{"id":4961,"date":"2019-04-23T10:30:24","date_gmt":"2019-04-23T10:30:24","guid":{"rendered":"http:\/\/www.odbms.org\/blog\/?p=4961"},"modified":"2019-04-24T11:53:29","modified_gmt":"2019-04-24T11:53:29","slug":"on-the-database-market-interview-with-merv-adrian","status":"publish","type":"post","link":"https:\/\/www.odbms.org\/blog\/2019\/04\/on-the-database-market-interview-with-merv-adrian\/","title":{"rendered":"On the Database Market. Interview with Merv Adrian"},"content":{"rendered":"<blockquote><p><strong>&#8220;Anyone who expects to have some of their work in the cloud (e.g. just about everyone) will want to consider the offerings of the cloud platform provider in any shortlist they put together for new projects. These vendors have the resources to challenge anyone already in the market.&#8221;&#8211;\u00a0Merv Adrian.<\/strong><\/p><\/blockquote>\n<p>I have interviewed<strong> Merv Adrian, <\/strong><em>Research VP, Data &amp; Analytics at Gartner<\/em>. We talked about the\u00a0the database market, the Cloud and the\u00a02018 Gartner Magic Quadrant for Operational Database Management Systems.<\/p>\n<p>RVZ<\/p>\n<p><strong>Q1. Looking Back at 2018, how has the database market changed?<\/strong><\/p>\n<p><strong>Merv Adrian<\/strong>: At a high level, much is similar to the prior year. The <a onclick=\"javascript:pageTracker._trackPageview('\/outgoing\/en.wikipedia.org\/wiki\/Database');\"  href=\"https:\/\/en.wikipedia.org\/wiki\/Database\" target=\"_blank\">DBMS<\/a> market returned to double digit growth in 2017 (12.7% year over year in Gartner\u2019s estimate) to $38.8 billion. Over 73% of that growth was attributable to two vendors: Amazon Web Services and Microsoft, reflecting the enormous shift to new spending going to <a onclick=\"javascript:pageTracker._trackPageview('\/outgoing\/en.wikipedia.org\/wiki\/Cloud_computing');\"  href=\"https:\/\/en.wikipedia.org\/wiki\/Cloud_computing\" target=\"_blank\">cloud<\/a> and <a onclick=\"javascript:pageTracker._trackPageview('\/outgoing\/en.wikipedia.org\/wiki\/Cloud_computing#Hybrid_cloud');\"  href=\"https:\/\/en.wikipedia.org\/wiki\/Cloud_computing#Hybrid_cloud\" target=\"_blank\">hybrid-capable<\/a> offerings. In 2018, the trend grew, and the erosion of share for vendors like Oracle, IBM and Teradata continued. We don\u2019t have our 2018 data completed yet, but I suspect we will see a similar ballpark for overall growth, with the same players up and down as last year. Competition from Chinese cloud vendors, such as Alibaba Cloud and Tencent, is emerging, especially outside North America.<\/p>\n<p><strong>Q2. What most surprised you?<\/strong><\/p>\n<p><strong>Merv Adrian<\/strong>: The strength of <a onclick=\"javascript:pageTracker._trackPageview('\/outgoing\/en.wikipedia.org\/wiki\/Apache_Hadoop');\"  href=\"https:\/\/en.wikipedia.org\/wiki\/Apache_Hadoop\" target=\"_blank\">Hadoop<\/a>. Even before the merger, both Cloudera and Hortonworks continued steady growth, with Hadoop as a cohort outpacing all other nonrelational DBMS activity from a revenue perspective. With the merger, Cloudera becomes the 7th largest vendor by revenue and usage and intentions data suggest continued growth in the year ahead.<\/p>\n<p><strong>Q3. Is the distinction between relational and nonrelational database management still relevant?<\/strong><\/p>\n<p><strong>Merv Adrian<\/strong>: Yes, but it\u2019s less important than the cloud. As established vendors refresh and extend product offerings that build on their core strengths and capabilities to provide <a onclick=\"javascript:pageTracker._trackPageview('\/outgoing\/en.wikipedia.org\/wiki\/Multi-model_database');\"  href=\"https:\/\/en.wikipedia.org\/wiki\/Multi-model_database\" target=\"_blank\">multimodel DBMS<\/a> and\/or or broad portfolios of both, the \u201carchitecture\u201d battle will ramp up. New disruptive players and existing cloud platform providers will have to battle established vendors where they are strong \u2013 so for <a onclick=\"javascript:pageTracker._trackPageview('\/outgoing\/www.gartner.com\/reviews\/market\/data-warehouse-solutions');\"  href=\"https:\/\/www.gartner.com\/reviews\/market\/data-warehouse-solutions\" target=\"_blank\">DMSA<\/a> players like Snowflake will have more competition and on the <a onclick=\"javascript:pageTracker._trackPageview('\/outgoing\/www.gartner.com\/reviews\/market\/operational-dbms');\"  href=\"https:\/\/www.gartner.com\/reviews\/market\/operational-dbms\" target=\"_blank\">OPDBMS<\/a> side, relational and nonrelational providers alike \u2013 such as EnterpriseDB,\u00a0MongoDB, and Datastax &#8211; will battle more for a cloud foothold than a \u201cnonrelational\u201d one.<br \/>\nSpecific nonrelational plays like <a onclick=\"javascript:pageTracker._trackPageview('\/outgoing\/www.gartner.com\/en\/newsroom\/press-releases\/2019-02-18-gartner-identifies-top-10-data-and-analytics-technolo');\"  href=\"https:\/\/www.gartner.com\/en\/newsroom\/press-releases\/2019-02-18-gartner-identifies-top-10-data-and-analytics-technolo\" target=\"_blank\">Graph<\/a>, <a onclick=\"javascript:pageTracker._trackPageview('\/outgoing\/en.wikipedia.org\/wiki\/Time_series_database');\"  href=\"https:\/\/en.wikipedia.org\/wiki\/Time_series_database\" target=\"_blank\">Time Series<\/a>, and <a onclick=\"javascript:pageTracker._trackPageview('\/outgoing\/aws.amazon.com\/qldb\/faqs\/');\"  href=\"https:\/\/aws.amazon.com\/qldb\/faqs\/\" target=\"_blank\">ledger DBMSs<\/a> will be more disruptive than the general \u201cnonrelational\u201d category.<\/p>\n<p><strong>Q4. Artificial intelligence is moving from sci-fi to the mainstream. What is the impact on the database market?<\/strong><\/p>\n<p><strong>Merv Adrian<\/strong>: Vendors are struggling to make the case that much of the heavy lifting should move to their DBMS layer with in-database processing. Although it\u2019s intuitive, it represents a different buyer base, with different needs for design, tools, expertise and operational support. They have a lot of work to do.<\/p>\n<p><strong>Q5. Recently Google announced <a onclick=\"javascript:pageTracker._trackPageview('\/outgoing\/cloud.google.com\/bigquery\/docs\/bigqueryml-intro');\"  href=\"https:\/\/cloud.google.com\/bigquery\/docs\/bigqueryml-intro\" target=\"_blank\">BigQuery ML<\/a>. Machine Learning in the (Cloud) Database. What are the pros and cons?<\/strong><\/p>\n<p><strong>Merv Adrian<\/strong>: See the above answer. Google has many strong offerings in the space \u2013 putting them together coherently is as much of a challenge for them as anyone else, but they have considerable assets, a revamped executive team under the leadership of <a onclick=\"javascript:pageTracker._trackPageview('\/outgoing\/en.wikipedia.org\/wiki\/Thomas_Kurian');\"  href=\"https:\/\/en.wikipedia.org\/wiki\/Thomas_Kurian\" target=\"_blank\">Thomas Kurian<\/a>, and are entering what is likely to be a strong growth phase for their overall DBMS business. They are clearly a candidate to be included in planning and testing.<\/p>\n<p><strong>Q6. You recently published the 2018 Gartner Magic Quadrant for Operational Database Management Systems. In a nutshell. what are your main insights?<\/strong><\/p>\n<p><strong>Merv Adrian<\/strong>: Much of that is included in the first answer above. What I didn\u2019t say there is that the degree of disruption varies between the Operational and DMSA wings of the market, even though most of the players are the same. Most important, specialists are going to be less relevant in the big picture as the converged model of application design and multimodel DBMSs make it harder to thrive in a niche.<\/p>\n<p><strong>Q7. To qualify for inclusion in this Magic Quadrant, vendors must have had to support two of the following four use cases: traditional transactions, distributed variable data, operational analytical convergence and event processing or data in motion. What is the rational beyond this inclusion choice? <\/strong><\/p>\n<p><strong>Merv Adrian<\/strong>: The rationale is to offer our clients the offerings with the broadest capabilities. We can\u2019t cover all possibilities in depth, so we attempt to reach as many as we can within the constraints we design to map to our capacity to deliver. We call out specialists in various other research offerings such as Other Vendors to Consider, Cool Vendor, Hype Cycle and other documents, and pieces specific to categories where client inquiry makes it clear we need to have a published point of view.<\/p>\n<p><strong>Q8. How is the Cloud changing the overall database market?<\/strong><\/p>\n<p><strong>Merv Adrian<\/strong>: Massively. In addition to functional and architectural disruption, it\u2019s changing pricing, support, release frequency, and user skills and organizational models. The future value of data center skills, container technology, multicloud and hybrid challenges and more are hot topics.<\/p>\n<p><strong>Q9. In your Quadrant you listed Amazon Web Services, Alibaba Cloud and Google. These are no pure database vendors, strictly speaking. What role do they play in the overall Operational DBMS market?<\/strong><\/p>\n<p><strong>Merv Adrian<\/strong>: Anyone who expects to have some of their work in the cloud (e.g. just about everyone) will want to consider the offerings of the cloud platform provider in any shortlist they put together for new projects. These vendors have the resources to challenge anyone already in the market. And their deep pockets, and the availability of open source versions of every DBMS technology type that they can use &#8211; including creating their own versions of with optimizations for their stack and pre-built integrations to upstream and downstream technologies required for delivery \u2013 makes them formidable.<\/p>\n<p><strong>Q10. What are the main data management challenges and opportunities in 2019?<\/strong><\/p>\n<p><strong>Merv Adrian<\/strong>: Avoiding silver bullet solutions, sticking to sound architectural principles based on understanding real business needs, and leveraging emerging ideas without getting caught in dead end plays. Pretty much the same as always. The details change, but sound design and a focus on outcomes remain the way forward.<\/p>\n<p><strong>Qx Anything else you wish to add?<\/strong><\/p>\n<p><strong>Merv Adrian<\/strong>: Fasten your seat belt. It\u2019s going to be a bumpy ride.<\/p>\n<p>&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/p>\n<p><a onclick=\"javascript:pageTracker._trackPageview('\/outgoing\/www.odbms.org\/blog\/wp-content\/uploads\/2019\/04\/Merv.jpeg');\"  href=\"http:\/\/www.odbms.org\/blog\/wp-content\/uploads\/2019\/04\/Merv.jpeg\"><img decoding=\"async\" loading=\"lazy\" class=\"alignnone  wp-image-4991\" src=\"http:\/\/www.odbms.org\/blog\/wp-content\/uploads\/2019\/04\/Merv.jpeg\" alt=\"Merv\" width=\"136\" height=\"136\" srcset=\"https:\/\/www.odbms.org\/blog\/wp-content\/uploads\/2019\/04\/Merv.jpeg 225w, https:\/\/www.odbms.org\/blog\/wp-content\/uploads\/2019\/04\/Merv-150x150.jpeg 150w\" sizes=\"(max-width: 136px) 100vw, 136px\" \/><\/a><\/p>\n<p><strong>Merv Adrian<\/strong>, <em>Research VP, Data &amp; Analytics. Gartner<\/em><\/p>\n<p><em> Merv Adrian is an Analyst on the Data Management team following operational DBMS, Apache Hadoop, Spark, nonrelational DBMS and adjacent technologies. Mr. Adrian also tracks the increasing impact of open source on data management software and monitors the changing requirements for data security in information platforms.<br \/>\n<\/em><\/p>\n<p><strong>Resources<\/strong><\/p>\n<p><strong>&#8211; \u00a0<a onclick=\"javascript:pageTracker._trackPageview('\/outgoing\/www.gartner.com\/doc\/3891967\/magic-quadrant-operational-database-management');\"  href=\"https:\/\/www.gartner.com\/doc\/3891967\/magic-quadrant-operational-database-management\" target=\"_blank\">2018 Gartner Magic Quadrant for Operational Database Management Systems<\/a><\/strong><\/p>\n<p>&#8211; \u00a0<strong><a onclick=\"javascript:pageTracker._trackPageview('\/outgoing\/www.gartner.com\/doc\/3898487\/magic-quadrant-data-management-solutions');\"  href=\"https:\/\/www.gartner.com\/doc\/3898487\/magic-quadrant-data-management-solutions\" target=\"_blank\">2019 Gartner\u00a0Magic Quadrant for Data Management Solutions for Analytics<\/a><\/strong><\/p>\n<p>&#8211;\u00a0<strong><a onclick=\"javascript:pageTracker._trackPageview('\/outgoing\/www.gartner.com\/doc\/reprints?id=1-65WC0O1&amp;ct=190128&amp;st=sb');\"  href=\"https:\/\/www.gartner.com\/doc\/reprints?id=1-65WC0O1&amp;ct=190128&amp;st=sb\" target=\"_blank\">\u00a02019 Gartner Magic Quadrant for Data Science and Machine Learning Platforms<\/a><\/strong><\/p>\n<div class=\"share\">\u00a0<strong>Related Posts<\/strong><\/div>\n<div class=\"share\"><\/div>\n<div class=\"share\">&#8211;\u00a0<a onclick=\"javascript:pageTracker._trackPageview('\/outgoing\/www.odbms.org\/2019\/04\/on-the-technical-challenges-posed-by-the-5g-revolution-qa-with-dheeraj-remella\/');\" title=\"On the technical challenges posed by the 5G revolution. 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I have interviewed Merv Adrian, Research [&hellip;]<!-- AddThis Advanced Settings generic via filter on get_the_excerpt --><!-- AddThis Share Buttons generic via filter on get_the_excerpt --><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[1],"tags":[1442,29,1441,97,105,142,1445,178,1018,239,258,907,1440,383,391,1444,449,1214,1443,569],"_links":{"self":[{"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/posts\/4961"}],"collection":[{"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/comments?post=4961"}],"version-history":[{"count":8,"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/posts\/4961\/revisions"}],"predecessor-version":[{"id":4993,"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/posts\/4961\/revisions\/4993"}],"wp:attachment":[{"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/media?parent=4961"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/categories?post=4961"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/tags?post=4961"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}