Amazon Web Services (AWS) has announced vector storage for its S3 cloud object storage – S3 Vectors – in a move it claims will reduce the cost of uploading, storing and querying vectorised data in AI ...