Tuesday, October 28, 2014

Gartner Magic Quadrant for Operational Database Management Systems 2014

The operational DBMS market continues to grow, with innovative products and features being delivered by both new and traditional vendors. Information management leaders will be particularly interested by the changes in the Leaders quadrant.

Gartner's Strategic Planning Assumptions
By 2017, the "NoSQL" label will cease to distinguish DBMSs, which will reduce its value and result in it falling out of use.
By 2017, all leading operational DBMSs will offer multiple data models, relational and NoSQL, in a single platform.

IBM, Oracle, Microsoft, SAP, InterSystems, EnterpriseDB (PostgreSQL), MarkLogic & MariaDB are in the Leaders Quadrant of "Magic Quadrant for Operational Database Management Systems 2014"

Market Definition/Description
The operational database management system (DBMS) market is defined by relational and nonrelational database management products that are suitable for a broad range of enterprise-level transactional applications. These include purchased business applications such as enterprise resource planning (ERP), customer relationship management and customized transactional systems built by an organization's development team. In addition, Gartner include DBMS products that also support interaction data and observation data as new transaction types. These products are also used both for purchased business applications, such as ERP, catalog management and security event management, and for customized systems.

Operational DBMSs must include functionality to support backup and recovery, and have some form of transaction durability — although the atomicity, consistency, isolation and durability (ACID) model is not a requirement. For open-source DBMSs, maintenance and support must be available from a vendor that owns, or has substantial control over, the source code, and must be offered with a full General Public License (GPL) or an alternative.

For this Magic Quadrant, Gartner define operational DBMSs as systems that support multiple structures and data types, such as XML, text, JavaScript Object Notation (JSON), audio, image and video content. They must include mechanisms to isolate workload resources and control various parameters of end-user access within managed instances of data . Emerging technologies, such as cloud-only DBMSs, are not included; nor are highly specialized engines such as graph-only or object databases, which may perform some transactions for small subsets of operational use cases. Products that "add a layer" to and require or embed a complete or near-complete implementation of another commercially marketed product, such as Oracle MySQL, are not included. Finally, "streaming" engines, whose use cases are dominated by immediate event processing, and which are rarely, if ever, used for subsequent management of the data involved, are also excluded.

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