Nowadays, organizations are dealing with data growth up to and beyond the petabyte levels. Thus, this massive growth in data makes management levels too complex, such as the overheads associated with storage acquisition and operation, as well as data protection, governance and security concerns due to regulatory issues.
Therefore, modern businesses are looking out for solutions which provide agility to both enterprise network users and to a geographically dispersed workforce. At the same time, the solutions must blend with the in-house staff capabilities to leverage big data analytics in order to gain value from the vast amounts of data stores.
Currently, there are number of options to select from when building storage that will not only scale out to petabyte levels, but will also meet the needs of local and mobile users. The three options are Object storage, Software defined Storage and now the latest Data defined Storage.
In this storage approach, it does not use a file system hierarchy to store data. But instead, data is stored as objects and every object is assigned to its own unique identifier. When the user needs to retrieve the data, he/she can do it with the help of a unique claim check code. So, the actual location of physical media is abstracted within the storage pool and therefore this architecture allows virtually unlimited scalability of the virtual storage pool. The use of object based storage eliminates the need of network file sharing protocol access, as users can use a REST API. As a result, object storage is ideal for all online (IP) and cloud environments.
However, in order to support the existing file data and support data access for file based workflows, a third-party gateway server must be added with file protocols on one side and object API commands on the other. And the downside is that these gateways often eliminate many of the advantages of using object storage, including scalability; parallel object access, architectural flexibility and improved data availability to certain levels.
Note- Some companies like StoneFly, Inc., are coming up with products inducted with Unified Storage concept. Here, StoneFly Unified Storage appliance when tucked with Unified concept offers object based storage benefits as well file based storage benefits or either any one via a single solution.
Software defined storage
Strictly speaking, the true definition of SDS or software defined storage is still floating. Each and every company is coming up with its own refinement for selling their products with this latest storage trend as a tagline. So, at this time, there are a variety of interpretations for this term. In general, SDS is nothing but to abstract storage services from the physical storage hardware. The software abstracts hardware resources, pools them into aggregated capacity and automates the action of distributing them, as needed to applications.
Users can make use of a SDS environment to virtualize storage pools to manage siloed data across geographic sites and to provide policy data management related to storage optimization. This in-turn helps in optimizing the storage resources and reduces the cost of storage and storage administration, by offering various options such as deduplication, replication, thin provisioning, backup and snapshots. Thus, with the help of software defined storage, abstraction of commodity hardware through storage virtualization software can be achieved and so low TCO and enhancement in infrastructure flexibility can also be achieved.
From the past two to three years, object storage and software defined storage products are being encouraged by most storage vendors. But from the past few months, the term Data defined Storage is also hitting the headlines in the storage field.
Data defined Storage
Few companies are coming up with products which they define as data-defined. It is said to be built on both object and software defined storage technologies. What some companies offering such products say is that Object storage and SDS only satisfy three main attributes like media independent data storage, utilization of any type of storage and low cost commodity storage to scale out to petabyte levels. Data-Defined Storage unifies all data repositories and exposes globally distributed data stores through the global namespace. Thus, this eliminates data silos and improves utilization to storage resources to full level.
Additionally, the users of data-defined storage will also get data security and identity management as other two attributes. This is possible as the value of data is captured across distributed data stores by collecting all basic metadata and custom metadata and conducting full-text indexing and filtering of all standard and industry specific files.
As a final point, the conclusion is Software-defined, object storage and data-defined storage are valid options to consider when storage demand becomes a challenge in the storage environments of today’s businesses. The key is that all these platforms may look familiar, but are quite different upon closer examination, when it comes to data storage, governance, accessibility and analytical needs.