We Shouldn’t Be Surprised MongoDB Dropped Off This Year’s Gartner Magic Quadrant

November 29, 2017

Contributed by Ken Rugg

The 2017 Gartner Magic Quadrant for Operational Database Management Systems (OPDBMS) packed a couple of surprises. High-flying NoSQL vendor MongoDB was gone. Plenty of other vendors had disappeared too. In fact, there were only 11 vendors included, down from 31 in the 2015 report—a 65% decrease. Still recognized in the report was EnterpriseDB (EDB), but that was no surprise. The focus of the Magic Quadrant for OPDBMS this year is on the upper tier of the pyramid of database solution providers, said one Gartner analyst during a presentation about this year’s report at the Gartner Symposium/ITxpo in Barcelona earlier this month.

Gartner 2018: Get insight into the trends shaping the Operational Database Management Systems industry.

So what is happening? The answer is that the database industry has undergone another cycle of expansion of new technologies followed by consolidation with existing ones.

With the flood of ever expanding voice, mobile, web, and Internet of Things data came greater demands for storing, managing, and relating these new kinds of data. The last few years saw a great deal of excitement with new vendors entering the market with dynamic new functionality to address ways to handle these unstructured data needs. And, as with previous periods of innovation in the database market there was a great deal of hype around the potential impact these new entrants would have on the established database vendors.

The new NoSQL vendors were positioned as better reflecting the needs of enterprises seeking to become more agile and innovative in the digital business era. Some even said they would become replacements for relational databases. When object oriented and XML databases came along in the 2000s they were also positioned as a significant threat to the leading relational database vendors. I had a front row seat to this before as Vice President, Product Development and Chief Technology Officer of Object Design/eXcelon Inc. It didn’t happen then, and it didn’t happen now.

The reality is that this new wave of innovation that NoSQL and other new technology vendors provide has been absorbed into mainstream relational databases just as it was in previous waves. Relational databases have a greater capacity for extension to provide the capabilities of NoSQL solutions than NoSQL solutions have for adding relational capabilities. And, since customers are looking for more robust solutions to leverage resources across more workloads, it should come as no surprise the number of vendors still recognized in the Gartner Magic Quadrant has declined. To view the 2017 Gartner Magic Quadrant report, click here.

This does not mean the new functionality is no longer relevant, but rather that the database market as a whole is maturing and the market for fit-for-purpose solutions is shrinking. As Gartner wrote, “The explosive growth of features, and the vendors emerging to implement them, continue to slow. The features that initiated the expansion, such as storing new data types, geographically distributed storage, cloud and flexible data consistency models, have become common; today, nearly every established or emerging DBMS vendor supports them to some degree. In 2016, the OPDBMS market shifted from a phase of rapid innovation to a phase of maturing products and capabilities. This has continued into 2017.”[1]

Gartner has gone so far as to recommend, in a July 2017 report, State of the Operational DBMS Market, 2017, that IT leaders who are modernizing or evolving their DBMS strategy “should evaluate the modern data management capabilities (i.e., multi-model, distributed, scale-out, eventual consistency) in existing and well-understood products, especially for distributed use cases, before adopting new DBMS products.”[2]

The modern data management capabilities of relational databases have kept up with changing demands:

  • Relational databases responded to the need for handling disparate data streams with multi-model capabilities for combining structured, unstructured, and semistructured data within a familiar relational environment.
  • As demands for deeper insight into customer behavior and operational efficiencies surged, relational systems incorporated complementary technologies to integrate transactional systems and Big Data solutions for more performant and cost-effective analytic capabilities.
  • As the need to combine data in vast infrastructures with multiple solution vendors emerged, relational systems introduced new technology that eased interoperability of heterogeneous data sources to form more cohesive data architectures.
  • As developers looked to new styles of programming that required native JSON support and RESTful APIs, relational databases like Postgres responded by adding those features.

The edge cases that required a specific NoSQL solution like MongoDB became fewer. 

What’s more, demand for relational technology shows no signs of letting up. According to Gartner, “through 2020, relational technology will continue to be used for at least 70% of new applications and projects.”[3] Additionally, Gartner wrote: “While there remains a need for best-of-fit solutions, the advantages of a single vendor from a cost and skills perspective many times outweigh the benefits from best-of-fit. This is just beginning in 2017 and will grow over the next several years.”[4]

Relational technologies are also a cornerstone of the largest strategic technology shift underway in IT—the move into the cloud. According to Gartner, “for 2017, cloud has moved to center stage. Extremely large companies, defined as having over 10,000 employees and several billion in annual revenue, are building roadmaps to be ‘all in’ on public cloud infrastructure in three to five years.”[5]

Databases that fail to provide organizations with what they need, full-featured solutions with modern capabilities, will fall behind. Or, as MongoDB has done, drop to the bottom tiers of the market pyramid to become solutions for edge cases no longer recognized among elite vendors.                                                                  

So, it is no surprise that EDB continues, for the fifth consecutive year, to be recognized among elite database vendors in Gartner Magic Quadrant for OPDBMS. The power of EDB Postgres comes from its technologies and capabilities that offer interoperability, flexibility, and greater control for enterprise customers. The EDB Postgres Platform now rivals traditional vendor offerings for features and performance; yet as an open source-based provider, offers dramatic cost savings and greater flexibility. EDB is now the only open source-based relational database vendor in the Gartner Magic Quadrant. 

With shifting data and infrastructure demands, EDB Postgres has evolved with multi-model capabilities, cross-platform integration support, and greater interoperability. As customers began moving toward new DevOps oriented processes, EDB introduced Container support for Docker, Kubernetes, OpenShift, and Cloud Foundry. With more development and production workloads moving into cloud environments, EDB introduced the EDB Postgres Ark DBaaS (database-as-a-service) framework to simplify the process of provisioning and managing Postgres clusters in public, private, and hybrid clouds.

What’s more, EDB offers something that traditional vendors cannot afford to—business arrangements that give customers broad flexibility in how they deploy EDB Postgres, cost-effectively, whether on-premises or in the cloud. EDB customers can move their EDB Postgres subscription licenses from on premises to virtualized, private cloud or public cloud environments seamlessly with no additional cost or licensing requirements.

As the database industry landscape continues to evolve and mature, EDB will continue to be the open source based leader for organizations seeking interoperability, flexibility, and greater control as they succeed in their digital initiatives. With no surprises.

Kenneth Rugg is Chief Product and Strategy Officer at EDB.

 

[1] Gartner Magic Quadrant for Operational Database Management Systems, by Nick Heudecker, Donald Feinberg, Merv Adrian, published November 2, 2017

[2] State of the Operational DBMS Market, 2017, by Donald Feinberg, Merv Adrian, and Nick Heudecker, published July 25, 2017

[3] Gartner Magic Quadrant for Operational Database Management Systems, by Nick Heudecker, Donald Feinberg, Merv Adrian, published November 2, 2017

[4] Ibid.

[5] Ibid.

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.

 

Share this

Relevant Blogs

The Power of Postgres for AI Enterprise Workloads

Artificial intelligence is a popular topic right now across organizations and industries. And it’s more than just a hot buzzword. According to Gartner’s recent research, 55% of organizations are in...
April 16, 2024

The Three Hidden Costs of Legacy Databases

No matter what industry you’re in, IT cost escalation is one of the top challenges faced by technical leaders  today. When an organization relies on legacy databases, hidden costs can...
April 13, 2024

More Blogs