Wednesday, June 24, 2015

Gartner’s Magic Quadrant for Structured Data Archiving and Application Retirement 2015

Magic Quadrant's definition: Structured data archiving is the ability to index, migrate and protect application data in secondary databases or flat files typically located on lower-cost storage for policy-based retention. It makes data available in context and protects it in the event of litigation or an audit.

IBM, Informatica, Delphix, Solix Technologies & HP are in the leader's quadrant of "Gartner’s Magic Quadrant for Structured Data Archiving and Application Retirement 2015 " considering following criteria by Gartner

·         Storage optimization — It can reduce the volume of data in production and maintain seamless data access. The benefits of using this technology include reduced capital and operating expenditures, improved information governance, improved recoverability, lower risk of regulatory compliance violations, and access to secondary data for reporting and analysis.
·         Governance — The technology preserves data for compliance when retiring applications. Structured data is often transactional and related to financial accounts or back-office functions (for example, HR, patient enrollment in healthcare and other use cases that might be regulated) that require information governance, control and security, along with the ability to respond to related events such as audits, litigation and investigation. These and other requirements, such as maintaining information context, can prevent organizations from moving data to lower-cost tiers of storage, or adopting other do-it-yourself approaches.
·         Cost optimization — Structured data archiving and application retirement can result in significant ROI. Structured data in legacy systems, ERP and databases accumulates over years — and, in some cases, over decades — driving up operational and capital expenses.

·         Data scalability — The technology can manage large volumes of nontraditional data resulting from newer applications that can generate billions of small objects. Scalability to petabytes of capacity is required in these cases.

Source : Gartner