Percona and VividCortex Collaborate to Provide Leading Database Solutions

Posted by Alex Slotnick on Dec 3, 2015 2:38:40 PM


We're thrilled to announce VividCortex's new partnership with Percona -- the only company that delivers enterprise-class solutions for both MySQL and MongoDB across traditional and cloud-based platforms. As part of the partnership, Percona will resell VividCortex as a value-added monitoring solution, and Percona's own support technicians and managed service administrators will have VividCortex at their fingertips, to assist in serving and optimizing their customers’ applications.  

Including VividCortex as part of Percona's services will provide enterprise users of Percona Server for MySQL and Percona Server for MongoDB with the safest, most streamlined, and precise method for monitoring high performance data systems. Percona customers who opt for VividCortex will enjoy improved visibility and greater insights into their database performance than ever before. And because VividCortex is cloud-based, its implementation for Percona customers will be smooth and effortless, requiring no additional equipment or software; VividCortex auto-discovers with a single line of code.

Peter Zaitsev, Percona's Co-founder and CEO, had this to say:

"VividCortex is perfectly aligned with our goal of enabling organizations of all sizes to affordably deploy and maintain highly scalable, high performance database environments. The solution allows DBAs to achieve optimal execution while eliminating issues faster and more effectively – all without a major impact on budgets and resources."

VividCortex monitors every query, every process, and every metric in industry-leading 1-second granularity, with no hinderance to the measured system itself. For high performance enviornments, the collaboration between Percona and VividCortex now offers the most cost-effective way to manage databases systems. By working with Percona, VividCortex looks forward to optimizing performance in more systems and for more users than every before.   

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