New Gartner Magic Quadrant for Operational Database Management Systems. Interview with Nick Heudecker
“It is too soon to call the operational DBMS market a commodity market, but it’s easy to see a future where that is the case.”–Nick Heudecker.
I have interviewed Nick Heudecker, Research Director on Gartner’s Data & Analytics team.
The main topic of the interview is the new Magic Quadrant for Operational Database Management Systems.
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Q1. You have published the new Magic Quadrant for Operational Database Management Systems (*). How do you define the operational database management system market?
Nick Heudecker: We define a DBMS as a complete software system used to define, create, manage, update and query a database. DBMSs provide interfaces to independent programs and tools that both support and govern the performance of a variety of concurrent workload types. There is no presupposition that DBMSs must support the relational model or that they must support the full set of possible data types in use today. OPDBMSs must include functionality to support backup and recovery, and have some form of transaction durability — although the atomicity, consistency, isolation and durability model is not a requirement. OPDBMSs may support multiple delivery models, such as stand-alone DBMS software, certified configurations, cloud (public and private) images or versions, and database appliances.
Q2. Can you explain the methodology you used for this new Magic Quadrant?
Nick Heudecker: The methodologies for several Gartner methodologies are public. The Magic Quadrant methodology can be found here.
We use a number of data sources when we’re creating the Magic Quadrant for Operational Database Management Systems.
We survey vendor reference customers and include data from our interactions with Gartner clients. We also consider earlier information and any news about vendors’ products, customers and finances that came to light during the time frame for our analysis.
Once we have the data, we score vendors across the various dimensions of Completeness of Vision and Ability to Execute.
One thing that’s important to note is Magic Quadrants are relative assessments of vendors in a market. We couldn’t have one vendor on an MQ because it would be right in the middle – there’s nothing to compare it to.
Q3. Why were there no Visionaries this year?
Nick Heudecker: We determined there was an overall lack of vision in the market. After a few years of rapid feature expansion, the focus has shifted to operational excellence and execution. Even Leaders shifted to the left on vision, but are still placed in the Leaders quadrant based on their vision for the development of hybrid database management, hardware optimization and integration, emerging deployment models such as containerization, as well as vertical features.
Q4. Were you surprised by the analysis and some of the results you obtained?
Nick Heudecker: The lack of overall vision in the market struck us the most. Other than in a few notable cases, we received largely the same story from most vendors. The explosion of features, and the vendors emerging to implement them, has slowed. 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 these features to some degree. The OPDBMS market has shifted from a phase of rapid innovation to a phase of maturing products and capabilities.
Q5. Do you believe the “NoSQL” label will continue to distinguish DBMSs?
Nick Heudecker: If you look at the entire operational DBMS space, there’s already a great deal of convergence between NoSQL vendors, as well as between NoSQL and traditionally relational vendors. Nearly every vendor, nonrelational and relational, supports multiple data types, like JSON documents, graph or wide-column. NoSQL vendors are adding SQL: MongoDB’s BI Connector and Couchbase’s N1QL are good, if diverse, examples. They’re also adding things like schema management and data validation capabilities.
On the relational side, they’re adding horizontal scaling options and alternative consistency models, as well as modern APIs. And everyone either has or is adding in-memory and cloud capabilities.
It is too soon to call the operational DBMS market a commodity market, but it’s easy to see a future where that is the case.
Q6. What are the other “Vendors to Consider”?
Nick Heudecker: The other vendors to consider are vendors that did not meet the inclusion requirements for the Magic Quadrant. Usually this is because they missed our minimum revenue requirements, but that doesn’t mean they don’t have compelling products.
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Nick Heudecker is a Research Director on Gartner’s Data & Analytics team. His coverage includes data management technologies and practices.
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– Complimentary Gartner Research: 100 Data and Analytics Predictions Through 2020. Get exclusive access to Gartner’s top 100 data and analytics predictions through 2020. Plus access other relevant Gartner research including Magic Quadrant reports for database and data warehouse solutions, and the market guide for in-memory computing (LINK to MemSQL web site – registration required).
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