We Often Hear the Terminology Data Defined Storage in the Context of Big Data. What is Data Defined Storage? Data defined storage is factually marketing termiology. The terminology is used for data related application and storage. In this brief article, we will discuss what apparently the terminology means.
What is Data Defined Storage?
Data defined storage has dual benefits of object storage and software-defined storage. Pillars of these storages can be mapped to through a process of unification. In such setup, users, apps and devices gain access to a repository of captured metadata providing a flexible and scalable platform for storage of data. So the total technology in essence abstracts the data entirely from the storage part. Primarily the matter is at software level.
Among the pillars, there is :
- Media Independent Data Storage
- Distributed Metadata Repository
- Data Security & Identity Management
The terminology possibly first was used for object storage with open protocol access for file system virtualization. So protocols include CIFS, NFS, FTP, REST APIs and others like we use for Amazon S3, OpenStack and so on.
Ultimate goal is to leverage speed and accuracy of search and discovery, leading to informed business decisions and analytics. The terminology was first coined by Tarmin GridBank. So it is normal to have slides and illustrations from them :
Conclusion on Data Defined Storage
As like any other cloud service, Data Defined Storage has similar advantages and disadvantages. It is factually more towards traditional Software as a Service (SaaS).