Data defined storage (also referred to as a data centric approach) is a marketing term for managing, protecting, and realizing the value from data by combining application, information and storage tiers.[1]
This is a process in which users, applications, and devices gain access to a repository of captured metadata that allows them to access, query and manipulate relevant data, transforming it into information while also establishing a flexible and scalable platform for storing the underlying data. The technology is said to abstract the data entirely from the storage, trying to provide fully transparent access for users.
Data defined storage explains information about metadata with an emphasis on the content, meaning and value of information over the media, type and location of data. Data-centric management enables organizations to adopt a single, unified approach to managing data across large, distributed locations, which includes the use of content and metadata indexing. The technology pillars include:
Data defined storage focuses on the benefits of both object storage and software-defined storage technologies. However, object and software-defined storage can only be mapped to media independent data storage, which enables a media agnostic infrastructure - utilizing any type of storage, including low cost commodity storage to scale out to petabyte-level capacities. Data defined storage unifies all data repositories and exposes globally distributed stores through the global namespace, eliminating data silos and improving storage utilization.
The first marketing campaign to use the term data defined storage was from the company Tarmin, for its product GridBank. The term may have been mentioned as early as 2013.[2]
The term was used for object storage with open protocol access for file system virtualization, such as CIFS, NFS, FTP as well as REST APIs and other cloud protocols such as Amazon S3, CDMI and OpenStack.