Powerful Generative AI Innovation Accelerates Discovery of New Molecules
Since 2018, MongoDB and Google Cloud have collaborated to revolutionize the way companies interact with their data, providing an unrivaled experience in Google Cloud regions around the world through a strategic partnership. By delivering MongoDB's popular Atlas developer data platform and deep integrations with Google's data cloud to customers, the two companies are empowering businesses to create applications at scale with unprecedented data richness, all available through the Google Cloud Marketplace . This strategic partnership is bearing fruit. In the chemical industry, for example, users are now combining AI and data mining techniques using MongoDB Atlas with Google Clouds Foundation Models to accelerate the discovery of new molecules and make the process more environmentally friendly. Check out our AI resource page to learn more about building AI-powered apps with MongoDB. The next big step in generative AI Developers can experience the powerful capabilities of MongoDB Atlas Vector Search and Google Cloud foundation models to quickly and easily build applications with AI-powered features to enable highly personalized and engaging end-user experiences. Vertex AI provides the text embedding API to generate embeddings from customer data stored in MongoDB Atlas. Atlas Vector Search is a fully managed service that simplifies the process of effectively indexing this high-dimensional embedding data within MongoDB and being able to perform fast vector similarity searches. This combined with Google’s PaLM can be used to create advanced functionality like semantic search, classification, outlier detection, AI-powered chatbots, and text summarization - enabling developers to quickly build and scale next-generation applications. With Atlas Vector Search, developers can build intelligent applications powered by generative AI over any type of data. MongoDB Atlas Vector search combined with Google Cloud foundation models integrates the operational database, vector search, and LLMs into a single, unified, and fully managed platform. You can find out more about using Vector Search with Google Cloud foundation models from our information hub . Accelerating the discovery of new molecules with generative AI Every day brings new innovations in generative AI, and Vector Search is no exception. Developers are now using Google Cloud foundation models and MongoDB Vector Search to bring inventive applications to growing industries. In one example, MongoDB Partner Exafluence is utilizing AI and data mining techniques with MongoDB Atlas Vector Search and foundation models from Google Cloud to help joint customer Anupam Rasayan discover new molecules. India-based Anupam Rasayan is one of the leading companies engaged in the custom synthesis and manufacturing of specialty chemicals. The new platform, called Exf ChemXpert, includes configurable components for a wide variety of applications in the chemical industry, such as property prediction to help design new molecules, chemical reaction optimization to make developing molecules more environmentally friendly, and novel drug discovery to develop new treatments in the pharmaceutical industry. The home page for EXF ChemXpert, a one-stop platform that's accelerating the discovery of new molecules According to Anand Desai, Managing Director of Anupam Rasayan, this powerful new integration shows great promise. "In the world of chemistry, LLMs are potential game-changers for day-to-day product research and optimization of reaction mechanisms and operations," Desai said. "It can speed up new product and process innovations, reduce usage factors and costs, and push R&D to new heights beyond conventional methods. This transformation driven by new generative AI-powered tools will bring in a shift from conventional perspectives and benefit the chemical industry at large." In the Retrosynthesis Planner, the user asks a question about how to synthesize the chemical, acrylamide. Next steps Generative AI represents a significant opportunity for developers to create new applications and experiences and to add real business value for customers. For more about building applications on MongoDB Atlas with Google Cloud foundation models, including demos where you can see generative AI in action with MongoDB Atlas on Google Cloud, visit this special information hub . To get started running MongoDB on Google Cloud, visit the Google Marketplace .
MongoDB and Google Partnership Gains Momentum
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.
MongoDB and AWS Expand Global Collaboration
MongoDB launched as a developer-friendly, open source database in 2009, but it wasn't until 2016, when we released MongoDB Atlas , our fully managed database service, that the full vision for MongoDB truly emerged. Realizing that vision, however, has never been a solo effort. From the earliest days, MongoDB has partnered with a range of companies, but none more closely than with Amazon Web Services (AWS) as we've joined forces to make the developer experience as seamless as possible. Now we're kicking that partnership into overdrive. As announced today , MongoDB is expanding our global partnership with AWS. Though details of the agreement are confidential, the results will not be: Customers stand to benefit from deeper, broader technical integrations, improvements in migrating workloads from legacy data infrastructure to modern MongoDB Atlas, and more. For those of us who have worked to grow this partnership, it's exciting (and rewarding!) to see the scope of the work envisioned by MongoDB and AWS, together. On that note, it's worth revisiting how we got here. Building together From the earliest days , we've positioned MongoDB as the best way to manage a wide variety of data types and sources, in real time, at significant scale. Back then we called it "Big Data," but now we recognize it for what it is: what all modern data looks like. Then and now, MongoDB came with an open license that encouraged developers to easily access and tune the database to their needs. And so they did, with many developers opting to run their instances of MongoDB on AWS, removing the need to buy and provision servers. In fact, almost from the start of the company, we have worked closely with AWS to ensure that MongoDB users and customers would have an excellent experience running MongoDB on AWS. It was a great start, but it wasn't enough. Developers, after all, still had to fiddle with the dials and knobs of managing the database. This began to change in 2011, when the company released the MongoDB Monitoring Service (MMS). MMS made it much easier to monitor MongoDB clusters of any size. By 2013, we rolled MMS, Backup, and other MongoDB services into the MongoDB Management Service, and continued to work closely with AWS to optimize these services for MongoDB customers. Then in 2016, again with extensive AWS assistance, we launched MongoDB Atlas, a fully managed, integrated suite of cloud database and data services to accelerate and simplify how developers build with data. Making life easier for developers was the vision that co-founders Dwight Merriman and Eliot Horowitz had when they started MongoDB (then 10gen) in 2007. That vision has always depended on a strong partnership with AWS. This partnership got even stronger, as we just announced , with the promise of even better serverless options, expanded use of AWS Graviton instances to improve performance, and improved hybrid options through AWS Outposts. Beyond product, we'll also be more closely collaborating to reach and educate customers through joint Developer Relations initiatives, programs to reach new customers, and more. As good as our partnership has been, it just got significantly better. Although focusing on how the two companies compete may be convenient (for example, both organizations provide database services), how we cooperate is a more compelling story. So let's talk about that. A mutual obsession Over the past 15 years, MongoDB has built an extensive partner ecosystem. From open source mainstays like Confluent, to application development innovators like Vercel, data intelligence pioneers like BigID, and trusted system integration powerhouses like Accenture, we work closely with the best partners to ensure developers enjoy an exceptional experience working with MongoDB. As already noted, AWS is the partner with which we've worked most closely for the longest time. That partnership has resulted in tight integration between MongoDB and AWS services such as AWS Wavelength, Amazon Kinesis Data Firehose, Amazon EventBridge, AWS PrivateLink, AWS App Runner, Amazon Managed Grafana, and more. We also recently announced Pay as You Go Atlas on AWS Marketplace , giving customers even more options for how they run MongoDB on AWS. Additionally, as part of our new strategic agreement, we'll be offering joint customer incentive programs to make it even easier for customers to run proofs of concept and migrate from expensive legacy data infrastructure to MongoDB Atlas running on AWS. If this seems to paint an overly rosy picture of our partnership with AWS, it's worth remembering that the guiding principle for both AWS and MongoDB is customer obsession. Of course we've had moments when we've disagreed over how best to take care of customers, because every partnership has its fair share of friction. But behind the scenes, our product, marketing, and sales teams have worked together for years to meet customer needs. Customers seem to recognize this. In MongoDB's most recent earnings call, we announced that we now have more than 33,000 customers — including Shutterfly , Cox Automotive , Pitney Bowes , and Nesto Software — many of which choose to run Atlas on AWS. Still not convinced? There's perhaps no better way to understand what MongoDB can do for your organization than to try it. You can try Atlas for free , or you can choose to pay-as-you-go by starting with Atlas on the AWS Marketplace . Either way, we hope you'll let us know what you think.
On Demand MongoDB Enterprise Server on Pivotal Cloud Foundry
As organizations become increasingly application-centric, rapid and iterative development is no longer just a nice-to-have differentiator. It has become the defacto way of writing and delivering software. The central premise of this shift relies on enhancing collaboration between developers and IT operations while streamlining software development processes. For years both MongoDB and Pivotal have been focussed on helping teams successfully do just that. Now with the availability of MongoDB Enterprise Server on Pivotal Cloud Foundry, we are enabling teams to deliver applications more easily and efficiently than ever. As always, it all started with understanding customers’ pain points. Some MongoDB customers, such as ‘ The Gap, Inc ’ and ‘ Bosch ’, were also using Pivotal Cloud Foundry, but separately from MongoDB. They were also consuming other application services, such as Jenkins, RabbitMQ, Mulesoft, etc. through their Pivotal Cloud Foundry platform. We realized that by providing developers with the same experience to run their code as well as spin up MongoDB and other services, we could further streamline the process of building, testing, and delivering applications. This led us to work with Pivotal to offer a turnkey integrated MongoDB Enterprise Server on Pivotal Cloud Foundry. “MongoDB and Pivotal have been at the forefront of driving enterprise cloud-native adoption - Pivotal through Pivotal Cloud Foundry, and MongoDB through its modern data platform. Our integrated solution makes it easier to store and structure data in ways that encourage flexibility, enabling workloads to efficiently scale up and scale out. Teams of developers, data architects, and cloud operators can instantly provision production ready MongoDB Enterprise Server with the flexibility, scalability, and management controls needed to accelerate modern application development.” - Nima Badiey, Head of Business Development, Pivotal With our joint offering, developers can now instantly provision MongoDB as a standalone server, replica set, or sharded cluster across public and private clouds, and bind it to their application with just a few clicks or a single command. Moreover, it allows organizations to reduce costs by driving operational excellence. Operators and DBAs can continue to use their favorite management tools, MongoDB Ops Manager and Cloud Foundry BOSH, to automate and simplify patching, configuring, scaling, tuning, backup, recovery, and monitoring MongoDB based applications. Additionally, as MongoDB Enterprise Server is natively integrated with the Pivotal Cloud Foundry platform, users have access to enterprise-grade features such as advanced security protection with encryption, auditing, and centralized authentication. “Whether you want to modernize your landscape or build new IoT, single view, or analytics capabilities, our joint solution with Pivotal Cloud Foundry enables enterprises to rapidly deploy MongoDB Enterprise Server powered applications by abstracting away the complexities of managing, scaling and securing the underlying in public, private or hybrid infrastructure.” - Alan Chhabra, Sr. Vice President, WW Partners and APAC Sales at MongoDB How to run MongoDB as a Service on Pivotal Cloud Foundry MongoDB Enterprise Advanced is integrated as a service broker on Pivotal Cloud Foundry (PCF). Below is a sample workflow to run MongoDB Enterprise Server as a Service on PCF: IT Operations team downloads the MongoDB Enterprise Service tile from Pivotal Network and publish it to their PCF platform. Developer locates the MongoDB service in the marketplace and create an instance of MongoDB Enterprise Server using the relevant service plan (standalone, replica set, or sharded). Developer uses “cf bind-service” to bind the MongoDB instance to the corresponding application. PCF BOSH provisions and configures required resources, such as VMs and network connections. MongoDB Ops Manager is invoked to deploy and configure MongoDB instances as per the service plan provided by the developer. Now this MongoDB instance is successfully bound to the application. Operations team can use MongoDB Ops Manager to backup and maintain the provisioned instances. Below is a short demo video put together by my colleague – Jordan Sumerlus, Sr. Product Manager at MongoDB – that showcases our integration in action. To learn more visit and read the technical documentation here . Attending SpringOne Platform (Dec 4-7th, San Francisco)? Use discount code S1P_SPON_MONGODB20 for 20% off! Attend our session on Continuous Operations and Monitoring: MongoDB on PCF Visit us at booth # 23
Personalized Customer Experience Made Simple & Secure
Sitecore as a Service from Avanade and MongoDB In today’s connected world, customers are more informed and demanding than ever before. Brands are judged as much by the experience they deliver to their customers as they are for their products or services. These expectations raise the stakes for people managing these brands. No longer can marketing teams rely on the straight and narrow customer journey to reach the target audience. They need to go the extra mile to build a personalized and secure experience for each of our customers. Whether the customer is browsing on the company website, interacting on social media, or chatting with a customer service representative, each touch point provides an opportunity to delight the customer as well as collect data to gain valuable insights. These insights can then be leveraged to deliver an enhanced, more tailored experience at the next interaction, improving the outcome of the customer journey. However, achieving such sophistication requires marketing teams to be equipped with a technology that offers rich data management and analytical capabilities. Sitecore has emerged as one such powerful technology. Technology teams can leverage Sitecore to empower business users with the capabilities to deliver personalized experiences and derive meaningful insights. Built on MongoDB, Sitecore Experience Database (xDB) is a huge marketing data repository that collects all customer interactions, connecting them to create a comprehensive, unified view of the individual customer. This unified view can be used to automate the delivery of a personalized customer experience across all channels. As the core component of Sitecore xDB, MongoDB provides a scalable data platform to store and analyze all data from any channel and any touchpoint in real time. Although powerful, we often observe that getting the most out of a Sitecore implementation requires careful planning, implementation, migration of existing data, delivery, and continuous operations. At the same time, it's essential to ensure that business users face no disruptions while relying on large scale Sitecore xDB deployments. This is why MongoDB and Avanade have partnered to offer enterprises a comprehensive, hassle-free, cloud-based managed service for Sitecore on the MongoDB Atlas . The solution is delivered and managed by Avanade , Sitecore’s largest partner and it’s only global platinum solutions partner. It is powered by MongoDB Atlas , engineered and hosted by the same team that builds the MongoDB database. For those who do not want to run MongoDB for Sitecore xDB in the cloud, we also provide MongoDB Enterprise Advanced which includes the same capabilities but within your own data center or private cloud. Managing backend infrastructure for your Sitecore deployment by yourself can prove to be a major distraction. We often hear from our customers that dealing with operational challenges takes away focus from the main priority of continuously delivering an enhanced and personalized experience. As Sitecore is a real-time workload, operating it at scale can prove to be even more demanding. MongoDB and Avanade joint solution is purpose built to eliminate such distractions. You no longer need to juggle between the priorities of providing a high performance, secure, always-on experience and rapidly delivering new capabilities. Moreover, to make things simple, our solution provides a single line of support for Sitecore, MongoDB, and Microsoft Azure. “As a fully managed service designed and built for the cloud, our offering gives leading businesses and brands the agility and flexibility to grow as their business grows with the unique assurances large organizations require. Moreover, our expertise with MongoDB Atlas and Azure will help you ensure success at each stage of the Sitecore deployment lifecycle.” - Justin Calvo, Executive, Digital Marketing Platform, Services & Offerings, Avanade We also understand that you need to protect your brand while delivering an uninterrupted personalized experience anytime, anywhere. This means that your data platform needs to be secure, reliable, and scalable. MongoDB Atlas addresses those requirements to provide the best data platform to run Sitecore xDB in the cloud. Also available on Azure, Atlas is an automated cloud service for MongoDB that is secure and highly available by default. It incorporates the operational best practices that MongoDB has learned from optimizing thousands of deployments across startups and the Fortune 100. As your data and performance needs grow, Atlas can elastically scale to match changing needs without any disruptions. To keep your deployment up to date, patches are applied automatically, and upgrades can also be performed without any downtime. It also offers continuous backup with point in time recovery, so that you don’t lose any customer touchpoints. As your Sitecore implementation matures, you might want to develop advanced functionalities. MongoDB’s analytics capabilities and Avanade’s expertise can further help you develop these sophisticated functionalities. For instance, organizations can leverage MongoDB Connector for Apache Spark to perform deep analytics on live operational data in MongoDB to update customer classifications and personalize offers in real time. To get the most out of your Sitecore investment, you must also ensure that your Sitecore deployment is tailored to address specific business needs. With over 1,300 trained Sitecore specialists and more than 250 clients spanning 21 countries, you can trust Avanade’s expertise in designing, delivering, and managing large scale Sitecore implementations. Migrating to our solution is also easy. Existing Sitecore xDB can migrate their existing MongoDB deployments, either from on-premises or any other cloud, to MongoDB Atlas with live migration . Additionally, Avanade has specialized migration and integration practices to help start empowering business users faster. Together, Avanade and MongoDB are committed to helping enterprises and brands drive their digital and CMS strategy by implementing, deploying and managing Sitecore xDB with minimal friction. MongoDB and Avanade have not only helped the organizations integrate MongoDB, the data layer for Sitecore xDB, across operational, system of record and digital applications, but also perform sophisticated analytics. All of this without requiring the customer to invest time and money in developing and maintaining in-house skills. Visit this page to learn more about how we can help you get the most out of Sitecore xDB. --- Adam Burden, Senior Managing Director of Accenture Technology, talks about how Accenture (including Avanade) and MongoDB are working together to help enterprises create a competitive advantage through digital transformation.