Date -2017-11-09 Location - BEDFORD, Mass. With its placement in the most recent report, EDB has now been recognized in Gartner’s Magic Quadrant for OPDBMS for five consecutive years, every year since Gartner began publishing them in 2013. EDB sees this consistency as particularly noteworthy as the number of vendors included in the report has dropped dramatically—by 65% in the past two years from 31 in 2015 to only 11 in 2017.
With its leadership in the Postgres community, EDB is now the only solely open source relational database vendor included the Magic Quadrant. “We believe open source alternatives like EDB Postgres now rival traditional vendor offerings for features and performance but provide far greater flexibility and cost savings,” said Ed Boyajian, CEO and President, EDB. “Our customers recognize this value as a key component enabling strategic initiatives for greater agility through DevOps and better customer relations through digital transformation.” Eighty-eight of the Fortune 500 and 241 of the Forbes Global 2000 now use EDB Postgres as part of their core data fabric infrastructures.
The EDB Postgres™ Platform is an open source-based relational data management platform that integrates with legacy systems and emerging Big Data solutions. It offers enterprise capabilities necessary to manage multi-model data and deploy rapidly across multiple environments, from public clouds like AWS and Google to private and hybrid clouds and in traditional modes on-premises. The EDB Postgres Ark™ database-as-a-service (DBaaS) framework, in particular, gives IT broader powers to quickly provision and control environments for development and production.
We feel the consolidation in vendors represented in the 2017 OPDBMS Gartner Magic Quadrant reflects dramatic changes under way in the operational database market. According to Gartner: “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]
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[1] Gartner Magic Quadrant for Operational Database Management Systems, by Nick Heudecker, Donald Feinberg, Merv Adrian, published November 2, 2017.
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