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For example, they could be completely different age groups. So, for the purpose of today's talk, I will stay mostly on the compatibility matching system, allowing us to focus a lot more on the usage of the Mongo DB solution. So this completes the first part of our matching system.
And finally, I will discuss some of the lessons we learned during the Mongo DB transition and some of the new cases we plan to use Mongo DB for.
He's going to share the story about how Mongo DB is helping make matches, how more and more people can fall in love more quickly. With 51 million plus registered members that we have, and 25 million plus visits per month, and more than 1.2 million people that get married on e Harmony since the company was founded 14 years ago by Dr. Our systems store and manage about 200 million plus photos with 15 plus terabytes of data in our photo storage.
Imagine, if you could take the speed of development that Mongo DB brings and bring it to love, we could cut out all that noise in dating and actually just find our soulmates, right? It also manages about four billion plus relationship questionnaires, with 25 plus terabytes of data.
In this particular scenario, Nikki's in the market looking for a toaster on Amazon, for example. Normally, if you meet someone at the bar or at work, a lot of you are, I'm not sure, but, or at a conference like Mongo DB World.
All that really matters in the uni-directional search is to return the toaster that meets the criteria that Nikki had specified. Hopefully, you're looking for your soulmate here in addition to Mongo.
So this CMP application was built on top of the relational database.