MongoDB, Inc.

Thank you for standing by, and welcome to MongoDB's Feasible 424. This is for all participants on a listen-only mode. After the speaker's presentation, question and answer session. To ask a question at that time, please press star 11 on your telephone. Please... I will now turn the conference over to your host, Mr. Brian. Go ahead. Thanks, Valerie.

Good afternoon, and thank you for joining us today to review MongoDB's fourth quarter fiscal 2024 financial results, which we announced in our press release issued after the closing market today. Joining me on the call today are Dave Itacheria, President and CEO of MongoDB, and Michael Gordon, MongoDB's COO and CFO. During this call, we will make four looking statements, including statements related to our market and future growth opportunities, our expectations for the macroeconomic environment in fiscal 2025 and the impact of AI, the benefits of our product platform, our competitive landscape, customer behaviors, our financial guidance, and our planned investments. These statements are subject to a variety of risks and uncertainties, including the results of operations and financial conditions that cause actual results to differ materially from our expectations. For discussion of material risks and uncertainties that could affect our actual results, please refer to the risk described in our quarterly report on Form 10-Q for the quarter ended October 31, 2023, followed the SEC on December 7th, 2023. Any forwarding statements made in this call reflect our views only as of today, and we undertake no obligation to update them except as required by law. Additionally, we'll discuss non-GAAP financial measures on this conference call. Please refer to the tables in our earnings release on the investor relations portion of our website for reconciliation of these measures, the most directly comparable GAAP financial measures. With that, I'd like to turn the call over to Dave.

Thanks, Brian, and thank you to everyone for joining us today. I'm pleased to report that we had another strong quarter that capped off an impressive year as we continue to execute well to capture our large market opportunity. I will start by reviewing our fourth quarter and full year results before giving you a broader company update. Starting with the fourth quarter, we generated revenue of $458 million, a 27% year-over-year increase and above the high end of our guidance. Atlas revenue grew 34% year-over-year, representing 68% of revenue. We generated non-GAAP operating income of $69.2 million, for a 15% non-GAAP operating margin, and we ended the quarter with over 47,800 customers. Overall, we are pleased with our performance in the fourth quarter. We had a healthy quarter of new business, led by continued strength in new workload acquisition within our existing Atlas customers. In addition, our enterprise advanced business again exceeded our expectations, demonstrating strong demand for our platform and the appeal of our Run Anywhere strategy. Moving on to Atlas consumption trends, the quarter played out in line with our expectations, and we saw a stronger consumption than in Q4 of last year. Michael will discuss consumption trends in more detail. Finally, retention rates remained strong in Q4, reinforcing the quality of our product and the mission criticality of our platform. Stepping back and looking at fiscal 24 as a whole, I am proud of what we accomplished. We achieved revenue growth of 31% and a non-GAAP operating margin of 16%, well above our initial expectations. Atlas grew 37% year-over-year, and we added over 7,000 customers, ranging from AI startups to Fortune 500 companies. We had a record year of fast-paced, innovative product releases such as vector search, queryable encryption, and the preview of Atlas stream processing, reinforcing why so many customers and developers choose MongoDB's developer data platform. Finally, we continued to innovate on our go-to-market motion to drive workload acquisition. As we look into fiscal 25, let me share with you what I see in the market. First, I'm excited about our opportunity to win new business. In today's digital world, customers express their business strategy through software. The software-equal strategy that one of the most important investments a company can make is in the productivity of its software developers. Consequently, customers are gravitating towards MongoDB as their next generation developer data platform standard. Second, I see stable consumption growth going to next year. Atlas consumption trends have been steady for several quarters now, and we experienced less consumption variability in fiscal 24 compared to fiscal 23. Ultimately, the main driver of Atlas consumption is the growth in the underlying application usage, and we see stable usage growth across our portfolio workloads. Third, while I strongly believe that AI will be a significant driver of long-term growth for MongoDB, we are in the early days of AI, akin to the dial-up phase of the Internet era. To put things in context, it's important to understand that there are three layers to the AI stack. The first layer is the underlying compute and LLMs. The second layer is the fine-tuning of models and building of AI applications. And the third layer is deploying and running AI applications that end users interact with. MongoDB's strategy is to operate at the second and third layers to enable customers to build AI applications by using their own proprietary data together with any LLM, closed or open source, on any computing infrastructure. Today, the vast majority of AI spend is happening in the first layer, that is, investments in compute to train and run LLMs. Neither are areas in which we compete. Our enterprise customers today are still largely in the experimentation and prototyping stages of building their initial AI applications, first focused on driving efficiencies by automating existing workflows. We expect that it will take time for enterprises to deploy production workloads at scale. However, as organizations look to realize the full benefit of these AI investments, they will turn to companies like MongoDB, offering differentiated capabilities in the upper layers of the AI stack. Similar to what happened in the Internet era, when value accrued over time to companies offering services and applications leveraging the built-out Internet infrastructure, platforms like MongoDB will benefit as customers build AI applications to drive meaningful operating efficiencies, create compelling customer experiences, and pursue new growth opportunities. We already see our platform resonating with innovative AI startups building exciting applications for use cases such as real-time patient diagnostics for personalized medicine, cyber threat data analysis for risk mitigation, predictive maintenance for maritime fleets, and auto-generated animations for personalized marketing campaigns. Finally, our competitive position is getting stronger. Our win rates remain very high across all competitors, We rarely compete with legacy database providers as enterprises understand that they need to move away from inefficient and brittle legacy technology. We also rarely run into niche database players since customers are overwhelmed by the proliferation of point solutions that are hard to manage and add limited value. Our main competition remains the cloud players. They offer a wide array of database options, relational and non-relational, and benefit from the size and reach. We compete well against these players due to the flexibility and scalability of our document architecture, the fact that our open platform can run anywhere and avoids lock-in, and MongoDB's popularity among developers all around the world. Finally, when you look at our newer products, we see increased success competing against the established players in those markets. We find that the same principle applies as in the core database market. Customers don't want to manage a myriad of point solutions and prefer consolidating their spend with strategic vendors, especially in the current cost-conscious environment. In summary, we expect the environment in fiscal 25 to be largely similar to the environment we experienced in fiscal 24. With that backdrop, let me tell you what our priorities are going to next year. First, we will continue pressing our product advantage in the core database, since we believe customers will place an even greater premium on performance and scalability in the AI-enabled world. In addition, we will continue maturing on newer products, including additional features of vector search, GA of Atlas Stream Processing, and enhancements to other offerings. Second, we will remain singularly focused on new workload acquisition as the key long-term driver of our business. We will continue fine-tuning incentives to ensure that our entire go-to-market organization is focused on identifying and sourcing new workload opportunities. In addition, we will leverage our expertise and learnings from our self-serve business to use product-led growth techniques to increase the adoption of Atlas by other development teams within our existing large enterprise accounts. Third, we are focused on growing sales capacity. As we told you in the past, we are slow to grow capacity in fiscal 24, especially in the first half due to macro uncertainty. Given that the market is more stable now and that we remain under-penetrated compared to our opportunity, we'll increase the pace of go-to-market investments in fiscal 25. Fourth, we will continue investing to become a standard in more of our customer base. We intend to double the size of our strategic account program and dramatically expand our account-based marketing efforts in our largest accounts. Finally, we remain focused on unlocking the relational migration opportunity. To remind everyone, there are three elements to migrating an application, transforming the schema, moving the data, and rewriting the application code. Our current relational migrator offering is designed to automate large parts of the first two elements, but rewriting application code is the most manually intensive element. GenAI holds tremendous promise to meaningfully reduce the cost and time of rewriting application code. We will continue building AI capabilities into relational migrator, but our view is that the end solution will be a mix of product and services. This year, we are investing in a number of pilots leveraging AI for relational migrations paired with services to substantially simplify and scale the process. Now I'd like to spend a few minutes reviewing the adoption trends of MongoDB across our customer base. Customers across industries around the world are running mission-critical projects on MongoDB Atlas, leveraging the full power of our developer data platform, including ZF, Forbes, and Swiss Federal Railways. ZF, a global technology company supplying systems for passenger cars, commercial vehicles, and industrial technology, needed a central database solution with broad functionality to support more than 300,000 commercial vehicles connected to ZF infrastructure. ZF originally began using MongoDB on-premise in 2014 and migrated to MongoDB Atlas to modernize the architecture behind its new fleet orchestration solution. The team now uses time series and online archive to reduce the overall data storage size, as well as MongoDB Atlas search to manage indexes and Atlas charts to display billing information. MongoDB's developer data platform enables ZF to release new features faster as innovative technologies like drones and autonomous vehicles continue to come to market. Any, PicPay, and Anywhere Real Estate are examples of customers turning to MongoDB to free up the developer's time for innovation while achieving significant cost savings. Anywhere Real Estate, a global leader in residential real estate services whose brand portfolio includes Better Homes and Gardens, Century 21, Caldwell Banker, Corcoran, ERA, Sotheby's International Realty, is leveraging MongoDB Atlas and Atlas Search to greatly enhance its search capabilities. Their previous solution was too costly and operationally burdensome to maintain. Now, with Atlas Search, they can ingest data from hundreds of MLS sources, aggregate the data, and provide customers with a search solution that efficiently delivers accurate and up-to-date information, saving time and lowering costs. Anywhere is also exploring the use of Atlas Vector Search to provide semantic search and Gen AI features to millions of consumers. Samsung Electronics, Arsalan Mittal, and Citizens Bank are turning to MongoDB to modernize applications. Samsung Electronics Digital Appliances Division transitioned from their previous MySQL database to MongoDB Atlas to manage appliance data more effectively. By leveraging MongoDB's document model, Samsung's smart home service can collect real-time data from the team's AI-powered home appliances and use it for a variety of data-driven initiatives, such as training AI services. Their migration to MongoDB Atlas improved response times by more than 50%, and disk read latency was reduced from 3 seconds to 18 milliseconds, significantly improving availability and developer productivity. Let me wrap up by saying that I remain highly confident about our ability to execute on a long-term growth opportunity. We are pursuing one of the largest and fastest growing markets in all of software, with significant expansion opportunities in both new and existing customer accounts. While it's early days, we expect that AI will not only support the overall growth of the market, but also compel customers to revisit both their legacy workloads and build more ambitious applications. This will allow us to win more new and existing workloads and to ultimately continue to establish MongoDB as a standard in enterprise accounts. Before I turn it over to Michael, I would like to personally invite all of you to attend the investor session at mongodb.localnyc to be held at the Javits Center on May 2nd. Please email ir at mongodb.com if you are interested in attending. With that, here's Michael.