MongoDB, Inc.

Good day, and thank you for standing by. Welcome to the MongoDB third quarter fiscal year 2025 conference call. At this time, all participants are in a listen-only mode. After the speaker's presentation, there'll be a question and answer session. To ask a question during the session, you'll need to press star 11 on your telephone. You will then hear an automated message advising your hand is raised. To withdraw your question, please press star 11 again. Please be advised that today's conference is being recorded. I would now like to turn the call over to your speaker for today. Brian, then you, please go ahead.

Thank you, Lisa. Good afternoon, and thank you all for joining us today to review MongoDB's third quarter fiscal 2025 financial results, which we announced in our press release issued after the close of the market today. Joining me on the call today are Dave Itacheria, President and CEO of MongoDB, and Michael Gordon, MongoDB 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 and growth opportunities in AI. These statements are subject to a variety of risks and uncertainties, including the results of operations and financial condition, They cause actual results to differ materially from our expectations. For a discussion of the material risks and uncertainties that could affect our actual results, please refer to the risks described in our quarterly report on Form 10-Q for the quarter ended July 31, 2024, that we filed with the SEC on August 30, 2024. Any forward-looking 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 will discuss non-GAAP financial measures on this conference call. Please refer to the tables of earnings released in the Investor Relations portion of our website for a reconciliation of these measures to the most directly comparable GAAP financial measure. With that, I'd like to turn the call over to Dave. Dave?

Thanks, Brian, and thank you to everyone for joining us today. I'm pleased to report that we had a strong quarter of new business and executed well against our large market opportunity. Let's begin by reviewing our third quarter results before giving you a broader company update. We generated revenue of $529 million, a 22% year-over-year increase and above the high end of our guidance. Atlas revenue grew 26% year-over-year, representing 68% of total revenue. We generated non-GAAP operating income of $101 million for a 19% non-GAAP operating margin, and we ended the quarter with over 52,600 customers. Overall, we were pleased with our performance in the third quarter. We had a strong new business quarter and were happy with our new workload acquisition on Atlas. Our non-Atlas business significantly exceeded expectations, in part because we benefited from a few large multi-year deals as customers continue to value our run-anywhere strategy and want to build a deeper, longer-term relationship with MongoDB. Atlas consumption was slightly better than expected in a macro environment that we would characterize as largely consistent with what we saw in the first half of the year. Michael will cover consumption trends in more detail. Retention rates remain strong in Q3, demonstrating the mission criticality of our platform. On our Q1 earnings call, we shared with you the three major strategic initiatives that we believe will enable us to maximize our long-term opportunity. I want to give you an update on the progress we're making on those initiatives. First, we are increasing our investment in the enterprise channel since we see the strongest returns in this part of the market. Specifically, we're expanding our strategic account program going to next year. as we see more accounts that will benefit from incremental investment. In addition, we're investing time and resources to educate developers in large enterprise accounts and up-level their MongoDB skills. These organizations have thousands of developers, and as we penetrate them more deeply, we encounter developers who have historically only built SQL applications and simply do not know how to use MongoDB to its full potential. In our experience, educating these developers on the benefits of MongoDB drives significant incremental adoption of our platform. To fund these upmarket investments, we are reallocating a portion of our mid-market investments. The mid-market remains an attractive opportunity for us, but we believe that prioritizing investment upmarket would deliver stronger returns in the current environment. We also believe there are additional ways to serve the mid-market more efficiently through our self-serve channel and other scaled technology-enabled sales and customer service motions. Second, we are optimistic about the opportunity to accelerate legacy app modernization using AI and are investing more in this area. As you recall, we ran a few successful pilots early in this year, demonstrating that AI tooling combined with professional services and our relational migrator product can significantly reduce the time, cost, and risk of migrating legacy applications onto MongoDB. While it's early days, we have observed a more than 50% reduction in the cost to modernize. On the back of these strong early results, additional customer interest is exceeding our expectations. Large enterprises in every industry in GRRP are experiencing acute pain from their legacy infrastructure and are eager for more agile, performant, and cost-effective solutions. Not only are customers excited to engage with us, they also want to focus on some of the most important applications in their enterprise, further demonstrating the level of interest and size of the long-term opportunity. As relational applications encompass a wide variety of database types, programming languages, versions, and other customer-specific variables, we expect modernization projects to continue to include meaningful services engagements in the short and medium term. Consequently, we are increasing our professional services delivery capabilities both directly and through partners. In the long run, we expect to automate and simplify large parts of the modernization process. To that end, we are leveraging the learnings from early service engagements to develop new tools to accelerate future modernization efforts. Although it's early days and scaling our legacy app modernization capabilities will take time, we have increased conviction that this motion will significantly add to our growth in the long term. Third, we are investing to capitalize on our inherent technical advantages as a key component of the emerging AI tech stack. As a reminder, MongoDB is uniquely equipped to query rich and complex data structures typical of AI applications. The ability of a database to query rich and complex data structures is crucial because AI applications often rely on highly detailed, interrelated, and nuanced data to make accurate predictions and decisions. For example, a recommendation system doesn't just analyze a single customer's purchase, but also considers their browsing history, peer group behavior, and product categories, requiring a database that can query and interlink these complex data structures. In addition, MongoDB's architecture unifies source data, metadata, operational data, and vector data in all in one platform, obviating the need for multiple database systems and complex back-end architectures. This enables a more compelling developer experience than any other alternative. From what we see in the AI market today, most customers are still in the experimental stage as they work to understand the effectiveness of the underlying tech stack and build early proof-of-concept applications. However, we are seeing an increasing number of AI apps in production. Today, we have thousands of AI apps on our platforms. What we don't yet see is many of these apps actually achieving meaningful product market fit and therefore significant traction. In fact, as you take a step back and look at the entire universe of AI apps, a very small percentage of them have achieved the type of scale that we commonly see with enterprise-specific applications. We do have some AI apps that are growing quickly, including one that is already a seven-figure workload that has grown 10x since the beginning of the year. Similar to prior platform shifts, as the usefulness of AI tech improves, and becomes more cost-effective, we will see the emergence of many more AI apps that do nail product market fit, but it's difficult to predict when that will happen more broadly. We remain confident that we will capture our fair share of these successful AI applications, as we see that our platform is popular with developers building more sophisticated AI use cases. We continue investing in our product capabilities, including enterprise-grade Atlas Vector Search functionality, to build on this momentum and even better position MongoDB to capture the AI opportunity. In addition, as previously announced, we are bringing search and vector search to our community and EA offerings, leveraging our run-anywhere competitive advantage in the world of AI. Finally, we are expanding our MongoDB AI Applications Program, or MAP, which helps enterprise customers build and bring AI applications into production by providing them with reference architectures, integrations with leading tech providers, and coordinated services and support. Last week, we announced a new cohort of partners, including McKinsey, Confluent, Capgemini, and Instructored, as well as a collaboration with Meta to enable developers to build AI-enriched applications on MongoDB using Llama. Next, I'd like to provide you with a brief product update. At our .local Developer Conference in London in October, we announced the general availability of MongoDB 8.0, the fastest and most performant version of MongoDB ever. MongoDB 8.0 performs 20% to 60% better against common industry benchmarks compared to our prior version, and is built to exceed our customers' most stringent security, resiliency, availability, and performance requirements. To best serve our customers, we regularly review and reprioritize investments in our product portfolio to ensure we're allocating our resources to products with the highest demand from our customers. And to do that, we also deprecate products that are not showing results we desire. Consequently, we made the decision to consolidate our Atlas serverless offerings With our smallest dedicated tiers to create Atlas Flex customers, a new offering with a simpler architecture that provides the elasticity features akin to serverless, we will begin migrating effective customers to the single simple entry-level solution in Q4. We also decided to deprecate Atlas Device Sync and other capabilities not widely adopted in order to focus our engineering resources on the core platform. While these reprioritization decisions are not made lightly, they allow us to deliver the most value to the largest number of customers reinforcing our commitment to being the best modern database and helping us to grow faster. Now I'd like to spend a few minutes reviewing the adoption trends of MongoDB across our customer base. Customers across industries and around the world are running mission-critical projects in MongoDB Atlas, leveraging the full power of our developer data platform, including Financial Times, CarGurus, and Victoria's Secret. As part of the digital transformation journey, global specialty retailer Victoria's Secret and Company migrated its e-commerce platform to MongoDB Atlas. As a fully managed platform, MongoDB Atlas allowed the company to simplify its architecture and improve performance, supporting the retail to provide a resilient, secure, and fast web and mobile e-commerce experience for their millions of customers around the world. Allianz, Alphamod, Swiss Post, and Paylocity are turning to MongoDB to modernize applications. Paylocity, a leading provider of cloud-based payroll and human capital management software, selected MongoDB to power a proprietary application aimed at fostering employee connections and engagement. When traffic increased and the original SQL-based solution was unable to keep up with the required performance metrics, Pielasi migrated to MongoDB Atlas to take advantage of the flexible schema architecture, performance, and scalability. MongoDB costs five times less than the previous SQL database solution, and the company's developers can now create an application within minutes, something that used to take weeks. Mature companies and startups alike are using MongoDB to help deliver the next wave of AI-powered application to their customers, including NerdWallet, Cisco, and Tealbook. Tealbook, a supplier intelligence platform, migrated from Postgres, PG Vector, and Elasticsearch to MongoDB to eliminate technical debt and consolidate their tech stack. The company experienced workload isolation and scalability issues in PG Vector and were concerned with the search index inconsistencies, which were all resolved with the migration to MongoDB. With Atlas Vector Search and dedicated search nodes, Tealbook has realized improved cost efficiency and increased scalability for the supplier data platform, an application that uses GenAI to collect, verify, and enrich supplier data across various sources. In summary, we had a healthy Q3 with both Atlas and EA exceeding expectations. We saw a strong new business quarter, and we remain confident in our ability to become an increasing strategic provider in our large and growing market. Looking forward, we see a great opportunity to grow our adoption in the enterprise through new workloads, modernizing legacy applications, and winning the next generation of AI-powered applications. I would like to finish by providing an update on our senior leadership. First, as we announced early in the press release, after nearly 10 years, Michael Gordon has made the decision to leave MongoDB. Michael has been instrumental in MongoDB's success over the past decade, leading our successful IPO, helping us grow our revenue nearly 50-fold, and successfully scaling our business model to generate meaningful operating leverage. He has been a trusted advisor and business partner to the board and me over the years, and also has become a personal friend. Michael is excited to take a well-deserved break. We have commenced the search for Michael's replacement and will be evaluating both internal and external candidates. One of Michael's proudest accomplishments has been building a world-class finance team under his leadership, and I'm confident that we will not miss a beat during this transition. Michael will continue to serve as CFO through January 31st to help us finish the fiscal year and then will transition to an advisor to the company to ensure a seamless process. If you have not named Michael's successor by fiscal year end, Serge Tanga, SEP of Finance, will serve as interim CFO beginning on February 1st. Second, we are promoting Cedric Pesch, currently our Chief Revenue Officer to the newly created role of President Worldwide Field Operations. In this new position, Cedric will oversee all our field-based customer-facing, and go-to-market enablement teams, including professional services. We believe this org structure will best enable us to execute on some of the key strategic initiatives I discussed earlier, in particular, our increased focus on upmarket and the app modernization opportunity. I would like to congratulate Cedric on this well-deserved promotion. With that, let me turn the call over to Michael.