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The latest news from around MongoDB
Redefining the Database for AI: Why MongoDB Acquired Voyage AI
February 24, 2025
News
2024 William Zola Award for Community Excellence Recipient
We are thrilled to announce the 2024 recipient of MongoDB’s prestigious William Zola Award for Community Excellence: Mateus Leonardi! Each year, the William Zola Award for Community Excellence recognizes an outstanding community contributor who embodies the legacy of William Zola, a lead technical services engineer at MongoDB who passed away in 2014. Zola had an unwavering commitment to user success, and believed deeply in understanding and catering to users' emotions while resolving their technical problems. His philosophy is a guiding force for MongoDB’s community to this day. This award comes with a cash prize and travel sponsorship to attend a regional MongoDB.local event . Mateus Leonardi embodies these leadership values within the MongoDB community. In 2023, he led the launch and leadership of a new MongoDB User Group (MUG) in Florianópolis/Santa Catarina, Brazil. With his co-leaders, he has organized six successful MUG events, and has formed partnerships with local organizations and universities. He has also expanded his impact by becoming a MongoDB Community Creator , and has actively shared his MongoDB expertise outside of the user group. For example, in 2024 Mateus volunteered as a subject matter expert for MongoDB certifications. This involved being a panelist on several critical exam development milestones—from defining the knowledge and skills needed to earn credentials, to developing exam blueprints, to writing exam questions and verifying the technical accuracy of MongoDB certifications. Based on this record of support for our community, Mateus was also honored as a MongoDB Community Champion in 2024. Mateus excels as a dynamic leader and community advocate, extending invitations to fellow Brazilian MongoDB community leaders to speak at MUGs and local events. He also organizes and delivers talks at numerous events, including those for local university students. Ultimately, Mateus goes above and beyond in everything he commits to, and has demonstrated a genuine commitment to enhancing both the local MongoDB community and the broader developer community in his area. Here’s what Mateus Leonardi had to say about what the MongoDB community means to him: Q: Could you tell our readers a little about your day-to-day work? Mateus: As Head of Engineering at HeroSpark, my mission is to empower our team to innovate with quality and consistency. I work to create an environment where efficiency and constant evolution are natural in our day-to-day, always focusing on solutions that benefit both our team and our customers. Q: How does MongoDB support you as a developer? Mateus: MongoDB has been instrumental in our journey to enable adaptability without compromising quality. In work, MongoDB gives us that same flexibility in development, allowing us to quickly adapt to market changes while maintaining high performance and controlled costs. This combination gives us the confidence to innovate sustainably. Q: Why is being a leader in the MongoDB community important to you? Mateus: My sixteen-plus-year career has been marked by people who have helped me grow, and now it's my turn to give back. I view my role in the community as a way to multiply knowledge and create a positive impact. Technology has transformed my life, and through the MongoDB community, I can help others transform their realities too. Q: What has the community taught you? Mateus: The community has taught me that true learning happens when we share experiences. The act of teaching makes us better learners. Each interaction in the community allows us to reflect on our limitations and grow collectively. I've learned that the most rewarding thing is not the destination, but a journey shared with other developers. Congratulations to Mateus Leonardi, recipient of the 2024 William Zola Award for Community Excellence! To learn more about the MongoDB Community, please visit the MongoDB Community homepage .
MongoDB Named a Leader in the 2024 Gartner® Magic Quadrant™ for Cloud Database Management Systems
I’m pleased to announce that MongoDB has been named a Leader in the 2024 Gartner® Magic Quadrant™ for Cloud Database Management Systems (DBMSs) for the third consecutive year. In our view, this recognition cements MongoDB’s status as the only pure-play database provider in the cloud database management system category, underscoring MongoDB’s innovation, execution, and customer-centric approach. According to Gartner, “The cloud DBMS market remains as vibrant as ever and is transforming in important ways, especially in the use of gen AI and how DBMSs interact with other data management components. This Magic Quadrant will help data and analytics leaders make the right cloud DBMS choices in this essential market.” We believe this continued recognition by Gartner is a testament to MongoDB’s commitment to serving developers, as well as the investments we’ve made in our unified platform and integrated services. Driving innovation for enterprises MongoDB's mission is to empower innovators to create, transform, and disrupt industries by unleashing the power of software and data. 2024 was a year of innovation and accolades at MongoDB, and I’m proud to share some of its highlights: In October, we released MongoDB 8.0 , the best performing version of MongoDB yet. MongoDB 8.0 is over 30% faster than the previous version of the database, it’s more secure than ever, horizontal scaling is faster and easier (at a lower cost), and MongoDB 8.0 gives teams greater control for optimizing database performance. We also launched—and grew—the MongoDB AI Applications Program (MAAP) . With MAAP, MongoDB offers customers a full AI stack and an integrated set of professional services to help them keep pace with innovation, identify the best AI use cases, and to help them future-proof AI investments. MongoDB became a founding member of the U.S. Artificial Intelligence Safety Institute Consortium . Established by the U.S. Department of Commerce’s National Institute of Standards and Technology, the Consortium supports the development and deployment of safe and trustworthy AI. MongoDB released hundreds of features and enhancements to accelerate innovation, manage costs, and simplify building applications at scale. MongoDB was recognized as the most loved vector database in Retool’s State of AI report —for the second consecutive year. The Gartner Magic Quadrant for cloud database management systems “Gartner defines the cloud database management systems (DBMSs) market as solutions designed to store, manipulate, and persist data, primarily delivered as Software-as-a-Service (SaaS). These systems must support transactional, analytical, and hybrid workloads while enabling enterprises to innovate across multi-cloud, hybrid, and intercloud ecosystems.” 1 It’s our opinion that this recognition by Gartner is a testament to MongoDB’s strong ability to execute and support customers today, as well as MongoDB’s comprehensive product vision that positions our platform to support tomorrow's operational workloads. What is the Magic Quadrant, and what is a Leader? “A Gartner Magic Quadrant is a culmination of research in a specific market, giving you a wide-angle view of the relative positions of the market’s competitors. By applying a graphical treatment and a uniform set of evaluation criteria, a Magic Quadrant helps you quickly ascertain how well technology providers are executing their stated visions and how well they are performing against Gartner’s market view.” 2 According to Gartner, “Leaders execute well against their current vision and are well positioned for tomorrow.” Overall, Magic Quadrants can help you “get quickly educated about a market’s competing technology providers and their ability to deliver on what end-users require now and in the future.” Powering innovation at scale with MongoDB Atlas Enterprises choose MongoDB Atlas because it gives them the freedom and agility they need to succeed in a rapidly evolving digital landscape. MongoDB Atlas’s multi-cloud architecture—including availability across Amazon Web Services, Google Cloud, and Microsoft Azure—ensures customers can design for unmatched scale and resilience. By automating functions like scaling and performance optimization , and giving them the ability to leverage industry-first capabilities like MongoDB Queryable Encryption (which allows customers to encrypt, store, and perform queries directly on data), with MongoDB Atlas customers can spend less time managing infrastructure and more time delivering experiences. MongoDB Atlas’s integrated capabilities to support multi-modal data types and use cases—like full-text and vector search , stream processing , and data federation —accelerate innovation, helping enterprises quickly respond to market changes, power AI-driven insights, and deliver meaningful digital experiences to their end users—all without the burden of operational complexity. Modernizing and building for the future In our opinion, the Gartner Magic Quadrant provides organizations with a clear and accessible evaluation framework to identify solutions that fit their needs, today and tomorrow. The placement of MongoDB in the Leader quadrant for Cloud Database Management Systems—for the third year in a row!—validates the efforts MongoDB has made to help developers and organizations take advantage of their most valuable resource, their data. I talk to MongoDB customers frequently, and many say the same thing: in today’s digital-first economy, AI-powered applications and scalable data infrastructure aren’t just advantages, they’re absolute necessities. They say that the time to act is now, and they’re looking for solutions that will help them innovate, streamline, and seize the AI-driven future. And when it comes to modernizing their operations, they consistently point to MongoDB as their go-to partner. Begin your cloud journey with MongoDB Atlas today. Contact our sales team or register for a free account to begin building! And to learn how MongoDB can help accelerate your AI journey, visit the MongoDB AI Applications Program page. Footnotes Gartner, Magic Quadrant for Cloud Database Management Systems, Henry Cook, Ramke Ramakrishnan, et al., 18 December 2024 GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and/or its affiliates and are used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose. 1 Gartner Peer Insights, Cloud Database Management Systems, December 2024 https://www.gartner.com/reviews/market/cloud-database-management-systems 2 Gartner Research Methodologies, Gartner Magic Quadrant, 20 December 2024 https://www.gartner.com/en/research/methodologies/magic-quadrants-research
MongoDB’s 2024 Year in Review
It’s hard to believe that another year is almost over! 2024 was a transformative year for MongoDB, and it was marked by both innovation and releases that further our commitment to empowering customers, developers, and partners worldwide. So without further ado, let’s dive into MongoDB’s 2024 highlights. We’ll also share our executive team’s predictions of what 2025 might have in store. A look back at 2024 MongoDB 8.0: The most performant version of MongoDB ever In October we released MongoDB 8.0 , the fastest, most resilient, secure, and reliable version of MongoDB yet. Architectural optimizations in MongoDB 8.0 have significantly improved the database’s performance, with 36% faster reads and 59% higher throughput for updates. Our new architecture also makes horizontal scaling cheaper and faster. Finally, working with encrypted data is easier than ever, thanks to the addition of range queries in Queryable Encryption (which allows customers to encrypt, store, and perform queries directly on data). Whether you’re a startup building your first app, or you’re a global enterprise managing mission-critical workloads, MongoDB 8.0 offers unmatched power and flexibility, solidifying MongoDB’s place as the world’s most popular document database. Learn more about what makes 8.0 the best version of MongoDB ever on the MongoDB 8.0 page . Delivering customer value with the MongoDB AI Applications Program AI applications have become a cornerstone of modern software, and MongoDB is committed to equipping customers with the technology, tools, and support they need to succeed on their AI journey. That’s why we launched the MongoDB AI Applications Program (MAAP) in 2024, a comprehensive program designed to accelerate the development of AI applications. By offering customers resources like access to AI specialists, an ecosystem of leading AI and tech companies, and AI architectural best practices supported by integrated services, MAAP helps solve customers’ most pressing business challenges, unlocks competitive advantages, and accelerates time to value for AI investments. Overall, MAAP’s aim is to set customers on the path to AI success. Visit the MongoDB AI Applications Program page or watch our session from AWS re:Invent to learn more! Advancing AI with MongoDB Atlas Vector Search In 2024, MongoDB further cemented its role in the AI space with enhancements to MongoDB Atlas Vector Search . Recognized in 2024 (for the second consecutive year!) as one of the most loved vector databases , MongoDB continues to provide a scalable, unified, and secure platform for building cutting-edge AI use cases. Recent advancements like vector quantization in Atlas Vector Search help deliver even more value to our customers, enabling them to scale applications to billions of vectors at a lower cost. Head over to our Atlas Vector Search quick start guide to get started with Atlas Vector Search today, or visit our AI resources hub to learn more about how MongoDB can power AI applications. Search Nodes: Performance at scale Search functionality is indispensable in modern applications, and with Atlas Search Nodes, organizations can now optimize their search workloads like never before. By providing dedicated infrastructure for Atlas Search and Vector Search workloads, Search Nodes ensure high performance (e.g., a 40–60% decrease in query times), scalability, and reliability, even for the most demanding use cases. As of this year , Search Nodes are generally available across AWS, Google Cloud, and Microsoft Azure. This milestone underscores MongoDB’s commitment to delivering powerful solutions that scale alongside our customers’ needs. To learn more about Search Nodes, check out our documentation or watch our tutorial . Looking ahead: MongoDB’s 2025 predictions After the excitement of the past few years, 2025 will be defined by ensuring that technology investments deliver tangible value. Organizations remain excited about the potential AI and emerging technologies hold to solve real business challenges, but are increasingly focused on maintaining a return on investment. “Enterprises need to innovate faster than ever, but speed is no longer the only measure of success. Increasingly, organizations are laser-focused on ensuring that their technology investments directly address critical business challenges and provide clear ROI and competitive advantage—whether it’s optimizing supply chains, delivering hyper-personalized customer experiences, or scaling operations efficiently,” said Sahir Azam, Chief Product Officer at MongoDB. “In 2025, I expect to see organizations make significant strides in driving this innovation and efficiency by applying AI to more production use cases and by maturing the way they leverage their data to build compelling and differentiated customer experiences.” Indeed, we expect to see organizations make more strategic investments in emerging technologies like gen AI—innovating with a sharp focus on solving business challenges. “In 2025, we can expect the focus to shift from ‘what AI can do’ to ‘what AI should do,’ moving beyond the hype to a clearer understanding of where AI can provide real value and where human judgment is still irreplaceable,” said Tara Hernandez, VP of Developer Productivity at MongoDB. “As we advance, I think we’ll see organizations begin to adopt more selective, careful applications of AI, particularly in areas where stakes are high, such as healthcare, finance, and public safety. A refined approach to AI development will be essential—not only for producing quality results but also to build trust, ensuring these tools genuinely support human goals rather than undermining them.” With more capable, accessible application development tools and customer-focused programs like MAAP at developers’ fingertips, 2025 is an opportunity to make a data-driven impact faster than ever before. "Right now, organizations have an opportunity to leverage their data to reimagine how they do business, to more effectively adapt to a changing world, and to revolutionize our quality of life,” said Andrew Davidson, SVP of Products at MongoDB. “By harnessing our latest technologies, developers can build a foundation for a transformative future." Head over to our updates page to learn more about the new releases and updates from MongoDB in 2024. Keep an eye on our events page to learn what's to come from MongoDB in 2025!
The MongoDB AI Applications Program: Delivering Customer Value
When people ask me about MongoDB, I tell them that they’ve probably interacted with MongoDB without realizing it. In fact, many of the world’s leading companies—including 70% of the Fortune 100—are powered by MongoDB. Everything we do at MongoDB is about serving our customers, but that often happens in the background, where our work is invisible to many users. In my case, that means building an ecosystem of partners who enable customer innovation. A recent example is how MongoDB teamed up with Amazon Web Services (AWS) and Amazon Bedrock to help Base39 —a Brazilian fintech provider—automate loan analysis, decreasing decision time from three days to one hour, and reducing cost per loan analysis by 96%. And there’s the Indian company IndiaDataHub, which joined the MongoDB AI Applications Program (MAAP) to access AI expertise, in-depth support, and a full spectrum of technologies to enhance AI functionality within IndiaDataHub’s analytics platform. This includes connecting relevant data in MongoDB with Meta's AI models to perform sentiment analysis on text datasets. I could go on and on—after all, tens of thousands of MongoDB’s customers have success stories like these. Enabling customer success is precisely why we launched MAAP last summer, and why the program has evolved since. Customers tell us that they want to take advantage of AI, but they’re unsure how to navigate a fast-moving market, how to control costs, and how to unlock business value from their AI investments. So with MAAP, MongoDB offers customers a full AI stack and an integrated set of professional services to help them keep pace with the latest innovations, identify the best AI use cases, and to help them future-proof AI investments. With today’s announcement , Capgemini, Confluent, IBM, QuantumBlack, AI by McKinsey, and Unstructured have joined the 22 companies that now comprise the MAAP partner network. Which means that the MAAP ecosystem (which was founded with Accenture, Anthropic, Anyscale, Arcee AI, AWS, Cohere, Credal, Fireworks AI, Google Cloud, gravity9, LangChain, LlamaIndex, Microsoft Azure, Nomic, PeerIslands, Pureinsights, and Together AI) offers additional cutting-edge AI integration and solutions to customers—and more ways to set them on the path to AI success. CentralReach: Making an impact on autism with AI More than 150 customers have already gotten involved with MAAP, but I’m particularly excited to share the work of CentralReach . CentralReach provides an AI-powered electronic medical record (EMR) platform that is designed to improve outcomes for children and adults diagnosed with autism and related intellectual and developmental disabilities (IDD). Prior to working with MongoDB and MAAP, CentralReach was looking for an experienced partner to further connect and aggregate its more than 4 billion financial and clinical data points across its suite of solutions. CentralReach leveraged MongoDB’s document model to aggregate the company’s diverse forms of information from assessments to clinical data collection, so the company could build rich AI-assisted solutions on top of its database. Meanwhile, MAAP partners helped CentralReach to design and optimize multiple layers of its comprehensive buildout. All of this will enable CentralReach to support initiatives such as value-based outcome measurement, clinical supervision, and care delivery efficacy. With these new data layers in place, providers will be able to make substantial improvements to their clinical delivery to optimize care for all those they serve. “As a mission-driven organization, CentralReach is always looking to innovate on behalf of the clinical professionals—and the more than 350,000 autism and IDD learners—that we serve globally,” said Chris Sullens, CEO of CentralReach. “So being able to lean on MongoDBs database technology and draw on the collective expertise of the MAAP partner network—in addition to MongoDB’s tech expertise and services—to help us improve outcomes for our customers and their clients worldwide has been invaluable.” Working backward from customer needs The addition of Capgemini, Confluent, IBM, QuantumBlack, AI by McKinsey, and Unstructured to the MAAP partner network offers customers additional technology and AI support options. It also builds on MongoDB’s larger partner ecosystem , which is designed to give customers flexibility and choice. By working closely with our partners on product launches, integrations, and real-world challenges, MongoDB has been able to bring a better understanding of the challenges facing customers—and to give them the resources and confidence to move forward with groundbreaking technology like AI . Examples of support MAAP has offered customers include: Guidance on chunking strategies for an AI-native healthcare provider providing patient recommendations based on complex data sources Collaboration on advanced retrieval techniques to improve response accuracies for a large consultancy to automate manual research Evaluation of embedding models for multi-modal data stores for a well-known automaker developing diagnostic applications Guidance on architectures for complex agentic workflows for a mature enterprise technology provider augmenting customer service workflows One way we offer this support is through the MAAP Center of Excellence (CoE). The MAAP CoE comprises AI technical experts from across MongoDB and the MAAP partner ecosystem who collaborate with customers to understand their challenges, technical requirements, and timelines. The MAAP CoE can then recommend custom full-stack architectures and implementation best practices, optimized for the customer’s specific use case and requirements. Indeed, customization is intrinsic to MAAP: MongoDB and our MAAP partners will meet customers wherever they are to help them achieve their goals. For example, if an organization wants to fully own its AI application development, MongoDB and partners can provide guidance and expertise. And in cases where customers want hands-on support, we can help speed projects with professional services. Ultimately, we want MAAP customers—and anyone who works with MongoDB’s partner ecosystem at large—to feel empowered to own their application development, and to transform challenges into opportunities. Let’s build the next big thing together! To learn more about building AI-powered apps with MongoDB, see MongoDB’s AI Resources Hub , the Partner Ecosystem Catalog , or visit the MAAP page . And check out our partner Confluent’s own blog post about MAAP!
New Course for Building AI Applications with MongoDB on AWS
Developers everywhere want to expand the limits of what they can build with new generative AI technologies. But the AI market and its offerings have evolved so quickly that for many developers, keeping up can feel overwhelming. As we’ve entered the AI era, MongoDB and Amazon Web Services (AWS) have built upon our eight year partnership to deliver technology integrations—like MongoDB Atlas’s integrations with Amazon Bedrock and Amazon Q Developer (formerly CodeWhisperer)—that simplify the process of building and deploying gen AI applications. By combining MongoDB’s integrated operational and vector database capabilities with AWS’s AI infrastructure solutions, our goal is to make it easier for our developer community to innovate with AI. So, to help developers get started, we’re launching a new, free MongoDB Learning Badge focused on Building AI Applications with MongoDB on AWS . Building AI with MongoDB on AWS This is MongoDB University’s first AWS Learning Badge, and with it, we’ve focused on teaching developers how Amazon Bedrock and Atlas work together—including how to create a knowledge base in Amazon Bedrock, configure a knowledge base to use Atlas, inspect how a query is answered, create an Agent to answer questions based on data in Atlas, and configure guardrails that support responsible agentic behavior. In short, developers will learn how to remove the heavy lifting of infrastructure configuration and integration so they can get up and running with innovative new semantic search and RAG applications faster. Amazon Bedrock is a fully managed service from AWS that offers a choice of high-performing foundation models from leading AI companies via a single API, along with a broad set of capabilities organizations need to build secure, high-performing AI applications. Developers can connect Bedrock to MongoDB Atlas for blazing-fast vector searches and secure vector storage with minimal coding. With the integration, developers’ can use their proprietary data alongside industry-leading foundation models to launch AI applications that deliver hyper-intelligent and hyper-relevant results. Tens of thousands of customers are running MongoDB Atlas on AWS, and many have already embarked successfully on cutting-edge AI journeys. Take Scalestack for example, which used MongoDB Atlas Vector Search to build a RAG-powered AI copilot, named Spotlight, and is now using Bedrock’s customizable models to enhance Spotlight’s relevance and performance. Meanwhile, Base39 —a Brazilian fintech provider—used MongoDB Atlas and Amazon Bedrock to automate loan analysis, decreasing decision time from three days to one hour and reducing cost per loan analysis by 96%. Badge up with MongoDB MongoDB Learning Badges are a powerful way to demonstrate your dedication to continuous learning. These digital credentials not only validate your educational accomplishments but also stand as a testament to your expertise and skill. Whether you're a seasoned developer, an aspiring data scientist, or an enthusiastic student, earning a MongoDB badge can elevate your professional profile and unlock new opportunities in your field. Learn, prepare, and earn Complete the Learning Badge Path and pass a brief assessment to earn your badge. Upon completion, you'll receive an email with your official Credly badge and digital certificate, ready to share on social media, in email signatures, or on your resume. Additionally, you'll gain inclusion in the Credly Talent Directory, where you will be visible to recruiters from top employers. Millions of builders have been trained through MongoDB University courses—join them and get started building your AI future with MongoDB Atlas and AWS. And if you’re attending AWS re:Invent 2024, come find MongoDB at Booth #824. The first 100 people to receive their learning badge will receive a special gift! Start learning today
MongoDB is a Leader in The Forrester Wave™: Translytical Data Platforms
We’re pleased to announce that MongoDB has been recognized as a Leader in the recently released Forrester Wave™: Translytical Data Platforms, Q4 2024. The report—which highlights “Leaders, Strong Performers, Contenders, and Challengers” and is “an assessment of the top vendors in the market”—notes that “MongoDB is an excellent choice for organizations looking to enhance their document and NoSQL platforms with real-time insights by leveraging translytical capabilities.” What are translytical capabilities? So what are translytical capabilities? In short, modern applications use a growing number of data types for transactional, operational, and analytical uses. Developers can silo different data types and workloads into separate systems, but this causes architectural complexity and reduced agility for teams. A better approach—and one that speeds development—is to leverage a single platform that can store and use multiple data types for different purposes. Forrester defines these “translytical data platforms” as “next-generation data solutions built on a single database engine to seamlessly support transactional, operational, and analytical workloads without compromising data integrity, performance, or real-time analytics.” That’s why we built MongoDB Atlas as a developer data platform. It brings data like documents, vectors, streaming, and time-series together in one system so that you can run transactional, operational, and analytics workloads in one place. How Forrester measured translytical capabilities To measure providers, Forrester evaluated 15 of the most significant translytical data platform vendors against 26 criteria. These criteria span current offering and strategy, to market presence. Being recognized as a Leader is based on an organization’s scores in both current offering and strategy categories for criteria like vision and innovation. Forrester gave MongoDB the highest possible scores across nine criteria, including: Multimodel 1 Search Development Tools / API Scale optimization Streaming Platform management Roadmap Adoption Number of customers According to the report, “MongoDB continues to expand its translytical market share by delivering new capabilities that enhance automation, intelligent memory tiering, and multimodel support, including vector, streaming, analytics, and integrated transactions.” “Developers have been telling us for years that they need easy ways to work with all their data in one place,” said Jim Scharf, Chief Technology Officer at MongoDB. “That’s what continues to drive our strategy of making MongoDB Atlas the developer data platform. We’re excited to be recognized as a Leader in the new The Forrester Wave™: Translytical Data Platforms, and we will continue to support our customers’ growing needs for their data.” What are MongoDB customers doing with translytical capabilities? The Forrester report notes that organizations “use MongoDB to support real-time analytics, customer intelligence, the Internet of Things (IoT), and AI applications.” So, let’s look at a few examples in action. Companies like Ignition started using MongoDB just for operational data—but, over time, expanded into using Atlas Vector Search for AI use cases. Meanwhile, Bosch Digital makes their IoT data easier to work with by bringing multiple data sources together in a single platform. And, Keller Williams uses MongoDB Charts to bring their analytics to where their transactional data is, making it faster to gather insights for their product teams. Overall, customers are attracted to MongoDB because of how developer-friendly the platform is, and because it simplifies their lives by bringing their data together. Access your complimentary copy of The Forrester Wave™: Translytical Data Platforms, Q4 2024 here . Interested in starting your own translytical journey? Sign up for a free MongoDB Atlas account today! 1 Multimodel is defined as support for storing and using various data types.
Introducing Two MongoDB Generative AI Learning Badges
Want to boost your resume quickly? MongoDB is introducing two new Learning Badges , Building gen AI Apps and Deploying and Evaluating gen AI Apps. Unlike high-stakes certifications, which cover a large breadth and depth of subjects, these digital credentials are focused on specific topics, making them easier and quicker to earn. Best of all, they’re free! The Building Gen AI Applications with MongoDB Learning Badge validates users’ knowledge of developing gen AI applications using MongoDB Atlas Vector Search. It recognizes your understanding of semantic search and how to build chatbots with retrieval-augmented generation (RAG), MongoDB, and Langchain. The Deploying and Evaluating Gen AI Applications with MongoDB Learning Badge validates users’ knowledge of optimizing the performance and evaluating the results of gen AI applications. It recognizes your understanding of chunking strategies, performance evaluation techniques, and deployment options within MongoDB for both prototyping and production stages. Learn, prepare, and earn To earn your badge, simply complete the Learning Badge Path and take a short assessment at the end. Once you pass the short assessment, you'll receive an email with your official Credly badge and digital certificate. You can share it on social media, in email signatures, or on digital resumes. Additionally, you'll gain inclusion in the Credly Talent Directory , where you will be visible to recruiters from top employers and can open up new career opportunities. Learning paths are like curated roadmaps that guide you through essential concepts and skills needed for the assessment. Each badge has its own learning path: Building Gen AI Apps Learning Badge Path: This learning path guides you through the foundations of building a gen AI application with MongoDB Atlas Vector Search. You'll learn what semantic search is and how you can leverage it across a variety of use cases. Then you'll learn how to build your own chatbot by creating a RAG application with MongoDB and Langchain. Deploying and Evaluating Gen AI Apps Learning Badge Path: This learning path will help you take a gen AI application from creation to full deployment, with a focus on optimizing performance and evaluating results. You'll explore chunking strategies, performance evaluation techniques, and deployment options in MongoDB for both prototyping and production stages. We recommend completing the Building gen AI Apps Learning Badge Path before beginning this path. Badge up with MongoDB MongoDB Learning Badges offer a valuable opportunity to showcase your commitment to continuous learning and expertise in specific topics. These digital credentials not only recognize your educational achievements but also serve as a testament to your knowledge and skills. Whether you're a seasoned developer, an aspiring data scientist, or an enthusiastic student, earning a MongoDB badge can significantly enhance your profile and open up new opportunities in your field. Start earning your badges today—it’s quick, effective, and free! Visit MongoDB Learning Badges to begin your journey toward becoming a gen AI application expert and boosting your career prospects.
Introducing the New MongoDB Application Delivery Certification
Since we launched our System Integrators Certification Program in 2022, we have certified over 18,000 associates and architects across MongoDB’s various system integrator, advisory, and consulting services partners. This program gives system integrators a solid foundation in MongoDB and the capabilities that enable them to architect modernization projects and modern, AI-enriched applications. Our customers continue to tell us that they are looking to innovate quicker and take advantage of new technologies, and we want to support them in these goals. They want to work with partners who have in-depth knowledge of the problems they are trying to solve and hands-on experience working with the technology they are implementing. To meet this customer need and continue to evolve our partnership with our system integrators, we have launched the MongoDB Application Delivery Certification . This is a natural evolution of our certification program that provides comprehensive training and equips developers and application delivery leads with the knowledge and skills needed to design, develop, and deploy modern solutions at scale. Driving innovation alongside our partners The MongoDB Application Delivery Certification includes exclusive, partner-only, online learning and hands-on labs, as well as a proctored certification exam that teaches application delivery fundamentals and implementation best practices. Partners can expect carefully curated content on everything from optimizing storage, queries, and aggregation to retrieval-augmented generation (RAG), and how to architect and deliver with Atlas Vector Search . We piloted this new program with our partners at Accenture and Capgemini to ensure it would drive value for all participants. Twenty developers were invited from each company to participate in an initial version of the curriculum and were able to provide their input on its content. Based on their feedback, we created a program that’s completely self-service and flexible, so learners can fit the coursework into their schedules, at their own pace. "With the growth of AI and data-powered applications, Capgemini are investing in our staff to ensure they have the skills required for this transformation,” said Steve Jones, Executive Vice President, Data Driven Business & Collaborative Data Ecosystems at Capgemini. “The MongoDB Application Delivery Certification helps ensure our people have the right skills to help MongoDB and Capgemini collaborate with our clients on delivering the maximum business value possible in the data-powered future." "Accenture, a strategic partner and part of MongoDB’s AI Application Program, leverages MongoDB’s certification program to ensure the highest quality of delivery capability as our clients race to modernize legacy systems to MongoDB,” said Ram Ramalingam, Senior Managing Director and Global Lead, Platform Engineering and Intelligent Edge at Accenture. We understand that for many businesses, speed is a necessity, and keeping pace with the technological innovation in the current market is essential. Now, customers looking to implement MongoDB solutions will be able to do so quickly and easily by working with partners who have achieved the new MongoDB Application Delivery Certification. They can have the peace of mind knowing that these validated partners are extensively equipped to create and deploy robust MongoDB solutions at scale. What’s more, this new certification will provide partners with other opportunities. Partners who have demonstrated deep technical expertise by successfully completing the MongoDB Application Delivery Certification Program may be considered for the MongoDB AI Applications Program (MAAP). This will give them access to a greater network of customers that need help building and deploying modern applications enriched with AI technology. To learn more about MongoDB’s partners helping boost developer productivity with a range of proven technology integrations, visit the MongoDB Partner Ecosystem . Current SI partners can register for the MongoDB Certification Program and MongoDB Application Delivery Certification Program .
MongoDB AI Course in Partnership with Andrew Ng and DeepLearning.AI
MongoDB is committed to empowering developers and meeting them where they are. With a thriving community of 7 million developers across 117 regions, MongoDB has become a cornerstone in the world of database technology. Building on this foundation, we're excited to announce our collaboration with AI pioneer Andrew Ng and DeepLearning.AI, a leading educational technology company specializing in AI and machine learning. Together, we've created an informative course that bridges the gap between database technology and modern AI applications, further enhancing our mission to support developers in their journey to build innovative solutions. Introducing "Prompt Compression and Query Optimization" MongoDB’s latest course on DeepLearning.AI, Prompt Compression and Query Optimization , covers the prominent form factor of modern AI applications today: Retrieval Augmented Generation (RAG) . This course showcases how MongoDB Atlas Vector Search capabilities enable developers to build sophisticated AI applications, leveraging MongoDB as an operational and vector database. To ensure that learners taking this course are not just introduced to vector search, the course presents an approach to reducing the operational cost of running AI applications in production by a technique known as prompt compression. “RAG, or retrieval augmented generation, has moved from being an interesting new idea a few months ago to becoming a mainstream large-scale application.” — Andrew Ng, DeepLearning.AI Key course highlights RAG Applications: Learn to build and optimize the most prominent form of AI applications using MongoDB Atlas and the MongoDB Query Language(MQL). MongoDB Atlas Vector Search: Leverage the power of vector search for efficient information retrieval. MongoDB Document Model: Explore MongoDB's flexible, JSON-like document model, which represents complex data structures and is ideal for storing and querying diverse AI-related data. Prompt Compression: Use techniques to reduce the operational costs of AI applications in production environments. In this course, you'll learn techniques to enhance your RAG applications' efficiency, search relevance, and cost-effectiveness. As AI applications become more sophisticated, efficient data retrieval and processing becomes crucial. This course bridges the gap between traditional database operations and modern vector search capabilities, enabling you to confidently build robust, scalable AI applications that can handle real-world challenges. MongoDB's document model: The perfect fit for AI A key aspect of this course is that it introduces learners to MongoDB's document model and its numerous benefits for AI applications: Python-Compatible Structure: MongoDB's BSON format aligns seamlessly with Python dictionaries, enabling effortless data representation and manipulation. Schema Flexibility: Adapt to varied data structures without predefined schemas, matching the dynamic nature of AI applications. Nested Data Structures: Easily represent complex, hierarchical data often found in AI models and datasets. Efficient Data Ingestion: Directly ingest data without complex transformations, speeding up the data preparation process. Leveraging the combined insights from MongoDB and DeepLearning.AI, this course offers a perfect blend of practical database knowledge and advanced AI concepts. Who should enroll? This course is ideal for developers who: Are familiar with vector search concepts Building RAG applications and Agentic Systems Have a basic understanding of Python and MongoDB and are curious about AI Want to optimize their RAG applications for better performance and cost-efficiency This course offers an opportunity to grasp techniques in AI application development. You'll gain the skills to build more efficient, powerful, cost-effective RAG applications, from advanced query optimization to innovative prompt compression. With hands-on code, detailed walkthroughs, and real-world applications, you'll be equipped to tackle complex AI challenges using MongoDB's robust features. Take advantage of this chance to stay ahead in the rapidly evolving field of AI. Whether you're a seasoned developer or just starting your AI journey, this course will provide invaluable insights and practical skills to enhance your capabilities. Improve your AI application development skills with MongoDB's practical course. Learn to build efficient RAG applications using vector search and prompt compression. Enroll now and enhance your developer toolkit.
Meet the 2024 MongoDB Community Champions!
MongoDB is excited to announce our new cohort of Community Champions! MongoDB Community Champions comprise an inspirational global group of passionate, dedicated MongoDB advocates—including customers, partners, and inspiring community leaders. They demonstrate exceptional leadership in advancing the growth and knowledge of MongoDB’s brand and technology. The eighteen Community Champions this year represent a range of expertise and serve in a variety of professional and community roles. For example, Zhiyang Su is a senior applied scientist specializing in search ranking. With extensive experience in natural language processing (NLP), deep learning, and high-performance systems, he excels in dialog system design and optimization. Passionate about knowledge sharing, he regularly writes technical blog posts about MongoDB, NLP, and product design. Community Champions serve as the connective tissue between MongoDB and our community, keeping them informed about MongoDB’s latest developments and offerings. Community Champions also share their knowledge and experiences with others through a variety of media channels and event engagements. “With my contributions, I’m helping developers to get the right thing done faster by boosting their productivity,” said Mark Paluch, Spring Data Engineer and 2024 Community Champion. “Close collaboration in the form of learning, discussing, and giving feedback is key to get there. As members of this program, Champions gain a variety of experiences—including exclusive access to executives, product roadmaps, preview programs, an annual Champions Summit with product leaders—and relationships that grow their professional stature as MongoDB practitioners and help them be seen as leaders in the technology community. “Building on our global Champions program, this impressive group allows us to highlight a new level of outstanding members,” said Chuck Freedman, Director of Advocacy and Enablement, Developer Relations at MongoDB. “Our team led a cross-company nomination, interview, and review process to welcome a range of qualified and inspiring individuals representing our customers, partners, and global community.” Reflecting on this year’s selection process, Abirami Sukumaran , Developer Advocate and 2024 Community Champion, said: “I was impressed by the comprehensive nature of the interview. It wasn't just about checking boxes; it felt like a 360-degree assessment of my knowledge and enthusiasm for MongoDB Atlas, which made the entire process very positive. I am really thrilled to share my experience on this database program with enthralled developers around the globe.” We are also currently accepting applications for the Community Creator program. The Creator program consists of community members who create and share content to help others learn and uplevel their MongoDB knowledge. Creators are given exclusive access to product sessions, priority access to content features, and swag. To learn more, please visit the MongoDB Community Creators page. And now, without further ado, let’s meet the 2024 cohort of Community Champions! For more, visit our MongoDB Community Champions page.
MongoDB Atlas Once Again Voted Most Loved Vector Database
The 2024 Retool State of AI report has just been released, and for the second year in a row, MongoDB Atlas was named the most loved vector database. Atlas Vector Search received the highest net promoter score (NPS), a measure of how likely a user is to recommend a solution to their peers. This post is also available in: Deutsch , Français , Español , Português , Italiano , 한국어 , 简体中文 . Interested in discovering how to leverage AI to boost productivity, streamline development, and solve real engineering challenges? Check out our on-demand webinar with Retool to learn more. The Retool State of AI report is a global annual survey of developers, tech leaders, and IT decision-makers that provides insights into the current and future state of AI, including vector databases, retrieval-augmented generation (RAG) , AI adoption, and challenges innovating with AI. MongoDB Atlas commanded the highest NPS in Retool’s inaugural 2023 report, and it was the second most widely used vector database within just five months of its release. This year, MongoDB came in a virtual tie for the most popular vector database, with 21.1% of the vote, just a hair behind pgvector (PostgreSQL), which received 21.3%. The survey also points to the increasing adoption of RAG as the preferred approach for generating more accurate answers with up-to-date and relevant context that large language models ( LLMs ) aren't trained on. Although LLMs are trained on huge corpuses of data, not all of that data is up to date, nor does it reflect proprietary data. And in those areas where blindspots exist, LLMs are notorious for confidently providing inaccurate "hallucinations." Fine-tuning is one way to customize the data that LLMs are trained on, and 29.3% of Retool survey respondents leverage this approach. But among enterprises with more than 5,000 employees, one-third now leverage RAG for accessing time-sensitive data (such as stock market prices) and internal business intelligence, like customer and transaction histories. This is where MongoDB Atlas Vector Search truly shines. Customers can easily utilize their stored data in MongoDB to augment and dramatically improve the performance of their generative AI applications, during both the training and evaluation phases. In the course of one year, vector database utilization among Retool survey respondents rose dramatically, from 20% in 2023 to an eye-popping 63.6% in 2024. Respondents reported that their primary evaluation criteria for choosing a vector database were performance benchmarks (40%), community feedback (39.3%), and proof-of-concept experiments (38%). One of the pain points the report clearly highlights is difficulty with the AI tech stack . More than 50% indicated they were either somewhat satisfied, not very satisfied, or not at all satisfied with their AI stack. Respondents also reported difficulty getting internal buy-in, which is often complicated by procurement efforts when a new solution needs to be onboarded. One way to reduce much of this friction is through an integrated suite of solutions that streamlines the tech stack and eliminates the need to onboard multiple unknown vendors. Vector search is a native feature of MongoDB's developer data platform, Atlas, so there's no need to bolt on a standalone solution. If you're already using MongoDB Atlas , creating AI-powered experiences involves little more than adding vector data into your existing data collections in Atlas. If you're a developer and want to start using Atlas Vector Search to start building generative AI-powered apps, we have several helpful resources: Learn how to build an AI research assistant agent that uses MongoDB as the memory provider, Fireworks AI for function calling, and LangChain for integrating and managing conversational components. Get an introduction to LangChain and MongoDB Vector Search and learn to create your own chatbot that can read lengthy documents and provide insightful answers to complex queries. Watch Sachin Smotra of Dataworkz as he delves into the intricacies of scaling RAG (retrieval-augmented generation) applications. Read our tutorial that shows you how to combine Google Gemini's advanced natural language processing with MongoDB, facilitated by Vertex AI Extensions to enhance the accessibility and usability of your database. Browse our Resources Hub for articles, analyst reports, case studies, white papers, and more. Interested in discovering how to leverage AI to boost productivity, streamline development, and solve real engineering challenges? Check out our on-demand webinar with Retool to learn more. Want to find out more about recent AI trends and adoption? Read the full 2024 Retool State of AI report . Head over to our quick-start guide to get started with Atlas Vector Search today.
AWS Names MongoDB ASEAN Global Software Partner of the Year
I’m thrilled to announce that during the recent AWS Partner Summit in Bangkok , MongoDB was recognized as the ASEAN Global Software Partner of the Year — for the second year in a row. This award highlights MongoDB's focus on driving innovation with AWS, and is a testament to the success of customers in the region building transformative, next-generation applications with MongoDB and AWS. Based on merit, the AWS ASEAN Partner Awards were determined through a data-driven decision-making process, and “celebrated stellar achievements from partners that have shown remarkable success and achievement with AWS.” “We are proud to announce and acknowledge the ASEAN AWS Partners of 2024 that are helping customers accelerate innovation, develop industry-focused solutions, and build resilience amid the current evolving economic climate,” said Kirsten Gilbertson, Partner Organization Leader, AWS ASEAN. “AWS Partners are the force multiplier to accelerate cloud transformation in the region and drive local economic growth. With our partners, AWS remains committed to helping customers address industry needs and drive positive business and societal outcomes by leveraging our secure global infrastructure for the latest generative—AI, analytics, and machine learning technologies.” Demystifying AI and building next-gen apps with partners To help organizations of all sizes make the most of AI, earlier this month, we announced the MongoDB AI Applications Program (MAAP). The new program is designed to help organizations rapidly build and deploy modern applications with generative AI technology at enterprise scale. MAAP—which will be available starting in July—is being launched with industry-leading consultancies, cloud infrastructure, and generative AI framework providers, including AWS. Together, MongoDB and its MAAP partners will help customers solve business problems with AI by providing them with strategic advisory, professional services, and an integrated end-to-end technology stack. In short, MongoDB and partners like AWS, Anthropic, and Cohere will help customers use generative AI to enhance productivity, revolutionize customer interactions, and drive industry advancements. So it’s a real honor to receive the AWS ASEAN Global Software Partner of the Year two years running. This award validates the strength of our strategic collaboration with AWS, and the growing number of customers across industries who deploy mission-critical workloads on MongoDB Atlas running on AWS. We look forward to building on this momentum with AWS to help our customers unlock new possibilities by leveraging the power of data! To learn more about the MongoDB AI Applications Program, visit the MAAP page . And, check out MongoDB’s Partner Ecosystem to learn more about the wide range of integrations and solutions to help you build and run modern applications.