In April 2022 MongoDB launched a pay-as-you-go Atlas service on Google Cloud Marketplace. As we said at the time, this offering provides developers with a simplified subscription experience and gives enterprises more freedom in how they run MongoDB on Google Cloud. Since that launch, we've had many hundreds of customers sign up from a wide range of industries including Retail, Automotive, Education, Media & Entertainment, Healthcare, and more.
But that's not all that happened in the past six months.
Developers clearly love to build data-rich applications with MongoDB Atlas, and just as clearly they love to bring that data to life through Google Cloud's data services like Google BigQuery, Vertex AI, and more. To indulge that developer affection for MongoDB + Google Cloud, the two companies have been busy integrating our managed services to help customers make data smarter, more intuitive, and easier to use—wherever developers choose.
Making data smart
Modern applications must be able to automate the process of capturing and processing the data within an application. Combining real-time, operational, and embedded analytics enables a business to influence and automate decision-making for the app and provide real-time insights for the user. This year MongoDB and Google Cloud have combined to deliver best-in-class, application-level analytics.
For example, in the weeks leading up to Google Cloud Next ’22, Google Cloud and MongoDB announced integration of Google BigQuery and MongoDB Atlas, among other Google data announcements. Many enterprises turn to BigQuery for its powerful, simple approach to data warehousing needs, but applying it to data in MongoDB wasn't always straightforward. To make moving and transforming data between Atlas and BigQuery easier, the MongoDB and Google teams worked together to build Dataflow templates that make it simple to package a Dataflow pipeline for deployment. The two companies also announced the integration of Atlas and BigQuery with Vertex AI to bring the power of Google's machine learning/AI expertise to MongoDB data. Developers can access a reference architecture and demo for retail and finance fraud detection scenarios. More integrations will roll out over the coming months.
All of which is great for customers. For years customers like Universe, part of Live Nation, have used MongoDB with Google Cloud services such as Cloud Pub/Sub, Cloud Dataflow, and BigQuery to build data pipelines and more. In early 2022, Forbes, a 100-year old leader in business journalism, turned to MongoDB and Google Cloud to deliver a recommendation engine for its journalists, which uses Google Cloud's machine learning services to make suggestions to appropriate contributors. These and other customers have discovered that MongoDB's data platform and Google's data services are truly better together.
Making data intuitive
All those data smarts don't amount to much if developers can't easily make use of them. Over the past six months, MongoDB and Google Cloud have further partnered to ensure a simple, intuitive developer experience. For example, we've made it incredibly easy to deploy a serverless, MEAN stack (MongoDB, ExpressJS, AngularJS, NodeJS) application with Google Cloud Run (you can read the how-to or watch a video tutorial). Similarly, we've also combined with Vercel to make it simple to build full-stack serverless apps. Serverless means you don't need to worry about any hassle associated with managing infrastructure, and Cloud Run means deployment is also a breeze. More collaboration like this will follow, all with the goal of reducing developer friction and making it easier to use stacks that combine Google and MongoDB products together.
Additionally, we've made it straightforward for developers to extend their MongoDB applications with APIs using Google's Apigee, a platform for managing and securing their APIs. For example, developers increasingly turn to Apigee and MongoDB to help enterprises pull data from legacy systems without needing the cumbersome process of integrating legacy systems. Recently, the MongoDB connector has been released in pre-GA to help developers build their APIs with MongoDB even more quickly.
Developers love these and other integrations. For example, Conrad, a leading European retailer, needed to find a way to build an online B2B marketplace for its own and third-party products. Conrad turned to Atlas and Google Cloud. Together, the companies partnered to help Conrad shift to a microservices-based architecture and delivered a simple, fast, and comprehensive data environment. In like manner, TIM, a global fixed, mobile, cloud, and data center service provider, has leaned on Atlas and Google Cloud to create a dynamic data infrastructure, which has led to a dramatic improvement in customer satisfaction scores.
Making data omnipresent
MongoDB has always put a premium on developer flexibility, which has not only meant unparalleled support for a wide variety of languages, frameworks, etc., but also flexibility in deployment, including multicloud.
Google, for its part, has been a leader in multicloud with Anthos, a platform that enables enterprises to manage GKE clusters and workloads running on virtual machines across environments. It's a way for developers to build once and deploy anywhere, including at the edge, in the data center, or on another cloud, yet with a single cloud control plane. Very cool. Among other benefits, this is a great way for enterprises to meet regulatory and data sovereignty requirements. It is not, however, the only way enterprises can attain that benefit with MongoDB and Google Cloud. As recently announced, MongoDB and Google Cloud have collaborated to give European customers additional choice in where they can securely keep their data, by making MongoDB available on the T-Systems Sovereign Cloud powered by Google Cloud.
Finally, MongoDB and Google Cloud have announced the availability of MongoDB Enterprise Advanced on Google Cloud Marketplace. As much as developers love cloud, sometimes they have the need to self-manage MongoDB. With this listing we together offer that freedom.
Now is the time to give it a try
MongoDB and Google keep giving developers increasingly rich ways to make use of data with operational, application-centered analytics and ML/AI, while also serving up a wide array of choices of where to run those applications. There are many reasons to run MongoDB Atlas on Google Cloud, and one of the easiest is with our self-service, pay-as-you-go listing on Google Cloud Marketplace. Please give it a try and let us know what you think.
Try our self-service, pay-as-you-go listing on Google Cloud Marketplace today.