Building Gen AI with MongoDB & AI Partners | October 2024

Gregory Maxson
November 11, 2024 | Updated: November 20, 2024
#genAI

It’s no surprise that AI is a topic of seemingly every professional conversation and meeting nowadays—my friends joke that 11 out of 10 words that come out of my mouth are “gen AI.” But an important question remains: do organizations truly know how to harness AI, or do they simply feel pressured to join the crowd? Are they driven by FOMO more than anything else?

One thing is for sure: adopting generative AI still presents a huge learning curve. Which is why we’ve been working to provide the right tools for companies to build innovative gen AI apps with, and why we offer organizations a variety of AI knowledge and guidance, regardless of where they are with gen AI.

We’re fortunate to work with our industry-leading partners to help educate and shape this nascent market. Working so closely with them on product launches, integrations, and solving real-world challenges allows us to bring diverse perspectives and a better understanding of AI to our customers, giving them the technology and confidence to move forward even before engaging with tough use cases and specific technical problems (something that the MongoDB AI Applications Program can definitely help with).

One of our main educational initiatives has been our webinar series with our top-tier MAAP partners. We’ve constantly launched video content to deepen understanding of topics essential to gen AI for enterprises answering broader questions such as “how can my company generate AI-driven outcomes” and “how can I modernize my workload,” to specific, tangible topics such as “how to build a chatbot that knows my business.” Each session is designed to move beyond the basics, sharing insights from experts in AI, and addressing our customers’ burning questions and challenges that matter most to them.

Welcoming new AI and tech partners

In October, we also welcomed four new AI and tech partners that offer product integrations with MongoDB. Read on to learn more about each great new partner!

Astronomer

Astronomer empowers data teams to bring mission-critical software, analytics, and AI to life and is the company behind Astro, the industry-leading data orchestration and observability platform powered by Apache Airflow.

"Astronomer's partnership with MongoDB is redefining RAG workflows for GenAI workloads. By integrating Astronomer's managed Apache Airflow platform with MongoDB Atlas' powerful vector database capabilities, we enable organizations to orchestrate complex data pipelines that fuel advanced AI and machine learning applications”, said Julian LaNeve, CTO at Astronomer. “This collaboration empowers data teams to manage real-time, high-dimensional data with ease, accelerating the journey from raw data to actionable insights and transforming how businesses harness the power of generative AI."

CloudZero

CloudZero is a cloud cost optimization platform that automates the collection, allocation, and analysis of cloud costs to identify savings opportunities and improve cloud efficiency rates.

"Database spending is one of the shared costs that can make it tricky for organizations to reach 100% cost allocation. CloudZero eliminates that problem," said Anand Sundaram, Senior Vice President of Product at CloudZero. “Our industry-leading allocation engine can organize MongoDB spend in a matter of hours, tracing it precisely to the products, features, customers, and/or teams responsible for it. This way, companies get a clear view of what’s driving their costs, who’s accountable, and how to optimize to maximize their cloud efficiency.”

ObjectBox

ObjectBox is an on-device vector database for mobile, IoT, and embedded devices that enables storing, syncing, and querying data locally online and offline.

"We’re thrilled to partner with MongoDB to give developers an edge,” celebrated Vivien Dollinger, CEO and co-founder of ObjectBox. “By combining MongoDB’s cloud and scalability with ObjectBox’s high-performance on-device database and data sync, we empower developers to build fast, data-rich applications that feel right at home across devices and environments. Offline, online, edge, cloud, whenever, wherever... We’re here to enable your data with speed and reliability."

Rasa

Rasa is a flexible framework for building conversational AI platforms that lets companies develop scalable generative AI assistants that hit the market faster.

“Rasa is excited to partner with MongoDB to empower companies in building conversational AI experiences. Together, we’re helping create generative AI assistants that save costs, speed up development, and maintain full brand control and security,” said Melissa Gordon, CEO of Rasa. “With MongoDB, deploying production-ready generative AI assistants is seamless, and we’re eager to continue accelerating our customers’ journey toward trusted conversational AI solutions.”

But wait, there's more!

Whether you’re starting out or scaling up, MongoDB and our partners are here with the resources, expertise, and trusted guidance to help you succeed in your genAI strategy! And if you have any suggestions for a good webinar topic, don’t hesitate to reach out.

To learn more about building AI-powered apps with MongoDB, check out our AI Resources Hub and stop by our Partner Ecosystem Catalog to read about our integrations with MongoDB’s ever-evolving AI partner ecosystem.

← Previous

MongoDB: Powering Digital Natives

Today's rapidly evolving digital landscape is dominated by digital native companies, driving innovation . These are companies born in the digital age and who operate through digital channels with a business model enabled by technology and data. They are not only adept at using technology but are also reshaping the way software is developed and deployed. This article delves into the challenges and opportunities facing digital natives in modern application development, with a particular focus on the complexities of managing data. We’ll explore how the right data platform can empower your digital native organization to build high-quality software faster, adapt to changing market demands, and unlock the full potential of your business. Strong foundations: The four pillars of tech-fueled growth for digital natives Achieving explosive growth requires a strong foundation built on specific principles, which empower rapid scaling and success. Here, we explore the four key pillars that fuel tech-driven growth for digital natives: Product-market fit, fast: As a digital native, you must continuously ship and iterate products to achieve a quick product-market fit. This builds customer trust and captures opportunities before competitors can in an evolving market. Data and AI-driven decisions: You must leverage data to personalize experiences, automate processes, and guide product decisions. A robust data architecture feeds real-time data into AI models, enabling data-driven decisions organization-wide. Balance of freedom and control: Your developers must have the freedom to choose technologies, even as your organization maintains control over the infrastructure to manage risks and costs at scale. Selected technologies must integrate within your overall technology estate. Extensible and open technologies: You must explore disruptive technologies while maintaining existing systems. Freedom from platform and vendor lock-in enables quick adoption of innovations, from current generative AI capabilities to future technological advances. Data: The unsolved challenge in modern application development From cloud platforms and managed services to gen AI code assistants, advancements have transformed how engineering teams build, ship, and run applications: Agile methods and programmatic APIs streamline development, while CI/CD and infrastructure as code automate processes. Containerization, microservices, and serverless architectures enable modularity, while new languages and frameworks boost capabilities. Enhanced logging and monitoring tools provide deep application health insights. Figure 1: Tools and processes to maximize velocity. But none of these advancements address where developers spend most of their time— data . In fact, 73% of developers share time and again that working with data is the hardest part of building an application or feature. So why is data the problem? Traditionally, selecting a database, often an open-source relational one, is the first step in development. However, these databases can struggle with the characteristics of modern data: it’s high volume, unstructured, and constantly evolving. As applications mature and their data demands grow, development teams may encounter challenges with achieving scalability and maintaining service resilience. Some teams turn to NoSQL databases, but even then they find there are limited capabilities, pushing them back to relational databases. As the application gains traction, the business’s appetite for innovation grows, compelling development teams to incorporate an expanding array of database technologies. This results in an architectural sprawl, imposing on teams the challenges of mastering, sustaining, and harmonizing new technologies. Concurrently, the dynamic technology landscape undergoes constant evolution, demanding teams to swiftly adjust. As a result, self-contained, autonomous teams encounter these hurdles recurrently, highlighting the pressing need for streamlined solutions to mitigate complexity and enhance agility. Figure 2: The evolving tech landscape. Data sprawl: A major threat to developer productivity and business agility Data sprawl is slowing everyone down. The more systems we add, the harder it is for developers to keep up. Each new database brings its own unique language, format, and way of working. This creates a huge headache for managing everything—from buying new systems to making sure they all work together securely. It’s a constant battle to keep data accessible, consistent, and backed up across all these different platforms. Figure 3: Teams building on separate stacks leads to data sprawl and manageability issues across the organization It compromises every single one of the four outcomes your technology foundation should be providing, yielding the opposite results: Missed opportunities, lost customers: Fragmented development experiences consume time as engineers struggle with multiple technologies, frameworks, and extract, transform, and load mechanisms for duplicating data between systems. This slows down releases, degrades digital product quality, and impedes engineers from achieving product-market fit and effective competition. Flying blind: With your operational data siloed across multiple systems, you lack the data foundations necessary to use live data in shaping customer experiences or reacting to market changes. This is because you are unable to feed reliable, consistent, real-time data into your AI models to take action within the flow of the application or to provide the business with up-to-the-second visibility into operations. High attrition, high costs: Complex data architecture impacts development team culture, leading to siloed knowledge, inefficient collaboration, and decreased developer satisfaction. This complexity also consumes substantial resources in maintaining existing systems by diverting resources from new projects that are vital for business competition in new markets. Disruption from new technologies: Dependence on any one cloud provider can stifle innovation for development teams by restricting access to the latest technologies. Developers are confined to the tools and services offered by a single provider, hindering their ability to explore and integrate new, potentially more efficient, or advanced technologies. Speed: A unified developer experience for building high-quality software faster In today’s digital world, speed is king. Your customers expect seamless experiences, but clunky applications leave them frustrated. But traditional databases can be a bottleneck, struggling to keep pace with your ever-evolving data and slowing down development. The future of data is here, and it’s flexible: a data platform built for digital natives . It leverages a flexible document model, letting you store and work with your data exactly how you need it. This eliminates rigid structures and complex migrations, freeing your developers to focus on what matters—building amazing applications faster. Flexible document data models empower developers to handle today’s rapidly evolving application data ( 80%+ unstructured) that relational databases struggle with. MongoDB documents are richly typed, boosting developer productivity by eliminating the need for lengthy schema migrations when implementing new features. Developers get to use their preferred tools and languages. Through its drivers and integrations, MongoDB supports all of the most popular programming languages, frameworks, integrated development environments, and AI-code assistance tools. MongoDB scales! It starts small and scales globally. Built for elasticity and horizontal scaling, it handles massive workloads without app changes. Figure 4: A unified developer experience, integrating all necessary data services for building sophisticated modern applications Introducing MongoDB Atlas : a fully-managed cloud database built for the modern developer. It enables the integration of real-time data from devices with AI capabilities (through vector embeddings and large language models ) to personalize user experiences. Stream processing empowers constant data analysis, while in-app analytics provides real-time insights without needing separate data warehouses, all while automatically managing data movement and storage for cost-effectiveness. MongoDB Atlas simplifies database management with the following: Easy deployment via UI, API, CLI, Kubernetes, and infrastructure as code tools. Automated operations for cost-effective performance and real-time monitoring. MongoDB Atlas customer success stories: Development with speed, scale, and efficiency Delivery Hero Delivery Hero, a global leader in online food delivery, leverages MongoDB Atlas to power its rapid service. Founded in 2011, Delivery Hero now serves millions of customers in over 70 countries through brands like PedidosYa, foodpanda, and Glovo. Having replaced its legacy SQL database, Delivery Hero optimized operations and bolstered performance by using MongoDB Atlas. By leveraging MongoDB Atlas Search, Delivery Hero revolutionized its search functionality, ensuring a seamless user experience for its extensive customer base through simplified indexing and real-time data accuracy. MongoDB’s scalability has empowered Delivery Hero to manage over 100 million products in its catalog without encountering latency issues, enabling the company to expand its services while maintaining peak performance. This agility, coupled with MongoDB’s cost-effectiveness, has enabled Delivery Hero to swiftly adapt to evolving customer demands, solidifying its position in the fiercely competitive delivery market. MongoDB Atlas Search was a game changer. We ran a proof of concept and discovered how easy it is to use. We can index in one click, and because it’s a feature of MongoDB, we know data is always up-to-date and accurate. Andrii Hrachov, Principal Software Engineer, Delivery Hero Read the full customer story to learn more. Coinbase Coinbase, a prominent cryptocurrency exchange boasting 245,000 ecosystem partners and managing assets worth $273 billion , trusts MongoDB to handle its extensive data workload. As the company grew, MongoDB scaled seamlessly to accommodate the increased demand. To further improve performance in the fast-paced crypto world, Coinbase partnered with MongoDB to develop a system that significantly accelerated data transfer to reporting tools, reducing processing time from days to a mere 5-6 hours. This near real-time data access enables Coinbase to rapidly analyze trends and make informed decisions, maintaining a competitive edge in the ever-evolving crypto landscape. Watch Coinbase's full session at MongoDB.local Austin, 2024 to learn more. MongoDB: Your flexible platform for digital growth With MongoDB, you can freely explore, experiment, develop, and deploy according to your digital-native business needs. If you would like to learn more about how MongoDB can empower your digital-native business to conquer market trends, visit: Innovate With AI: The Future Enterprise Application-Driven Intelligence: Defining the Next Wave of Modern Apps AI-Driven Real-Time Pricing with MongoDB and Vertex AI

November 7, 2024

Next →

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

December 23, 2024