Data-defined storage is more of a methodology than a product. While there are vendors who offer data-defined storage products, the technology is not implemented in a consistent manner like a software application would be.
The main idea behind data-defined storage is that almost every organization has large amounts of unstructured data or big data. Deriving business value from this data means figuring out what information the organization has and how it can be used. Data-defined storage indexes data and metadata to turn raw data into useful information. Some data-defined storage offerings can also assign metadata to raw data that tags it and defines its purpose.
Data-defined storage can be beneficial to organizations looking for new ways to capitalize on their existing data and better meet their compliance objectives. Because data-defined storage uses data indexing, it becomes much easier to locate data in the event of litigation.
While data-defined storage is concerned with data, software-defined storage is based on the idea that storage hardware can be abstracted and treated as a pool of resources. This means an organization can assemble different storage hardware types with varying capabilities, manage that storage through a single interface and allocate that storage on an as-needed basis. A data storage administrator simply defines the required capabilities, and the software then decides how to meet those requirements using the available hardware resources.
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