target audience: TECH BUYER Publication date: Jun 2022 - Document type: IDC Perspective - Doc Document number: # US49039822
Object Storage Moves Beyond Traditional Backup and Archival Use Cases to Target High-Performance Workloads
Content
List of Figures
Get More
When you purchase this document, the purchase price can be applied to the cost of an annual subscription, giving you access to more research for your investment.
Related Links
Abstract
This IDC Perspective provides an overview of major object storage products designed for use in on-premises datacenters, edge locations, and hybrid cloud environments. Object storage vendors are expanding their focus beyond traditional backup and archive use cases to target higher-performance workloads such as big data analytics and AI/ML applications. Key developments driving the transition include product support for flash-based media to speed data storage and metadata operations, the growing adoption of Amazon's S3 API among software developers, and the availability of new and re-architected object stores designed for Kubernetes-, container-, and/or edge-based deployments. Backup and archive will remain important if not dominant use cases for object storage, especially as vendors promote features such as immutability and object locking for ransomware protection. However, new product capabilities and long-standing advantages of cost effectiveness and ease of scaling to petabytes and potentially exabytes of data should make modern object storage a strong contender against block- and file-based alternatives for next-generation workloads.
"Enterprises undertaking digital transformation initiatives face decisions about whether to use block-, file-, or object-based storage for their escalating volumes of unstructured data," said Carol Sliwa, research director, Infrastructure Systems, Platforms, and Technologies Group at IDC. "Object storage has evolved beyond its roots as a cheap-and-deep repository for backups and archives and merits consideration for many high-performance modern workloads, including analytics and artificial intelligence."