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Data Defined Storage

As new technologies, such as growing image and video resolution, social media, mobile internet and bio-sensitive medical devices, and an ever more interconnected world through the Internet of Things, drive increasing volumes of data, traditional models for managing data are being stretched to their scalability limits [1] This has driven the storage industry and data management, industry to take a new approach to scalable data storage, known as Data Defined Storage, or abbreviated DDS. It is a mechanism for storing, retaining and accessing data based on its content, meaning and value. It is designed to address the requirements of industries characterized by escalating data volumes, increasing regulatory requirements and data driven innovation.

Introduction

Data Defined Storage takes a new approach to managing, scaling, protecting, retaining, searching and realizing value from data by uniting the application, information and storage tiers into a single, integrated data centric management architecture[2] .Through this process of unification, users, applications and devices gain access to a repository of captured metadata that empowers organizations to access, query and manipulate the critical components of the data to transform it into information, whilst providing a flexible and scalable platform for storage of the underlying data. The main advantage of the technology is that the data is entirely abstracted from the storage, allowing the user transparent access whatever, and wherever the data resides, allowing a high performance, grid based, scalable approach to storage and data management.

Core Innovation Pillars

With its focus on metadata, Data Defined Storage emphasizes the content, meaning and value of information over the media, type and location of data. This translates into three key innovations that are tied together with Data Centric Management and are necessary to meet the emerging requirements associated with the growing data volumes. Data Centric Management as part of Data Defined Storage enables organizations to take a single, holistic view and approach to accessing and managing application-based data across large, distributed locations with deep content and arbitrary metadata tag search and big data analytics integration. The innovation pillars include:

  1. Media Independent Data Storage: Data Defined Storage removes media centric data storage boundaries within and across solid-state drive , hard disk drive , cloud storage and tape storage platforms, promotes linear scale out functionality through implementing a grid based Map Reduce architecture and provides transparent data access across globally distributed repositories for storage performance at high volumes.
  2. Data Security & Identity Management: Data Defined Storage allows organizations to gain end-to-end identity management down to the individual user and device level providing consumerization of IT, mobility and enhanced information security and information governance.
  3. Distributed Metadata Repository: Data Defined Storage enables organizations to virtualize aggregate file systems for a single global namespace, and access metadata information to extract value leading to important and informed business decisions and analytics.

Typical Implementation

The first implementation of Data Defined Storage was pioneered by Tarmin, in its GridBank Data Management Platform. The company was founded by Shahbaz Ali and Steve Simpson in 2007, following an engagement working at MasterCard, where they experienced the challenges associated with storing, capturing and processing massive volumes of financial transactions first hand. GridBank was designed to meet the promise of Data Designed Storage, by taking a data centric approach to storage and data management. It was in development for 3 years prior to its initial release to the market in 2010, with its 3rd version being released in June 2013. [3]

Market Status

Though the Data Defined Storage market is still in its early days, there is wide acknowledgement amongst key storage and data management industry players that the future of the market is in emphasizing the value of data through scalable distributed metadata management techniques[4] Additionally, the category has received strong support in the analyst space, with firms such as ESG and IDC providing predictions of significant market growth with the category representing a “blueprint for a new breed of modular architectures that unlock the value of data as a business-critical asset”[5][6] whilst Steve Duplessie has highlighted the broader value of Data Defined Infrastructure [7] Pioneering customers have begun deploying Data Defined Storage solutions in industries such as oil and gas data discovery[8] , healthcare, financial services and managed service provision [9] .

Technology

Data Defined Storage takes the approach of unifying object storage with open protocol for file system virtualization, such as CIFS , NFS, FTP as well as REST API's.When implemented in combination with block storage technologies, such as IBM XIV , Data Defined Storage unifies block, file and object technologies to enable high performance[10] , massively scalable[11] data storage.

See Also

References

  1. ^ "Object Storage: The Future Building Block for Storage Systems" (PDF). IBM Hiafa Research Laboratories.
  2. ^ Peters, Mark. "Tarmin GridBank:Unlocking the Power of Data with Data-Defined Storage" (PDF). ESG. Retrieved June 2013. {{cite web}}: Check date values in: |accessdate= (help)
  3. ^ "Data Defined Storage Emerges with Tarmin GridBank 3.0". Financial Content. Retrieved 4 June 2013.
  4. ^ Goyal, Ambuj. "Edge2013 General Session Keynote Speech". IBM Edge.
  5. ^ Nadkami, Ashsh. "Tarmin Launches GridBank 3.0: Data-Defined Storage". IDC.
  6. ^ Peters, Mark. "Tarmin GridBank: Unlocking the Power of Data with Data Defined Storage" (PDF). ESG. Retrieved June 2013. {{cite web}}: Check date values in: |accessdate= (help)
  7. ^ Duplessie, Steve. "Video Blog: Data-defined Infrastructure". ESG.
  8. ^ Miller, Dan (12 July 2013). "Tarmin and IBM help Premier Oil manage rapidly growing unstructured data". PR Newswire.
  9. ^ Miller, Dan (17 December 2012). "Leading U.K. MSP brightsolid sees a shining future with Tarmin". PR Newswire.
  10. ^ "IBM XIV Storage System Gen3 Architecture, Implementation, and Usage" (PDF). IBM.
  11. ^ "Object Storage: The Future Building Block for Storage Systems" (PDF). IBM Haifa Research Laboratories.
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