AWS Named 'Leader' in Data Management Solutions for Analytics
Research firm Gartner Inc. is out with a new Magic Quadrant report for Data Management Solutions for Analytics, in which the Amazon Web Services Inc. (AWS) cloud was named a "leader."
Gartner's Magic Quadrant reports rank vendors according to their "ability to execute" and "completeness of vision," placing companies that excel on both indices in the "leaders" category.
In its latest "Magic Quadrant for Data Management Solutions for Analytics" (DMSA) report, AWS was joined by Oracle, Teradata, Microsoft, IBM and SAP in the leaders quadrant. All of those companies graded better than AWS on the "completeness of vision" scale, while on the "ability to execute" scale, AWS was ahead of SAP.
As far as the category of research, Gartner said the DMSA moniker refers to "a complete software system that supports and manages data in one or many file management systems (most commonly a database or multiple databases)."
In the report, cloud vendors -- where AWS is the undisputed leader in public cloud computing services -- figure prominently and are "gaining traction," according to Gartner.
"Expectations are now turning to the cloud as an alternative deployment option, because of its flexibility, agility and operational pricing models," Gartner said. "As the use of a combined cloud and on-premises hybrid is quickly becoming the norm, so organizations expect vendors to support them in enabling such deployments."
Gartner said AWS is helping to lead this trend. "Although the Leaders quadrant this year is largely populated with large traditional vendors that are relatively close to each other, we also see a new entrant in AWS," the research firm said. "AWS has continued to focus on market execution, while also progressing its vision in addressing a broader set of use cases by combining and delivering multiple services to the market."
The company indicated that AWS rules the cloud space with offerings such as: Amazon Redshift, a data warehouse service; Amazon Simple Storage Service (S3); Amazon Elastic MapReduce (EMR); and Amazon Athena, a serverless computing, metered query engine for data stored in Amazon S3.
"AWS is the dominant cloud vendor in this market by a significant margin, with only Microsoft Azure even close in terms of market share and presence," Gartner said in detailing the strengths of the AWS offering. "This dominance provides increasing network effects for all of its services, because the sources of data for a DMSA use case are more likely to reside in an AWS service than that of any other cloud vendor."
Other listed strengths of AWS include its several different services that can be found to provide a best fit for many DMSA use cases, along with its low-cost, pay-as-you-go pricing.
As far as "cautions" about AWS, Gartner cited: monolithic storage and compute sizes; being a cloud-only vendor; and integration issues.
"Amazon Redshift is available in configurations that include a specific amount of compute and storage," Gartner said about the first caution concerning monolithic storage sizes. "Customers cannot easily scale these resources independently without doing a resizing exercise, which takes several hours while data is redistributed. This can lead to excess capacity and a more cumbersome process to upgrade Redshift instances."
Meanwhile, being a cloud-only vendor leaves it out of contention in enterprises that need hybrid environments that also span on-premises implementations.
The final caution indicates that AWS's many options that provide the "best fit" advantage can also work against the company. "By offering multiple independent services, AWS can reduce the complexity of each individual service, but this can increase the work required to integrate the separate services," Gartner said. "At this point, integration requirements must be addressed by customers, so the proliferation of service instances can lead to significant integration issues."
In its concluding market overview, Gartner said: "The DMSA market continues to evolve. Customers now expect solutions that support all types of data for analytics and that take a coordinated approach. This demands different types of integrated solution and an interoperable services tier for managing and delivering data. Data lakes and the ability to manage streaming data are now being pursued by a growing number of organizations."
About the Author
David Ramel is an editor and writer for Converge360.