Thank Gartner for the info.
Entering 2014, the hype around replacing the data warehouse gives way to the more sensible strategy of augmenting it. New competitors have arisen, leveraging big data and cloud, while traditional vendors have invested — which will force improved execution from new technology companies.
For this Magic Quadrant, we define a DBMS as a complete software system that supports and manages a database or databases in some form of storage medium (which can include hard-disk drives, flash memory, and solid-state drives or even RAM). Data warehouse DBMSs are systems that can perform relational data processing and can extended to support new structures and data types, such as XML, text, documents, and access to externally managed file systems. They must support data availability to independent front-end application software, include mechanisms to isolate workload requirements (see Note 2) and control various parameters of end-user access within managed instances of the data.
A data warehouse is a solution architecture that may consist of many different technologies in combination (see Note 3). At the core, however, any vendor offering or combination of offerings must exhibit the capability of providing access to the files or tables under management by open access tools. A data warehouse is simply a warehouse of data, not a specific class or type of technology.
In 2014, this Magic Quadrant introduces non-relational data management systems for the first time. No specific rating advantage is given regarding the type of data store used (for example, DBMS, Hadoop Distributed File System [HDFS]; relational, key-value, document; row, column and so on). All vendors are expected to provide multiple solutions (although one approach is adequate for inclusion), each demonstrating maturity and customer adoption. Also, cloud solutions (such as platform as a service) are considered viable alternatives to on-premises warehouses.
A data warehouse DBMS is now expected to coordinate data virtualization strategies, and distributed file and/or processing approaches, to address changes in data management and access requirements.
Microsoft (www.microsoft.com) markets SQL Server 2012 (Service Pack 1 has been available since November 2012), a reference architecture and the parallel data warehouse appliance. Microsoft does not report customer or license counts. Gartner estimates Microsoft’s relational DBMS revenue grew 13.6% during 2013 — faster than the overall market.
– Microsoft offers appliances, reference architectures including a variety of hardware, prebuilt offerings built to customer selections then delivered ready to run, software licensing and managed services data warehouses.
– Customers report a low count of software issues, above-average customer experience and obvious interoperability with Excel (and Office).They also like the easy-to-understand licensing and pricing — adding to execution.
– Customers are predominantly on the current release, and almost 60% of customers report it is their data warehouse standard. Microsoft has taken steps in pursuing the LDW with HDInsight (HDP for Windows), PolyBase and Microsoft Cloud (Windows Azure Infrastructure Services can be used to deploy a data warehouse).
– Microsoft is catching up with the other leaders, but a fast-follower market demand still drives the Microsoft road map. However, Microsoft has demonstrated its willingness to be aggressive in certain areas (such as unstructured data via SharePoint search and Azure).
– Organizations report large volumes of data but, in general, Microsoft data warehouses have a small number of users — better examples of scaling warehouses are needed. Customers want easier access to usable metadata for heterogeneous environments.
– Reference customers still report a significant cost advantage, but inquiries indicate that even small price increases do matter and Microsoft needs to maintain its price differentiation from other vendors.