Bimodal approaches that demand infrastructure agility and scalability are stimulating market adoption of scale-out file and object storage products. This research helps I&O leaders assess the key attributes, vision and execution prowess of distributed file systems and object storage market vendors.
Strategic Planning Assumption
By 2021, more than 80% of enterprise data will be stored in scale-out storage systems in enterprise and cloud data centers, up from 30% today.
Market Definition/Description
Scale-out storage systems are growing fast and becoming a popular platform to tackle the unabated growth of unstructured data. With data growth exceeding 40% year over year in many enterprises, infrastructure and operations (I&O) leaders are looking for extensible storage products that can address an increasing number of use cases with lower acquisition and operational costs.
Enterprises are demanding features and capabilities prevalent in big data cloud infrastructures, such as self-healing and ease of management. Software-defined storage (SDS), deployed on commodity hardware, is emerging as a threat to external controller-based (ECB) storage arrays in environments with a steep growth of unstructured data. New and established storage vendors are continuing to develop scalable storage clustered file systems and object storage products to address cost and scalability limitations in traditional, scale-up storage environments.
Gartner defines distributed file systems and object storage as software and hardware solutions that offer object and/or scale-out file technology to address requirements for unstructured data growth and based on ‘shared nothing architecture.’ A shared nothing architecture is a distributed computing architecture in which each node is independent and self-sufficient, and there is no single point of contention across the system (see the Acronym Key and Glossary Terms section).
Distributed file system storage uses a single parallel file system to cluster multiple storage nodes together, presenting a single namespace and storage pool to provide high bandwidth for multiple hosts in parallel. Data is distributed over multiple nodes in the cluster to deliver data availability and resilience in a self-healing manner, and to provide high throughput and capacity linearly.
Object storage refers to devices and software that house data in structures called “objects,” and serve clients via RESTful HTTP APIs, such as Amazon Simple Storage Service (S3) and OpenStack Swift.
Vendor Strengths and Cautions
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