Three Takeaways from Gartner’s 2019 Magic Quadrant for Data Management Solutions for Analytics
The Magic Quadrant (MQ) is an established, widely-referenced series of research reports published by the analyst firm Gartner, Inc. The January 2019 “Magic Quadrant for Data Management Solutions for Analytics” provides valuable insights into the status, direction, and players in the DMSA market. A total of 19 vendors satisfied Gartner’s extensive inclusion criteria for insertion in this year’s MQ DMSA report.
In this blog, we share our takeaways as they relate to the DMSA market trends.
Cloudera is positioned furthest for “Completeness of Vision.” Gartner states, “The criteria for Completeness of Vision assess a vendor’s ability to understand the functional capabilities needed to support DMSA environments. Also, its ability to develop a product strategy that meets the market’s requirements, to comprehend overall market trends, and to influence or lead the market when necessary. A visionary leadership role is necessary for long-term viability of both products and companies. A vendor’s vision may be demonstrated — and improved — by a willingness to extend its influence throughout the market by working with independent third-party application software vendors that deliver additional functionality for its DMSA environment. A successful vendor will be able not only to understand the competitive landscape for DMSAs, but also to shape its future.”
Cloudera’s 3 Key Takeaways
We recognize the following takeaways from Gartner’s 2019 MQ DMSA:
1. “Disruption slows as cloud and nonrelational technology take their place beside traditional approaches, the leaders extend their lead, and distributed data approaches solidify their place as a best practice for DMSA.” Cloudera believes disruption persists around multi-cloud.
Established, mature technologies represent an integral part of DMSA. However, we believe disruption persists around multi-cloud approaches. Why multi-cloud? Because it doesn’t lead to vendor lock-in; diverse needs across departments may require alternative clouds and differentiated capabilities. Moving processing to data creates the need for multi-cloud.
Only Cloudera provides multi-cloud choice and hybrid cloud flexibility – powered by cloud-native technologies – for a public cloud experience across public and private clouds, significantly simplifying IT operations and governance. Cloudera delivers ubiquitous enterprise-wide control spanning any cloud for better SLA performance, simpler regulatory compliance, and faster response to business challenges and opportunities.
2. “Best-fit and platform combine in the cloud “
According to the report, “while the cloud is characterized by best-fit point solutions, the cloud ecosystem and infrastructure can serve as the basis for a platform play. This applies to native CSP product offerings as well as point solutions from independent software vendors.”
Larger vendors with extensive resources and a broad portfolio that enable a platform approach are beginning to confront the best-fit approaches promoted by smaller vendors.
Cloudera provides a unified platform with multiple data apps and tools, big data management, hybrid cloud deployment flexibility, admin tools for platform provisioning and control, and a shared data experience for centralized security, governance, and metadata management. Concurrently, it enables organizations to deploy specific workloads – such as modern data warehouse, data science, and ML – with the capability to expand to additional workloads. All this while the platform serves as the core foundation providing metadata and governance capabilities across these workloads. It accomplishes this while avoiding issues around interoperability among the workloads.
3. Expansion beyond core data management
“Small and large vendors alike are starting to expand their product capabilities to integrate metadata management, data integration, governance, ML for optimization and performance management, and other aspects required for long-term strategic success.
Cloudera champions powerful data analytics anywhere, empowering people with robust data analytics at scale – streaming, SQL, transactional, data science, machine learning and AI – with an experience that improves individual and team innovation and productivity. Cloudera recognizes that machine learning is built on data management; integrated data, workflows, metadata, security, and governance. Cloudera advocates a unified platform that breaks down silos by bringing data management and data science together.
To learn more about Data Management Solutions for Analytics, Gartner subscribers can download Gartner’s report here.
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
About the Author:
Lakshmi Randall is Director of Product Marketing at Cloudera, the enterprise data cloud company. Previously, she was a Research Director at Gartner (News – Alert) covering Data Warehousing, Data Integration, Big Data, Information Management, and Analytics practices. To learn more, visit www.cloudera.com or follow the company @cloudera or the author on Twitter (News – Alert): @LakshmiLJ
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