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.
Peters, Mark. "Unlocking the Power of Data with Data-Defined Storage" (PDF). ESG. Archived from the original (PDF) on 2014-11-29. Retrieved 30 June 2013. https://web.archive.org/web/20141129113204/http://www.esg-global.com/default/cache/File/2D9FD2A8-B6D3-4D17-A23527EF427F6C96.pdf ↩
Goyal, Ambuj. "Edge2013 General Session Keynote Speech". IBM Edge. Archived from the original on 2016-04-13. Retrieved 2016-11-27. https://www.youtube.com/watch?v=JfHTDnspaaQ&feature=c4-overview-vl&list=PLUbRx39vvOvj0meMsZiU6DWYEDmi0iali ↩