MongoDB Atlas Vector Search dramatically simplifies securely building real-time generative AI applications to create highly accurate and personalized end-user experiences

MongoDB Atlas Search Nodes provide dedicated infrastructure to scale generative AI and relevance-based search workloads with up to 60 percent faster query times

AT&T Cybersecurity and Pathfinder Labs among customers building and scaling next-generation applications using MongoDB Atlas Vector Search and MongoDB Atlas Search Nodes

NEW YORK, Dec. 4, 2023 /PRNewswire/ -- MongoDB, Inc. (NASDAQ: MDB) today announced the general availability of MongoDB Atlas Vector Search and MongoDB Atlas Search Nodes to make it faster and easier for organizations to securely build, deploy, and scale next-generation applications at less cost. MongoDB Atlas Vector Search simplifies bringing generative AI and semantic search capabilities into real-time applications for highly engaging and customized end-user experiences using an organization's operational data. MongoDB Atlas Search Nodes provide dedicated infrastructure for applications that use generative AI and relevance-based search to scale workloads independent of the database and manage high-throughput use cases with greater flexibility, performance, and efficiency. Together, these capabilities on MongoDB Atlas provide organizations with the required foundation to seamlessly build, deploy, and scale applications that take advantage of generative AI and robust search capabilities with greater operational efficiency and ease of use. To get started with MongoDB Atlas, visit mongodb.com/atlas.

"Customers of all sizes from startups to large enterprises around the world tell us they want to take advantage of generative AI and relevance-based search to build next-generation applications that reimagine how businesses find ways to deeply personalize engagement with their customers, drive increased efficiency through automation, and propel new product development. But these customers know that complexity is the enemy of speed, and the choice of a database is fundamental to ensuring not just the success of an application but also how fast it can be built, deployed, and continually updated with the flexibility and scale needed to meet shifting end-user demands," said Sahir Azam, Chief Product Officer at MongoDB. "With the general availability of MongoDB Atlas Vector Search and MongoDB Atlas Search Nodes, we're making it even easier for customers to use a unified, fully managed developer data platform to seamlessly build, deploy, and scale modern applications and provide end users with the types of personalized, AI-powered experiences that save them time and keep them engaged."

As the use of MongoDB Atlas as an integrated developer data platform has rapidly grown, and more customers want to take advantage of generative AI, they have asked for more even integrated capabilities to meet the shifting demands of their businesses and end users—and MongoDB is meeting that demand:

• Integrate AI-powered capabilities into applications with MongoDB Atlas Vector Search: Unlike an add-on solution that only stores vector data, MongoDB Atlas Vector Search powers generative AI applications by functioning as a highly performant and scalable vector database with the added benefits of being integrated with a globally distributed operational database that can store and process all of an organization's data. This allows developers to use a single API to more easily build generative AI applications for virtually any type of workload across major cloud providers without the complexity of unnecessary data duplication and synchronization that bolt-on vector databases require. MongoDB Atlas Vector Search allows customers to easily and securely use retrieval-augmented generation (RAG) with pre-trained foundation models (FMs) to leverage their own up-to-date data for intelligent applications. As a result, applications built with MongoDB Atlas Vector Search can provide more accurate and relevant responses for specific domains and AI-powered use cases without the complex and tedious work of training and fine-tuning FMs or tacking on a separate database to store and process vector data. With the general availability of MongoDB Atlas Vector Search, customers can quickly build, deploy, and scale AI-powered features from semantic search to image comparison to highly personalized recommendations using a single, familiar, unified platform with minimal developer friction. Because MongoDB Atlas uses a flexible and scalable document-based data model that supports virtually any type of data, customers can easily combine a breadth of queries for vector data, analytical aggregations, text-based search, geospatial data, and time series data unavailable with other solutions to augment RAG and further refine responses to end-user requests. For example, an end-user could request, "Find real estate listings with houses that look like this image, were built in the last five years, and are in an area within seven miles north of downtown Seattle with top-rated schools and walking distance to parks," and an application running on MongoDB Atlas can quickly and seamlessly provide an FM the right data to produce accurate results—without the complexity of processing separate queries across multiple data stores that can increase response times and degrade end-user experiences. To get started, visit mongodb.com/products/platform/atlas-vector-search. 

• Isolate and scale generative AI and search workloads on MongoDB Atlas: Now generally available, MongoDB Atlas Search Nodes provide dedicated infrastructure for customers to manage generative AI and relevance-based search workloads that use MongoDB Atlas Vector Search and MongoDB Atlas Search independent of the core operational nodes of their database—enabling workload isolation, cost optimization, and better performance at scale. For example, a retailer running promotions leading up to a holiday shopping event may want to isolate and scale workloads for AI-powered chatbots and relevance-based search in specific geographical regions independent of their global operational database to optimize performance.With MongoDB Atlas Search Nodes, customers can improve performance by reducing query times by up to 60 percent to provide end users optimized AI-powered and relevance-based search experiences using their operational data with a single API, all with less complexity. To get started, visit mongodb.com/atlas/search.

Customers across industries including AT&T Cybersecurity, Pathfinder Labs, and many more are building and scaling next-generation applications with MongoDB Atlas Vector Search and MongoDB Atlas Search Nodes.

AT&T Cybersecurity simplifies securing valuable business assets by providing broad cybersecurity experience and award-winning services for network security, extended detection and response, and endpoints. "AT&T AlienVault is the world's most trusted and widely used open source Security Information and Event Management (SIEM) platform, and the ability to find relevant information with low latency is critical in the world of cybersecurity, threat detection, and incident response management. A delay could mean the difference between a successful detection and response, or a breach causing unfathomable destruction," said Matthew Schneid, Chief Architect at AT&T Cybersecurity. "We are very excited to continue our usage of Atlas Search Nodes as it becomes generally available. It has helped us host larger search deployments and scale our workloads, while significantly boosting the performance of complex search queries. Further, the platform as a whole, and the approach MongoDB has taken to build the feature in a way that engineers enjoy working with it regularly, is a huge plus."

Pathfinder Labs is a global leader in software development specializing in protecting vulnerable children by empowering law enforcement agencies with state-of-the-art technology. "We are committed to delivering investigators the most advanced tools, and we cannot accept delays in removing a child from harm due to investigations being overwhelmed by large amounts of disparate data. In situations where every minute impacts a child's well-being, these tools must enable investigators to swiftly navigate data challenges and rapidly apprehend perpetrators," said Bree Atkinson, CEO of Pathfinder Labs. "By using MongoDB Atlas, we're able to make data-driven decisions swiftly, boosting our productivity and decision-making speed. And with MongoDB Atlas Vector Search, we don't have to incorporate multiple tools to achieve AI-powered semantic search functionality. Now, we can handle it all from a single platform that delivers the scale and performance we require with less complexity and operational overhead."

MongoDB Atlas Vector Search is generally available today on AWS, Google Cloud, and Microsoft Azure. MongoDB Atlas Search Nodes are generally available today on AWS, with availability on Google Cloud and Microsoft Azure coming soon.

About MongoDB AtlasMongoDB 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.

About MongoDBHeadquartered in New York, MongoDB's mission is to empower innovators to create, transform, and disrupt industries by unleashing the power of software and data. Built by developers, for developers, MongoDB's developer data platform is a database with an integrated set of related services that allow development teams to address the growing requirements for today's wide variety of modern applications, all in a unified and consistent user experience. MongoDB has tens of thousands of customers in over 100 countries. The MongoDB database platform has been downloaded hundreds of millions of times since 2007, and there have been millions of builders trained through MongoDB University courses. To learn more, visit mongodb.com.

Forward-looking StatementsThis 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 enhancements of MongoDB's technology and offerings. 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 impact the COVID-19 pandemic may have on our business and on our customers and our potential customers; the effects of the ongoing military conflict between Russia and Ukraine on our business and future operating results; economic downturns and/or the effects of rising interest rates, inflation and volatility in the global economy and financial markets on our business and future operating results; our potential failure to meet publicly announced guidance or other expectations about our business and future operating results; our limited operating history; our history of losses; failure of our platform to satisfy customer demands; the effects of increased competition; our investments in new products and our ability to introduce new features, services or enhancements; our ability to effectively expand our sales and marketing organization; our ability to continue to build and maintain credibility with the developer community; our ability to add new customers or increase sales to our existing customers; our ability to maintain, protect, enforce and enhance our intellectual property; the growth and expansion of the market for database products and our ability to penetrate that market; our ability to integrate acquired businesses and technologies successfully or achieve the expected benefits of such acquisitions; our ability to maintain the security of our software and adequately address privacy concerns; our ability to manage our growth effectively and successfully recruit and retain additional highly-qualified personnel; and the price volatility of our common stock. These and other risks and uncertainties are more fully described in our filings with the Securities and Exchange Commission ("SEC"), including under the caption "Risk Factors" in our Quarterly Report on Form 10-Q for the quarter ended July 31, 2023, filed with the SEC on September 1, 2023 and other filings and reports that we may file from time to time with the SEC. Except as required by law, we undertake no duty or obligation to update any forward-looking statements contained in this release as a result of new information, future events, changes in expectations or otherwise.

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