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.

Gartner Magic Quadrant for Web Content Management: 2014

Web content management is no longer simply a tool for creating Web pages — it's now vital software for increasing the effectiveness of digital strategies. IT leaders responsible for WCM should consider the software's functions in the broader context in which they will deliver their full value.

IBM, Adobe, HP, Oracle, Acquia & Sitecore are in the leader’s quadrant in ‘Gartner Magic Quadrant for Web Content Management: 2014’ .

Gartner defines Web content management (WCM) as the process of controlling content to be consumed over one or more digital channels through the use of management software based on a core repository. These may be commercial products, open-source or hosted service offerings. Product functions go beyond simply publishing Web pages, to include:

• Content creation functions, such as templating, workflow and change management.
• WCM repositories that contain content or metadata about the content.
• Library services, such as check-in/check-out, version control and security.
• Content deployment functions that deliver prepackaged or on-demand content to Web servers.
• A high degree of interoperability with adjacent technologies, such as CRM, multichannel campaign management (MCCM), marketing resource management, digital asset management (DAM) and Web analytics.
• Real-time adaptation to visitor interaction through a delivery engine, an enhanced framework for delivery applications or similar. Some products also integrate well with delivery tiers such as e-commerce, social media and portal software.

The Forrester Wave™: Web Analytics, Q2 2014

Adobe, AT Internet, IBM, And Webtrends Are Leaders In Enterprise Web Analytics

For more refer: http://webtrends.com/files/report/Report-Forrester_Wave_Web_Analytics.pdf 

Gartner Hype Cycle 2014 and its 2000 digital business technologies

 New Hype Cycles this year include Digital Workplace, Connected Homes, Enterprise Mobile Security, 3D Printing and Smart Machines.

Gartner’s road map to digital business is made up of 6 models –  analog, web, e-business, digital marketing, digital business, autonomous – with the focus this year on the last three.

• Digital Marketing tech includes: Software-Defined Anything; Volumetric and Holographic Displays; Neurobusiness; Data Science; Prescriptive Analytics; Complex Event Processing; Big Data; In-Memory DBMS; Content Analytics; Hybrid Cloud Computing; Gamification; Augmented Reality; Cloud Computing; NFC; Virtual Reality; Gesture Control; In-Memory Analytics; Activity Streams; Speech Recognition.
• Digital Business tech includes: Bioacoustic Sensing; Digital Security; Smart Workspace; Connected Home; 3D Bioprinting Systems; Affective Computing; Speech-to-Speech Translation; Internet of Things; Cryptocurrencies; Wearable User Interfaces; Consumer 3D Printing; Machine-to-Machine Communication Services; Mobile Health Monitoring; Enterprise 3D Printing; 3D Scanners; Consumer Telematics.
• Autonomous stage tech include:   Virtual Personal Assistants; Human Augmentation; Brain-Computer Interface; Quantum Computing; Smart Robots; Biochips; Smart Advisors; Autonomous Vehicles; Natural-Language Question Answering.

From: http://diginomica.com/2014/08/12/gartnerhypecycle/#.U-tgvfmSwaA 

Gartner Magic Quadrant for Data Integration Tools : 2014

The demand for data integration tools emphasizes broad applicable use, a well-integrated portfolio and interoperability with information and application infrastructures. Flexible deployment and scalability are still expected, while interest in business-facing and platform-as-a-service models grows.

Informatica, IBM (InfoSphere Suite), SAP (SAP DS ..), Oracle (ODI, OWB ..), SAS (SAS DMP..) are in the leader's quadrant. Gartner has consider broadly following criteria as given below:

• Connectivity/adapter capabilities (data source and target support)
• Data delivery capabilities
• Data transformation capabilities
• Metadata and data modeling capabilities
• Design and development environment capabilities
• Data governance support capabilities (via interoperation with data quality, profiling and mining capabilities)
• Deployment options and runtime platform capabilities
• Operations and administration capabilities
• Architecture and integration capabilities
• Service enablement capabilities

For more please refer: http://www.informatica.com/us/data-integration-magic-quadrant/?ref=wwwlnkpr#fbid=oP2vqjqI1WB 

Magic Quadrant for Structured Data Archiving and Application Retirement

Structured data archiving describes 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, HP, Solix Technologies are in the leader's quadrant.

Refer : http://www.informatica.com/us/data-archiving-magic-quadrant/?ref=wwwbnrhp#fbid=oP2vqjqI1WB

Forrester Wave™: Big Data Streaming Analytics Platforms, Q3 2014

Software AG, IBM, Informatica, SAP & Tibco are the leader in 'Forrester Wave™: Big Data Streaming Analytics Platforms, Q3 2014'.

Business won’t wait. That is truer today than ever before because of the white-water flow of data from innumerable real-time data sources. Market data, clickstream, mobile devices, sensors, and even good old fashioned transactions may contain valuable, but perishable insights. Perishable because the insights are only valuable if you can detect and act on them right now. That’s where streaming analytics platforms can help. Forrester defines streaming analytics platform as:

Software that can filter, aggregate, enrich, and analyze a high throughput of data from multiple disparate live data sources and in any data format to identify simple and complex patterns to visualize business in real-time, detect urgent situations, and automate immediate actions.

For more please refer: https://info.softwareag.com/apama-leader-forrester-wave-big-data-streaming-analytics-solution.html