June 17, 2022
Few companies can credibly claim to understand and work with data as effectively as Google, so when Google Cloud announced this week that MongoDB is the Google Cloud Technology Partner of the Year for Data Management, the award felt particularly meaningful.
But if the honor was just a matter of two leaders in data management slapping each other on the back, it wouldn't be that interesting. No, what makes the award compelling is the customer success that Google Cloud and MongoDB have jointly enabled. We agree with Google Cloud's vision that "True transformation spans the entire business and enables every person to transform," and together have helped customers to achieve this.
Some customers elect to run MongoDB Atlas, our fully managed database service, on Google Cloud because of its broad footprint (Atlas is available in 29 Google Cloud regions), cost/performance benefits, seamless security and scalability, and the recently launched pay-as-you-go option that simplifies subscriptions and can reduce costs. Others have gone further, choosing to take advantage of combining the best services from both companies, like using Google Kubernetes Engine (GKE) or Google Cloud Run for their application tier and MongoDB for their data tier. And some choose Google Cloud so they can tie into Google services that are tightly integrated with MongoDB, including BigQuery, Datastream, and Dataproc.
A few examples that show the ambition and innovation MongoDB and Google Cloud customers are bringing to their products:
Precognitive combines device intelligence, advanced behavioral analytics, and a real-time decision engine to accurately detect and prevent fraud for online businesses. Using Google Cloud Bigtable as their data store for behavioral and device data, and MongoDB as the data store for everything else, Precognitive is able to capture and analyze vast amounts of data from around the world, in near real time, to combat fraud. Read our full story on how Precognitive uses MongoDB Atlas.
Forbes, the world's largest business media brand, reaches more than 140 million people worldwide every month across a number of online and offline channels. The company needed to innovate its way through the global COVID-19 pandemic and turned to MongoDB Atlas running on Google Cloud to enable dramatically better agility. Among other initiatives, the publishing giant married MongoDB's flexible data schema with Google Cloud’s machine learning services to deliver a trending story recommendation engine for journalists. Read our full story on Forbes’ migration to Atlas — and the successes of that move.
One of the things we love about working with Google Cloud is the company's pragmatic approach to solving customer problems. Customers tend to choose a predominant cloud vendor upon which to build the majority of their applications, and Google Cloud often serves this role. At Plaid, which helps retailers decipher the complexities of consumer behavior, the company chose to migrate its legacy databases to MongoDB Atlas running on Google Cloud, allowing it to tap into Google Kubernetes Engine, Google Cloud Engine (GCE), Cloud BigTable, and BigQuery. But Plaid also needed to ensure it could run across multiple clouds, which Google Cloud enables with its Anthos service. MongoDB and Google Cloud, working together, deliver that multi-cloud experience for customers. Read our case study on Plaid, MongoDB, and Google Cloud.
If you’re ready to experience the fruits of the MongoDB and Google Cloud partnership, take a look at MongoDB Atlas in the Google console. You can get started for free.
Read more stories about MongoDB and Google Cloud customers doing great things: