MongoDB Expands Collaboration with Google Cloud to Help Customers Across Industries Deploy and Scale New Classes of Applications
- Expanded collaboration between MongoDB and Google Cloud to facilitate building, scaling, and deploying generative AI applications
- Introduction of new solutions for retail and manufacturing industries
- Enhanced support for data processing with BigQuery and industry-specific solutions
- MongoDB Enterprise Advanced on Google Distributed Cloud for stringent security and data privacy requirements
- Focus on creating seamless development environments for engaging shopping experiences and data-driven applications
- None.
Insights
The expanded collaboration between MongoDB and Google Cloud, with a focus on generative AI and industry-specific solutions, signifies a strategic maneuver to capture a larger share of the cloud services market. MongoDB's introduction of Atlas Search Nodes on Google Cloud is designed to enhance performance and cost-efficiency for AI workloads. This is particularly relevant given the increased demand for AI applications, which require substantial computing resources.
Furthermore, the integration with Google Cloud Manufacturing Data Engine and the entry into Google Cloud's IVN partner program highlight MongoDB's commitment to vertical integration, tapping into the specific needs of the manufacturing and retail sectors. These moves are likely to strengthen MongoDB's competitive position and could lead to increased adoption of its services, potentially impacting its market share and revenue growth.
MongoDB Enterprise Advanced's availability on Google Distributed Cloud addresses a critical market need for enhanced data security and privacy, especially for sensitive workloads in regulated industries. By offering a solution that can operate in an air-gapped environment, MongoDB is catering to a niche but essential segment of the market that has stringent compliance requirements.
This move could result in increased trust and credibility among potential clients in the public sector and regulated industries. Over time, this could translate into a stable revenue stream for MongoDB, as these sectors typically engage in long-term contracts. However, the complexity and cost associated with these solutions may limit the addressable market size.
The seamless integration of MongoDB Atlas with Google Cloud's services, such as BigQuery and Vertex AI, simplifies the development process for generative AI applications. This ease of use can be a significant driver for developer adoption. By reducing the barriers to entry for building sophisticated AI-driven applications, MongoDB and Google Cloud are well-positioned to attract a broader developer community, potentially leading to a wider range of innovative applications being developed on their platforms.
Additionally, the enhanced integration with Spark and automated data pipelines can streamline data management processes, offering efficiency gains for customers. This could lead to increased customer satisfaction and retention, as well as attract new customers prioritizing development efficiency.
MongoDB Atlas Search Nodes now generally available on Google Cloud to make it easier and more cost-effective for customers to isolate and scale generative AI workloads
Google Cloud Vertex AI extension for MongoDB Atlas and new Spark integration with BigQuery make it even more seamless for customers to build generative AI applications with their proprietary data
MongoDB joins Google Cloud's Industry Value Network and introduces new MongoDB Atlas integration with Google Cloud Manufacturing Data Engine to help businesses build industry-specific solutions
MongoDB Enterprise Advanced on Google Distributed Cloud helps customers run applications that meet the most stringent security and data privacy requirements
"MongoDB's strong partnership with Google Cloud is the result of our close collaboration to meet the unique demands of organizations across industries," said Alan Chhabra, Executive Vice President of Partners at MongoDB. "Being awarded Google Cloud Partner of the Year—Marketplace is a testament to our commitment to providing the best solutions for customers building modern applications, while operating under the highest levels of security and data privacy requirements. We look forward to continuing to grow our partnership as more customers choose MongoDB and Google Cloud to enhance their businesses with new classes of generative AI applications."
"Customers continue to tell us they want world-class generative AI support built into the leading tools they already use, such as MongoDB," said Stephen Orban, Vice President of Migrations, ISVs, and Marketplace at Google Cloud. "MongoDB and Google Cloud have already helped thousands of joint customers successfully build and deploy applications with MongoDB Atlas on Google Cloud. We're excited to continue to build on this strategic partnership and provide even more ways for developers to quickly and effectively create and enhance applications with generative AI, including access to leading models through Vertex AI and automated data pipelines with BigQuery."
Partnered since 2018, MongoDB and Google Cloud have helped thousands of joint customers—including Keller Williams, Powerledger, Rent the Runway, and Ulta—adopt cloud-native data strategies to modernize how they run their organizations and serve end users. The expanded collaboration between MongoDB and Google Cloud now allows customers to:
- Seamlessly isolate and scale generative AI applications for high performance and efficiency: MongoDB Atlas Search Nodes—now generally available on Google Cloud—provide dedicated infrastructure for generative AI and relevance-based search workloads that use MongoDB Atlas Vector Search and MongoDB Atlas Search. MongoDB Atlas Search Nodes are independent of core operational database nodes and allow customers to isolate workloads, optimize costs, and reduce query times by up to 60 percent. For example, a financial services company running a high-traffic application during tax season can use dedicated infrastructure with Atlas Search Nodes to optimize performance independent of their database by isolating and scaling the generative AI portion of the workload. The company could then scale a knowledge retrieval workload that uses MongoDB Atlas Vector Search for AI-powered agents that autonomously take action on behalf of end users—without having to resize their entire database.
- Streamline building generative AI applications with leading foundation models: MongoDB Atlas Vector Search has provided an integration with Vertex AI since last year to give developers more choice of managed foundation models to build generative AI applications. Now, with a deepened integration, developers can use a dedicated Vertex AI extension to make it even easier to work with large language models (LLMs)—from Anthropic, Google Cloud, Meta, Mistral, and more—without having to transform data or manage data pipelines between MongoDB Atlas and Google Cloud. This allows developers to more easily augment LLMs with an organization's real-time operational data to build applications that provide context-aware and highly personalized end-user experiences that are more accurate, up to date, and trustworthy—all with less complexity. Developers can also use the new extension to input natural language in the Vertex AI console to automatically generate queries for manipulating data and performing database operations (e.g., create, read, update, delete) on data stored in MongoDB Atlas for a more seamless experience.
- Enhance analytical workloads with automated pipelines for operational data: BigQuery is a serverless, scalable, and cost-effective enterprise data warehouse that works across clouds for analytics, business intelligence (BI), and machine learning workloads. Customers currently use bi-directional sync between BigQuery and MongoDB Atlas to enhance their analytical workloads with real-time operational data or to easily provide end-user applications access to historical enterprise data. With a new integration for Spark stored procedures with BigQuery, customers can better automate, optimize, and reuse data processing workflows between BigQuery and MongoDB Atlas for analytics, BI, and end-user applications. For example, customers can automate pipelines that combine and transform real-time operational data stored in MongoDB Atlas with analytical data in BigQuery and send it to Vertex AI to create new types of end-user application experiences.
- Enrich data from the factory floor with real-time application data to optimize manufacturing and supply chain operations: Tens of thousands of organizations rely on MongoDB Atlas to securely store, process, and manage real-time application data of diverse types with high performance and scale. Manufacturers today want to modernize their operations by combining data from many sources like factory equipment sensors, end-user applications, and enterprise resource planning systems to automate decision-making and run more efficiently. However, many organizations are unable to transform their operations because they still rely on legacy technologies that are difficult to replace and cost-prohibitive to modernize. With a new integration between MongoDB Atlas and Google Cloud Manufacturing Data Engine, manufacturers can more easily combine and transform data from across their organizations to automate processes and optimize operations with modern, real-time applications.
- Easily build and deploy applications that provide modern shopping experiences with composable commerce capabilities: Retail organizations are at the forefront of inventing new customer experiences with personalization and automation. However, building applications that support these types of experiences at scale can be cumbersome and complex. To address these challenges, MongoDB is joining Google Cloud's Industry Value Network (IVN) partner program, an initiative that streamlines the development of differentiated end-to-end solutions across industries through collaboration with system integrator partners to accelerate innovation. Beginning with a new solution for retailers, customers can now take advantage of MongoDB Atlas on Google Cloud using the Integrated Commerce Network from Kin + Carta, a digital transformation consultancy, to deploy a modern commerce architecture to meet their unique business needs and provide customers with highly engaging shopping experiences.
- Run highly sensitive workloads in a tightly controlled and secured environment: Governments, public sector organizations, and enterprises in regulated industries often struggle to modernize their operations because of their data's high sensitivity. As a result, these organizations face limited choices when running workloads. With MongoDB EA on GDC, organizations can now build, deploy, and scale applications in an air-gapped environment without needing to connect to Google Cloud or the public internet. MongoDB is among the first software providers to offer a validated solution for the new Google Cloud Ready—Distributed Cloud program, a marketplace that provides tailored integrations to support use cases for customers with highly sensitive workloads. GDC enables governments, public sector organizations, and regulated enterprises to address strict data residency and security requirements, and combined with MongoDB EA, these organizations can now modernize all of their operations with the flexibility needed to securely deploy innovative applications and features while protecting sensitive data.
MongoDB and Google Cloud joint customers and partners welcome expanded partnership
Founded in 2009, Rent the Runway is disrupting the trillion-dollar fashion industry and changing the way women get dressed through the Closet in the Cloud, the world's first and largest shared designer closet. "MongoDB Atlas on Google Cloud is fantastic because it provides the whole set of infrastructure, which we don't have to take care of, so we can focus on our solutions and innovations," said Mike Liberant, Senior Director of Software Engineering at Rent the Runway. "For example, MongoDB Atlas enables us to process our garments more quickly and accurately without human error, which ultimately means our customers get a better, faster service to rent more and spend less. MongoDB and Google Cloud have been great partners, providing the services and tools where we require them."
Kin + Carta, a global digital transformation consultancy, helps companies modernize their business to better address the evolving needs of their customers. "Through the Integrated Commerce Network, we're showcasing the best-in-breed software partners who together make building an end-to-end commerce solution much easier," said Tara Catalano, National Google Cloud Alliance Lead at Kin + Carta. "MongoDB's connectors and integrations with both BigQuery and Vertex AI make it a compelling choice for customers who want flexibility and optionality in building the best composable solution for their needs, as well as positioning them well to seize the opportunity with generative AI."
About MongoDB Atlas
MongoDB Atlas is the leading multi-cloud developer data platform that accelerates and simplifies building modern applications with a highly flexible, performant, and globally distributed operational database at its core. By providing an integrated set of data and application services in a unified environment, MongoDB Atlas enables development teams to quickly build with the security, performance, and scale modern applications require. Millions of developers and tens of thousands of customers across industries—including Cathay Pacific, Cisco, GE Healthcare, Intuit, Toyota Financial Services, and Verizon—rely on MongoDB Atlas every day to innovate more quickly, efficiently, and cost-effectively for virtually every use case across the enterprise. To get started with MongoDB Atlas, visit mongodb.com/atlas.
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This press release includes certain "forward-looking statements" within the meaning of Section 27A of the Securities Act of 1933, as amended, or the Securities Act, and Section 21E of the Securities Exchange Act of 1934, as amended, including statements concerning MongoDB's expanded collaboration with Google Cloud. These forward-looking statements include, but are not limited to, plans, objectives, expectations and intentions and other statements contained in this press release that are not historical facts and statements identified by words such as "anticipate," "believe," "continue," "could," "estimate," "expect," "intend," "may," "plan," "project," "will," "would" or the negative or plural of these words or similar expressions or variations. These forward-looking statements reflect our current views about our plans, intentions, expectations, strategies and prospects, which are based on the information currently available to us and on assumptions we have made. Although we believe that our plans, intentions, expectations, strategies and prospects as reflected in or suggested by those forward-looking statements are reasonable, we can give no assurance that the plans, intentions, expectations or strategies will be attained or achieved. Furthermore, actual results may differ materially from those described in the forward-looking statements and are subject to a variety of assumptions, uncertainties, risks and factors that are beyond our control including, without limitation: the effects of the ongoing military conflicts between
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FAQ
What collaboration was announced between MongoDB and Google Cloud?
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What does MongoDB Enterprise Advanced on Google Distributed Cloud offer?
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