MongoDB Inc (MDB) 2024 Q4 法說會逐字稿

Thank you for standing by, and welcome to MongoDB's Q4 FY 2024. (Operator Instructions). I will now turn the conference over to your host, Mr. Brian Denyeau, go ahead.

感謝您的耐心等待，歡迎來到 MongoDB 2024 財年第四季。（操作員說明）。現在我將把會議交給東道主布萊恩·德尼奧先生，請繼續。

Thanks. 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 close of market today. Joining me on the call today are Dev Ittycheria, President and CEO of MongoDB; and Michael Gordon, MongoDB's COO and CFO. During this call, we will make forward-looking statements, including statements related to our market and our 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.

謝謝。下午好，感謝您今天與我們一起回顧 MongoDB 2024 年第四季度財務業績，我們在今天收盤後發布的新聞稿中宣布了這一結果。今天和我一起參加電話會議的是 MongoDB 總裁兼執行長 Dev Ittycheria；以及 MongoDB 營運長兼財務長 Michael Gordon。在本次電話會議中，我們將做出前瞻性陳述，包括與我們的市場和未來成長機會相關的陳述；我們對2025財年宏觀經濟環境的預期以及人工智慧的影響；我們產品平台的優勢；我們的競爭格局；客戶行為；我們的財務指導；以及我們計劃的投資。這些陳述受到各種風險和不確定性的影響，包括導致實際結果與我們的預期有重大差異的營運結果和財務狀況。

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 October 31, 2023 filed with the SEC on December 7, 2023. Any forward-looking statements on 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 a reconciliation of these measures to the most directly comparable GAAP financial measures. With that, I'd like to turn the call over to Dev.

有關可能影響我們實際業績的重大風險和不確定性的討論，請參閱我們於 2023 年 12 月 7 日向 SEC 提交的截至 2023 年 10 月 31 日的季度 10-Q 表格季度報告中所述的風險。本次電話會議的前瞻性陳述僅反映我們截至今天的觀點，我們不承擔更新這些陳述的義務，除非法律要求。此外，我們將在本次電話會議上討論非公認會計準則財務指標。請參閱我們網站投資者關係部分收益發布中的表格，以了解這些指標與最直接可比較的 GAAP 財務指標的對帳情況。有了這個，我想把電話轉給 Dev。

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.

謝謝布萊恩，也謝謝大家今天加入我們。我很高興地向大家報告，我們又一個強勁的季度為令人印象深刻的一年畫上了圓滿的句號，因為我們繼續出色地執行以抓住巨大的市場機會。我將首先回顧我們第四季度和全年的業績，然後再向您提供更廣泛的公司最新情況。

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.

從第四季開始，我們的營收達到 4.58 億美元，年成長 27%，高於我們指導的上限。 Atlas 營收年增 34%，佔總營收的 68%。我們的非 GAAP 營業收入為 6,920 萬美元，非 GAAP 營業利潤率為 15%，本季末我們擁有超過 47,800 名客戶。總體而言，我們對第四季的表現感到滿意。

We had a healthy quarter of new business led by continued strength in new workload acquisitions 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 strong consumption -- 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.

由於現有 Atlas 客戶新工作負載獲取的持續強勁，我們的新業務季度表現良好。此外，我們的企業高級業務再次超出了我們的預期，證明了對我們平台的強勁需求以及我們隨處運行策略的吸引力。接下來是 Atlas 消費趨勢。該季度的表現符合我們的預期，我們看到了強勁的消費——比去年第四季更強勁的消費。邁克爾將更詳細地討論消費趨勢。最後，第四季的保留率仍然很高，增強了我們產品的品質和我們平台的任務關鍵性。

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 start-ups 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 continue to innovate on our go-to-market motion to drive workload acquisition. As we look into fiscal '25, let me share what -- share with you what I see in the market.

回顧 24 財年的整體情況，我為我們所取得的成就感到自豪。我們實現了 31% 的營收成長和 16% 的非 GAAP 營業利潤率，遠高於我們最初的預期。 Atlas 年比成長 37%，我們增加了 7,000 多家客戶，從人工智慧新創公司到財富 500 強公司。今年我們發布了創紀錄的快節奏創新產品，例如向量搜尋、可查詢加密和 Atlas 串流處理預覽版，這強化了為什麼如此多的客戶和開發人員選擇 MongoDB 的開發人員資料平台。最後，我們繼續對上市行動進行創新，以推動工作負載的取得。當我們展望 25 財年時，讓我與大家分享一下我在市場上看到的情況。

First, I'm excited to you to win new business. In today's digital world, customers express their business strategy through software. This software equals 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 till 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 growth -- this stable usage growth across our portfolio of workloads.

首先，我很高興您贏得新業務。在當今的數位世界中，客戶透過軟體表達他們的業務策略。該軟體等於策略，公司可以做出的最重要的投資之一就是提高軟體開發人員的生產力。因此，客戶傾向於將 MongoDB 作為下一代開發人員資料平台標準。其次，我預計明年消費成長將保持穩定。 Atlas 消費趨勢現已穩定幾個季度，與 23 財年相比，24 財年的消費波動較小。最終，Atlas 消費的主要驅動力是底層應用程式使用量的成長，而且我們看到了穩定的成長——我們的工作負載組合中的這種穩定的使用量成長。

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 days of the Internet era. To put things in context, it's important to understand that there are 3 layers to the AI stack. The first layer is the underlying compute and LLMs, the second layers of fine-tuning of models and building of AI applications. And the third layer is deploy and running applications that end users interact with. MongoDB 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.

第三，雖然我堅信人工智慧將成為 MongoDB 長期成長的重要驅動力，但我們正處於人工智慧的早期階段，類似於網路時代的撥號時代。為了將事情放在上下文中，了解 AI 堆疊分為 3 層非常重要。第一層是底層運算和法學碩士，第二層是模型微調和人工智慧應用程式建構。第三層是部署和運行最終用戶與之互動的應用程式。 MongoDB 的策略是在第二層和第三層運行，使客戶能夠在任何運算基礎設施上使用自己的專有資料以及任何 LLM（封閉或開源）來建立 AI 應用程式。

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 workloads. We expect that 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.

如今，絕大多數人工智慧支出都發生在第一層，也就是用於訓練和運行法學碩士的運算投資，這也不是我們競爭的領域。如今，我們的企業客戶在很大程度上仍處於建立初始人工智慧應用程式的實驗和原型設計階段，首先專注於透過自動化現有工作負載來提高效率。我們預期企業大規模部署生產工作負載需要時間。然而，當組織希望實現這些人工智慧投資的全部好處時，他們將轉向像 MongoDB 這樣的公司，在人工智慧堆疊的上層提供差異化的功能。

Similar to what happened in the Internet area -- 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 autogenerated animations for personalized marketing campaigns.

與網路領域發生的情況類似，在這個時代，利用內建網路基礎設施提供服務和應用程式的公司會隨著時間的推移而累積價值，隨著客戶建立人工智慧應用程式以提高有意義的營運效率，創造引人注目的客戶體驗，MongoDB 等平台將受益。並尋求新的成長機會。我們已經看到我們的平台與創新人工智慧新創公司產生了共鳴，他們為用例構建了令人興奮的應用程序，例如用於個人化醫療的即時患者診斷、用於緩解風險的網路威脅數據分析、海上船隊的預測性維護以及用於個人化行銷活動的自動生成動畫。

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 went to 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 to cloud players. They offer a wide array of database options, relational and nonrelational and benefit from their 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 avoid lock-in and MongoDB's popularity among developers all around the world.

最後，我們的競爭地位越來越強。我們的勝率在所有競爭對手中仍然很高。我們很少與遺留資料庫供應商競爭，因為企業知道他們需要擺脫低效且脆弱的遺留技術。我們也很少選擇利基資料庫廠商，因為客戶對單點解決方案的激增感到不知所措，這些解決方案難以管理且增加的價值有限。我們的主要競爭仍然是雲端廠商。它們提供廣泛的資料庫選項（關係型和非關係型），並受益於其規模和覆蓋範圍。由於我們的文件架構的靈活性和可擴展性、我們的開放平台可以在任何地方運行並避免鎖定以及 MongoDB 在世界各地開發人員中的受歡迎程度，我們能夠很好地與這些參與者競爭。

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.

最後，當您查看我們的新產品時，我們會發現與這些市場中的老牌企業競爭時取得了更大的成功。我們發現核心資料庫市場也適用同樣的原則。客戶不想管理無數的單點解決方案，而是更喜歡與策略性供應商整合支出，特別是在當前註重成本的環境中。總之，我們預期 25 財年的環境將與我們在 24 財年所經歷的環境大致相似。

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 and performance and scalability in the AI-enabled world. In addition, we will continue maturing our 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 a 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.

在此背景下，讓我告訴大家我們明年的優先事項是什麼。首先，我們將繼續在核心資料庫中發揮我們的產品優勢，因為我們相信客戶將在人工智慧支援的世界中給予更高的溢價、效能和可擴展性。此外，我們將繼續完善我們的新產品，包括向量搜尋的附加功能、Atlas 流處理的 GA 以及其他產品的增強功能。其次，我們將繼續專注於新工作負載的獲取，將其作為我們業務的關鍵長期驅動力。我們將繼續微調激勵措施，以確保我們整個行銷組織專注於識別和尋找新的工作負載機會。此外，我們將利用我們的專業知識和從自助服務業務中學到的知識，使用產品主導的成長技術來增加我們現有大型企業帳戶中其他開發團隊對 Atlas 的採用。

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 underpenetrated 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 customers. 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 locking the relational migration opportunity. To remind everyone, there are 3 elements to migrating an application: transforming the schema, moving the data and rewriting the application code.

三是著力提升銷售能力。正如我們過去告訴過您的那樣，由於宏觀不確定性，我們在 24 財年的產能增長緩慢，尤其是上半年。鑑於市場現在更加穩定，與我們的機會相比，我們的滲透率仍然不足，我們將在 25 財年加快市場投資的步伐。第四，我們將繼續投資，成為更多客戶的標準。我們打算將策略客戶計畫的規模擴大一倍，並在最大的客戶中大幅擴展以客戶為基礎的行銷工作。最後，我們仍然專注於鎖定關係遷移機會。提醒大家，遷移應用程式有3個要素：轉換架構、行動資料和重寫應用程式程式碼。

Our current relational migrator offering is designed to automate large parts of the first 2 elements, but rewriting application code is the most manually intensive element. Gen AI 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 products 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.

我們目前的關係遷移器產品旨在自動化前兩個元素的大部分，但重寫應用程式程式碼是手動最密集的元素。 Gen AI 預計將大幅降低重寫應用程式程式碼的成本和時間。我們將繼續將人工智慧功能建置到關係遷移器中，但我們認為最終解決方案將是產品和服務的組合。今年，我們正在投資一些試點項目，利用人工智慧進行關係遷移，並結合服務來大幅簡化和擴展流程。

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.

現在我想花幾分鐘回顧 MongoDB 在我們客戶群中的採用趨勢。全球各行各業的客戶都在 MongoDB Atlas 上運行關鍵任務項目，充分利用我們開發者資料平台的全部功能，包括 ZF、福布斯和瑞士聯邦鐵路。

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-premises 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.

採埃孚(ZF) 是一家為乘用車、商用車和工業技術提供系統的全球科技公司，需要一個具有廣泛功能的中央資料庫解決方案來支援連接到採埃孚基礎設施的超過300,000 輛商用車。 ZF 最初於 2014 年開始在本地使用 MongoDB，並遷移到 MongoDB Atlas，以實現其新車隊編排解決方案背後的架構現代化。團隊現在使用時間序列和線上存檔來減少整體資料儲存大小，並使用 MongoDB Atlas Search 來管理索引，使用 Atlas Charts 來顯示計費資訊。隨著無人機和自動駕駛汽車等創新技術不斷進入市場，MongoDB 的開發者資料平台使採埃孚能夠更快地發布新功能。

[Even PicPay] and Anywhere Real Estate are examples of customers turning to MongoDB to free up the developers' 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 & Gardens, Century 21, Coldwell 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.

[甚至 PicPay] 和 Anywhere Real Estate 都是客戶轉向 MongoDB 的例子，以釋放開發人員的創新時間，同時實現顯著的成本節省。 Anywhere Real Estate 是住宅房地產服務的全球領導者，其品牌組合包括Better Homes & Gardens、Century 21、Coldwell Banker、Corcoran、ERA、Sotheby's International Realty，該公司正在利用MongoDB Atlas 和Atlas Search 來大幅增強其搜尋能力。他們之前的解決方案成本太高，而且維護起來操作繁重。現在，借助 Atlas Search，他們可以從數百個 MLS 來源獲取數據，聚合數據，並為客戶提供搜尋解決方案，有效提供準確和最新的信息，從而節省時間並降低成本。

Anywhere is also exploring the use of Atlas Vector Search to provide semantic search and Gen AI features to millions of consumers. Samsung Electronics, ArcelorMittal 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 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 data re-latency was reduced from 3 seconds to 18 milliseconds, significantly improving availability and developer productivity.

Anywhere 也正在探索使用 Atlas Vector Search 為數百萬消費者提供語意搜尋和 Gen AI 功能。三星電子、安賽樂米塔爾和公民銀行正在轉向 MongoDB 來實現應用程式現代化。三星電子數位家電部門從先前的 MySQL 資料庫過渡到 MongoDB Atlas，以更有效地管理家電資料。透過利用 MongoDB 的文檔模型，三星智慧家庭服務可以從團隊的人工智慧家電中收集即時數據，並將其用於各種數據驅動的計劃，例如培訓人工智慧服務。他們遷移到 MongoDB Atlas 將回應時間縮短了 50% 以上，資料重新延遲從 3 秒減少到 18 毫秒，顯著提高了可用性和開發人員的工作效率。

Let me wrap up by saying that I remain highly confident about our ability to execute on our 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 contribute to establish MongoDB as a standard in enterprise accounts.

最後，我要說的是，我對我們執行長期成長機會的能力仍然充滿信心。我們正在尋求所有軟體中最大和成長最快的市場之一，並在新客戶和現有客戶帳戶中提供巨大的擴展機會。雖然現在還處於早期階段，但我們預計人工智慧不僅將支援市場的整體成長，還將迫使客戶重新審視其遺留工作負載並建立更雄心勃勃的應用程式。這將使我們能夠贏得更多新的和現有的工作負載，並最終為將 MongoDB 建立為企業帳戶的標準做出貢獻。

Before I turn it over to Michael, I would like to personally invite all of you to attend the investor session at MongoDB.local NYC to be held at the Javits Center on May 2. Please e-mail ir@mongodb.com if you're interested in attending. With that, here's Michael.

在將其交給 Michael 之前，我想親自邀請大家參加 MongoDB.local NYC 將於 5 月 2 日在賈維茨中心舉行的投資者會議。如果您願意，請發送電子郵件至 ir@mongodb.com有興趣參加。麥可就是這樣。

Thanks, Dev. As mentioned, we delivered a strong performance in the fourth quarter, both financially and operationally. I'll begin with a detailed review of our fourth quarter results and then finish with our outlook for the first quarter and full fiscal year 2025. First, I'll start with our fourth quarter results. Total revenue in the quarter was $458 million, up 27% year-over-year and above the high end of our guidance. As Dev mentioned, we had another quarter of healthy new business acquisition, demonstrating our product market fit and the mission criticality of our platform.

謝謝，德夫。如前所述，我們在第四季度在財務和營運方面均取得了強勁的業績。我將首先詳細回顧我們第四季的業績，然後結束我們對第一季和 2025 財年的展望。首先，我將從我們第四季的業績開始。本季總營收為 4.58 億美元，年增 27%，高於我們指引的上限。正如 Dev 所提到的，我們又一個季度進行了健康的新業務收購，展示了我們的產品市場契合度和平台的任務關鍵性。

Shifting to our product mix. Let's start with Atlas. Atlas grew 34% in the quarter compared to the previous year and now represents 68% of total revenue, compared to 65% in the fourth quarter of fiscal 2023 and 66% last quarter. We recognize Atlas revenue primarily based on customer consumption of our platform, and that consumption is closely related to end-user activity of the application. As a reminder, in Q4 of fiscal '23, we had a higher-than-normal amount of revenue from unused commitments, making this a tough year-over-year comparison. Excluding the impact of unused commitments, Atlas year-over-year growth in Q4 was in line with the growth that we observed in Q3.

轉向我們的產品組合。讓我們從阿特拉斯開始。 Atlas 本季較上年成長 34%，目前佔總營收的 68%，而 2023 財年第四季為 65%，上季為 66%。我們主要根據我們平台的客戶消費來確認 Atlas 收入，而該消費與應用程式的最終用戶活動密切相關。提醒一下，在 23 財年第四季度，我們未使用承諾的收入高於正常水平，這使得與去年同期的比較變得困難。排除未使用承諾的影響，Atlas 第四季度的同比增長與我們在第三季度觀察到的增長一致。

Let me provide some additional context on Atlas consumption in the quarter. As we shared in our guidance last quarter, we were expecting consumption to be impacted by the seasonal slowdown in Q4 around the holidays. Week-over-week consumption growth in Q4 was stronger than in Q4 of last year and in line with our expectations. We've seen less consumption variability this year and so, as in Q3, we forecasted less of a seasonal impact than in prior years. And that's exactly what we saw. Turning to non-Atlas revenue, EA exceeded our expectations in the quarter, and we continue to have success selling incremental workloads into our existing EA customer base. Ongoing EA strength speaks to the appeal and success of our run anywhere strategy. The EA revenue outperformance was in part a result of more multiyear deals than we had expected. As a reminder, the term license component for multiyear deals is recognized as upfront revenue at the start of the contract and therefore, includes term license revenue related to future years.

讓我提供一些有關本季度 Atlas 消費的其他背景資訊。正如我們在上季度的指引中所分享的那樣，我們預計消費將受到第四季度假期期間季節性放緩的影響。第四季消費環比成長強於去年第四季，符合我們的預期。我們今年的消費波動較小，因此，與第三季一樣，我們預測季節性影響將小於往年。這正是我們所看到的。談到非 Atlas 收入，EA 在本季度超出了我們的預期，我們繼續成功地將增量工作負載銷售給現有的 EA 客戶群。持續不斷的 EA 實力證明了我們隨處運作策略的吸引力和成功。 EA 收入表現優異的部分原因是多年期交易數量超出了我們的預期。提醒一下，多年交易的定期許可部分在合約開始時被確認為預付款收入，因此包括與未來幾年相關的定期許可收入。

Turning to customer growth. During the fourth quarter, we grew our customer base by approximately 1,400 customers sequentially, bringing our total customer count to over 47,800 which is up from over 40,800 in the year ago period. Of our total customer count, over 7,000 are direct sales customers which compares to over 6,400 in the year ago period. The growth in our total customer count is being driven primarily by Atlas, which had over 46,300 customers at the end of the quarter, compared to over 39,300 in the year ago period. It's important to keep in mind that the growth of our Atlas customer count reflects new customers to MongoDB in addition to existing EA customers adding incremental Atlas workloads. Moving on to ARR, we had another quarter with our net ARR expansion rate above 120%. We ended the quarter with 2,052 customers with at least $100,000 in ARR and annualized MRR, which is up from 1,651 in the year ago period. We also finished the year with 259 customers spending $1 million or more annualized on our platform compared to over 213 a year ago.

轉向客戶成長。第四季度，我們的客戶群連續增加了約 1,400 名客戶，使我們的客戶總數超過 47,800 名，高於去年同期的 40,800 名。在我們的客戶總數中，有 7,000 多名直銷客戶，而去年同期為 6,400 多名。我們客戶總數的成長主要是由 Atlas 推動的，截至本季末，Atlas 擁有超過 46,300 名客戶，而去年同期為 39,300 多名。請務必記住，Atlas 客戶數量的成長反映了 MongoDB 的新客戶以及現有 EA 客戶增加的 Atlas 工作負載。接下來的 ARR 方面，我們又一個季度的淨 ARR 擴張率超過 120%。本季末，我們有 2,052 名客戶的 ARR 和年化 MRR 至少為 100,000 美元，高於去年同期的 1,651 名。去年年底，我們的平台上有 259 名客戶每年消費金額達到或超過 100 萬美元，而一年前這一數字超過 213 名。

Moving down the income statement, I'll be discussing our results on a non-GAAP basis unless otherwise noted. Gross profit in the fourth quarter was $353.6 million, representing a gross margin of 77% which is down from 78% in the year ago period. As we said at the time, our gross margin in the year-ago period reflected a onetime benefit of roughly 2.5 percentage points related to one of our cloud partner contracts.

向下移動損益表，除非另有說明，我將在非公認會計原則的基礎上討論我們的表現。第四季毛利為3.536億美元，毛利率為77%，低於去年同期的78%。正如我們當時所說，我們去年同期的毛利率反映了與我們的一份雲端合作夥伴合約相關的約 2.5 個百分點的一次性收益。

Our income from operations was $69.2 million or a 15% operating margin for the fourth quarter compared to a 10% margin in the year ago period. Our strong bottom line results demonstrate the significant operating leverage in our model and are a clear indication of the strength in our underlying unit economics. The primary reason for operating income results versus guidance is our revenue outperformance. Net income in the fourth quarter was $71.1 million or $0.86 per share based on 82.9 million diluted weighted average shares outstanding. This compares to net income of $46.4 million or $0.57 per share on 80.8 million diluted weighted average shares outstanding in the year ago period.

第四季我們的營運收入為 6,920 萬美元，營運利潤率為 15%，而去年同期的營運利潤率為 10%。我們強勁的獲利結果證明了我們模型中的顯著營運槓桿，並清楚地表明了我們基礎單位經濟效益的實力。營業收入結果與指導相比的主要原因是我們的收入表現優異。第四季淨利為 7,110 萬美元，即每股 0.86 美元，基於 8,290 萬股稀釋加權平均流通股計算。相比之下，去年同期淨收入為 4,640 萬美元，即 8,080 萬股稀釋加權平均已發行股票的每股淨收入為 0.57 美元。

Turning to the balance sheet and cash flow. We ended the fourth quarter with $2 billion in cash, cash equivalents, short-term investments and restricted cash. Operating cash flow in the fourth quarter was $54.6 million and $121.5 million for the full fiscal year 2024. After taking into consideration approximately $4.1 million in capital expenditures, and principal repayments of finance lease liabilities, free cash flow was $50.5 million in the quarter. This compares to free cash flow of $23.8 million in the fourth quarter of fiscal 2023. For the full fiscal year '24, free cash flow was $109.9 million compared to negative $24.7 million in fiscal '23.

轉向資產負債表和現金流量。截至第四季末，我們擁有 20 億美元的現金、現金等價物、短期投資和限制性現金。第四季的營運現金流為5,460 萬美元，2024 年全年營運現金流為1.215 億美元。考慮到約410 萬美元的資本支出和融資租賃負債的本金償還後，該季度的自由現金流為5050 萬美元。相較之下，2023 財年第四季的自由現金流為 2,380 萬美元。24 財年的自由現金流為 1.099 億美元，而 23 財年為負 2,470 萬美元。

I'd now like to turn to our outlook for the first quarter and full fiscal year 2025. For the first quarter, we expect revenue to be in the range of $436 million to $440 million. We expect non-GAAP income from operations to be in the range of $22 million to $25 million and non-GAAP net income per share to be in the range of $0.34 to $0.39 based on 83.8 million estimated diluted weighted average shares outstanding. For the full fiscal year 2025, we expect revenue to be in the range of $1.9 billion to $1.93 billion, non-GAAP income from operations to be in the range of $186 million to $201 million and non-GAAP net income per share to be in the range of $2.27 to $2.49 based on 85.1 million estimated diluted weighted average shares outstanding. Note that the non-GAAP net income per share guidance for the first quarter and full fiscal year 2025 includes a non-GAAP tax provision of approximately 20%.

現在我想談談我們對 2025 年第一季和整個財年的展望。我們預計第一季的營收將在 4.36 億美元至 4.4 億美元之間。我們預計非 GAAP 營運收入將在 2,200 萬美元至 2,500 萬美元之間，非 GAAP 每股淨利潤將在 0.34 美元至 0.39 美元之間，基於 8,380 萬股估計稀釋加權平均流通股。對於 2025 年整個財年，我們預計收入將在 19 億美元至 19.3 億美元之間，非 GAAP 營運收入將在 1.86 億美元至 2.01 億美元之間，非 GAAP 每股淨利潤將在範圍為2.27 美元至2.49 美元，基於估計的8,510 萬股稀釋加權平均已發行股票。請注意，2025 年第一季及整個財年的非 GAAP 每股淨利指引包括約 20% 的非 GAAP 稅務撥備。

I'll now provide some more context on our guidance, starting with the full year fiscal '25 where we're facing difficult compares in 2 ways. First, we expect to recognize close to 0 revenue from unused Atlas commitments in fiscal '25 compared to over $40 million in fiscal '24. As you may recall, in fiscal '24, we changed our sales incentive structure to reduce the importance of upfront commitments, and so we saw far fewer upfront commitments. Therefore, as those fiscal '24 deals come up for renewal in fiscal '25, we expect to see limited revenue related to unused commitments. Second, in fiscal '24, we recognized approximately $40 million more in multiyear license revenue than we did in fiscal '23. As you know, our fiscal year '24 non-Atlas revenue benefited from a higher-than-usual amount of license revenue related to pay year contracts, including our extended partnership with Alibaba. Clearly, we are pleased with the fiscal '24 performance, but it was unusual in terms of the magnitude of multiyear deals and we don't expect similar performance in fiscal '25. As a result, we expect non-Atlas revenues to be modestly down in fiscal '25. Next, we expect Atlas consumption growth to be in line with the consumption growth we've experienced in fiscal '24.

我現在將提供有關我們指導的更多背景信息，從 25 財年全年開始，我們在兩個方面面臨著困難的比較。首先，我們預計 25 財年未使用的 Atlas 承諾的收入將接近 0，而 24 財年則超過 4,000 萬美元。您可能還記得，在 24 財年，我們改變了銷售激勵結構，以降低預先承諾的重要性，因此我們看到的預先承諾要少得多。因此，隨著這些 24 財年交易在 25 財年續簽，我們預計與未使用承諾相關的收入將有限。其次，在 24 財年，我們確認的多年授權收入比 23 財年多了約 4,000 萬美元。如您所知，我們 24 財年的非 Atlas 收入受益於與發薪年合約相關的授權收入高於平常，包括我們與阿里巴巴的長期合作夥伴關係。顯然，我們對 24 財年的業績感到滿意，但就多年交易的規模而言，這是不尋常的，我們預計 25 財年不會有類似的業績。因此，我們預計 25 財年非 Atlas 營收將小幅下降。接下來，我們預期 Atlas 消費成長將與我們在 24 財年經歷的消費成長保持一致。

Finally, I want to provide some context to better understand our operating margin guidance. The $80-plus million of fiscal '24 revenue that won't repeat for fiscal '25 was very high margin, making for an exceptionally tough operating margin compare. In addition, as we mentioned in the past, in fiscal '24, we began increasing our pace of hiring relatively late in the year. So the full cost from those investments will impact our fiscal '25 operating margin. We're expecting headcount growth in the mid-teens versus 9% growth in fiscal '24. And as Dev mentioned, we are prioritizing growth in sales production capacity. Consequently, we expect to see a year-over-year operating margin decline while still delivering 500 basis points of margin expansion on a 2-year basis. We believe this is the most appropriate way to understand our continued margin progression.

最後，我想提供一些背景信息，以更好地理解我們的營業利潤率指導。 24 財年營收超過 8,000 萬美元的利潤率非常高，而 25 財年不會出現這種情況，因此營運利潤率的比較異常艱難。此外，正如我們過去提到的，在 24 財年，我們在今年相對較晚的時候開始加快招募步伐。因此，這些投資的全部成本將影響我們 25 財年的營業利益率。我們預計員工人數將成長 10%左右，而 2024 財年的成長率將達到 9%。正如 Dev 所提到的，我們優先考慮銷售產能的成長。因此，我們預計營業利潤率將年減，但兩年利潤率仍將成長 500 個基點。我們相信這是了解我們持續的利潤成長的最合適的方式。

Moving on to our Q1 guidance, a few things to keep in mind. First, we expect Atlas revenue to be flat to slightly down sequentially. Q1 has 2 fewer days than Q4 this year, which represents a revenue headwind. Also the slower Atlas consumption growth during the holidays will have a bigger impact on Q1 revenue than it did in Q4, thereby negatively impacting sequential revenue growth. Finally, the sequential impact from the expected decline in unused Atlas commitments will be most pronounced in Q1, given that we made the changes in Q1 of last year.

繼續我們的第一季指導，需要記住一些事情。首先，我們預計 Atlas 收入將持平或略有下降。今年第一季比第四季少了 2 天，代表著收入的逆風。此外，假期期間Atlas消費成長放緩將對第一季營收產生比第四季更大的影響，從而對環比收入成長產生負面影響。最後，鑑於我們在去年第一季做出了改變，未使用的 Atlas 承諾預期下降的連續影響將在第一季最為明顯。

Second, we expect to see a meaningful sequential decline in EA revenue. As discussed in past years, Q4 is our seasonally highest quarter in terms of our EA renewal base which is an excellent indicator of our ability to win new EA business. In Q1, the EA renewal base is sequentially much lower.

其次，我們預期 EA 收入將出現顯著的環比下降。正如過去幾年所討論的，第四季度是我們 EA 續約基數方面季節性最高的季度，這是我們贏得新 EA 業務能力的絕佳指標。在第一季度，EA 續訂基數連續低得多。

Finally, we expect operating income to decline sequentially due to lower revenue as well as our increased pace of hiring. To summarize, MongoDB delivered strong fourth quarter results, we're pleased with our ability to win new business and see stable consumption trends in Atlas. We remain incredibly excited about the opportunity ahead, and we'll continue to invest responsibly to maximize our long-term value. With that, we'd like to open it up to questions. Operator?

最後，由於收入下降以及招聘步伐加快，我們預計營業收入將環比下降。總而言之，MongoDB 在第四季度取得了強勁的業績，我們對贏得新業務並在 Atlas 中看到穩定的消費趨勢的能力感到高興。我們對未來的機會仍然感到非常興奮，我們將繼續負責任地投資，以最大限度地提高我們的長期價值。至此，我們願意接受提問。操作員？

(Operator Instructions). Our first question comes from the line of Sanjeet Singh of Morgan Stanley.

（操作員說明）。我們的第一個問題來自摩根士丹利的桑吉特辛格。

Michael, I wanted to walk through the guidance with you a little bit. This time last year coming out of Q4 '23, I think there was a pretty different environment, a much more cautious environment. I think usage growth was particularly impacted in the outlook last year. This year, coming into fiscal year '25, things feel a little bit healthier or at least stable in sort of on how you guys are framing it. And yet the guidance -- the initial guidance for growth looks a lot like the initial guidance growth for last year. Just trying to understand, and I know you talked about some of the onetime impacts from last year. But just in terms of a better spending environment versus the initial guide that looks also pretty similar to the last year, could you sort of frame out like being conservative in things you have embedded in guidance.

邁克爾，我想和你一起逐步完成該指南。去年這個時候，從 23 年第四季開始，我認為當時的環境非常不同，一個更謹慎的環境。我認為去年的使用量成長尤其受到前景的影響。今年，進入第 25 財年，從你們的框架來看，事情感覺有點健康，或至少穩定了。然而，最初的成長指導看起來很像去年的最初成長指導。只是想了解一下，我知道您談到了去年的一些一次性影響。但就更好的支出環境而言，與看起來也與去年非常相似的最初指南相比，您是否可以在指南中嵌入的內容中採取保守態度。

Yes. So a couple of things. Thanks for the question. Yes, I think the key thing is, once you adjust for those onetime items that we called out, we see a stable environment. That's what we described in and experienced in Q4 compared to Q3. So we feel good about that. I think just to underscore, there's the $80 million in revenue that won't repeat both from the unused commitments as well as from the multiyear deals. And when you adjust from those, we feel good about the dynamic. To your question, which is sort of embedded in that around sort of, I'll call it, guidance approach or approach to guidance. We haven't changed our view as it relates to guidance. We have seen more stable consumption that obviously gives us higher confidence in part, given the less variability that we've seen over the course of fiscal '24.

是的。有幾件事。謝謝你的提問。是的，我認為關鍵是，一旦你調整了我們提出的那些一次性項目，我們就會看到一個穩定的環境。這就是我們在第四季與第三季相比所描述和經歷的。所以我們對此感覺良好。我想強調的是，8000 萬美元的收入不會從未使用的承諾和多年協議中重複。當你根據這些進行調整時，我們對動態感到滿意。對於你的問題，它有點嵌入在我稱之為指導方法或指導方法的周圍。我們沒有改變我們的觀點，因為這與指導有關。鑑於我們在 24 財年期間看到的波動性較小，我們看到消費更加穩定，這顯然在一定程度上給了我們更高的信心。

I think we also have a better understanding of the underlying seasonality of the business. We had updated at the end of last year in our call -- in our Q3 call around the success that we're having on EA, and we had updated those EA new business assumptions. And so that our guidance reflects kind of continued strength there. So I think that's how we approach it and there are no fundamental changes, but hopefully, we've given you a fair amount of the piece parts so people can help do the math.

我認為我們也對業務的潛在季節性有了更好的了解。去年年底，我們在第三季的電話會議中更新了我們在 EA 上的成功，並且更新了 EA 的新業務假設。因此，我們的指導反映了那裡的持續實力。所以我認為這就是我們的處理方式，沒有根本性的改變，但希望我們已經給了你相當多的零件，這樣人們就可以幫忙做數學計算。

Yes. I really appreciate that. And thank you for breaking out that $80 million between unused commitments and the multiyear term license deals. On the unused commitment side of the house, that $40 million, can you give us a sense of like how that has flowed through to the balance of the year? Obviously, [it sort of it] all came in Q4, but the prior year in Q4, you also mentioned a several million dollar impact to Atlas revenue in that quarter. Was that impact worse or better this year when we think about the unused commitment's contribution to this quarter's Atlas results?

是的。我真的很感激。感謝您在未使用的承諾和多年期許可協議之間突破了 8000 萬美元。在房屋未使用的承諾方面，即 4000 萬美元，您能否讓我們了解一下這部分資金是如何流向今年剩餘時間的？顯然，[有點]全部發生在第四季度，但前一年第四季度，您還提到該季度對 Atlas 收入產生了數百萬美元的影響。當我們考慮未使用的承諾對本季 Atlas 業績的貢獻時，今年的影響是更糟還是更好？

Yes. So I think the key thing is the $40 million will happen over the course of the year. It obviously tracks to the actual contracts. It affects a relatively small number of customers and a small percentage of the commitments. It's a dynamic that goes away over time as we've discussed. We do -- we particularly called out that on a sequential basis, it will be most obvious and most pronounced in Q1 because we're basically hitting the first wave of those renewals where we don't have commits. And so especially as people are trying to do the sequential math, we just wanted to call that out to make sure people sort of understood that dynamic.

是的。所以我認為關鍵是 4000 萬美元將在今年內實現。它顯然追蹤到實際的合約。它影響相對較少數量的客戶和一小部分承諾。正如我們所討論的，這種動態會隨著時間的推移而消失。我們確實這樣做了——我們特別指出，按順序來看，這將在第一季度最為明顯和最明顯，因為我們基本上正處於我們沒有承諾的續訂的第一波浪潮中。因此，特別是當人們試圖進行順序數學時，我們只是想指出這一點，以確保人們理解這種動態。

Our next question is from Raimo Lenschow with Barclays.

我們的下一個問題來自巴克萊銀行的 Raimo Lenschow。

Congrats on a nice Q4. A question also a little bit on guidance. Mike, the last few quarters before Q4, we talked about EA seeing a little bit of a tailwind from customers kind of maybe modernizing on premise rather than doing to Atlas to kind of still modernize but maybe not spending all the money to go to the cloud. Is that trend still valid? And if you think about the multiyear commitments, obviously, you had, what, 10 million, 15 million for the Alibaba deal. But then the other stuff is like customers that are just doing this work. Do you think that will change and people go back to like shorter commitments? Or is it just more that you're kind of thinking about the renewal pool.

恭喜第四季取得了不錯的成績。還有一個關於指導的問題。麥克，在第四季度之前的最後幾個季度，我們談到EA 看到了來自客戶的一點推動力，他們可能會在本地進行現代化，而不是對Atlas 進行現代化，但可能不會花所有的錢去雲上。這種趨勢仍然有效嗎？如果你考慮一下多年的承諾，顯然，你為阿里巴巴的交易付出了 1000 萬、1500 萬美元。但其他的東西就像只是做這項工作的客戶。您認為這種情況會改變嗎？人們會重新喜歡較短的承諾嗎？或者您只是更多地考慮續訂池。

Yes. So a few different things embedded in there. On the multiyear, we've -- it's always been a dynamic. And as we've seen deals or variability, we've tried to call that out and that's why we sort of call out, given under the ASC 606 that increased variability and reduced comparability that comes from EA. Obviously, Atlas has grown as a percentage of the business, but that continues to be the dynamic for the EA portion. I expect that we will continue to see multiyear deals, but we just -- in fiscal '24, it was just so many more than we thought. And to your point, not just EA, but broadly non-Atlas. And it's just -- it's not something that will repeat in fiscal '25. And so that's why we wanted to call it out and quantified it.

是的。所以裡面嵌入了一些不同的東西。多年來，我們一直充滿活力。正如我們所看到的交易或可變性，我們試圖指出這一點，這就是為什麼我們要指出這一點，因為根據 ASC 606，EA 增加了可變性並降低了可比性。顯然，Atlas 在業務中所佔的比例有所增長，但這仍然是 EA 部分的動力。我預計我們將繼續看到多年期交易，但我們只是 - 在 24 財年，它比我們想像的要多得多。就你的觀點而言，不僅僅是 EA，而且廣泛非 Atlas 也是如此。只是——這不會在 25 財年重演。這就是為什麼我們想要指出並量化它。

On the first part of your question on modernization, the way I would think about it is customers all have their own IT strategies, including deployment, including their cloud postures and things like that. That's for them to decide. We want to make MongoDB easy for them to consume. Our run anywhere strategy has proven to be successful and we've seen that in the EA outperformance. And so I think the other thing I'd add is we have increasingly seen people appreciate, even if they are operating in a business or maybe in a regulated environment where they can't fully move to the cloud, where they do want to start to modernize applications and modernize infrastructure. And MongoDB is seen -- and Enterprise Advanced is seen now as an on-ramp to the cloud. Even if you can't fully modernize and put yourself in a public cloud setting, EA can help that because eventually, given the run anywhere strategy, it will make it easier for your ultimate move to the cloud, if that's what you wind up doing.

關於現代化問題的第一部分，我的想法是客戶都有自己的 IT 策略，包括部署、雲端態勢等。這是由他們決定的。我們希望讓他們能夠輕鬆使用 MongoDB。事實證明，我們的隨處運作策略是成功的，我們已經在 EA 的出色表現中看到了這一點。因此，我認為我要補充的另一件事是，我們越來越多地看到人們欣賞，即使他們在企業中運營，或者可能在受監管的環境中運營，他們無法完全遷移到雲，但他們確實想從雲端開始實現應用程式現代化和基礎設施現代化。 MongoDB 和 Enterprise Advanced 現在被視為通往雲端的入口。即使您無法完全現代化並將自己置於公有雲環境中，EA 也可以提供協助，因為最終，考慮到隨處運行策略，它將使您更輕鬆地最終遷移到雲端（如果這就是您最終要做的事情） 。

(Operator Instructions). Our next question comes from the line of Kash Rangan of Goldman Sachs.

（操作員說明）。我們的下一個問題來自高盛的卡什·蘭根（Kash Rangan）。

Congrats on the results. One quick one for Dev and one hopefully will go to Michael as well. Dev, you talked about generative AI applications. You've described the 3-layer architecture. When do you think it hits the sweet spot of how MongoDB is positioned from a timing standpoint? When do these generative AI applications start to really drive underlying need for the kind of databases that you're best suited for?

祝賀結果。一份給 Dev 的快速報告，一份希望也能送給 Michael。 Dev，您談到了產生式人工智慧應用程式。您已經描述了 3 層架構。從時間的角度來看，您認為 MongoDB 的定位何時達到最佳點？這些生成式人工智慧應用程式何時開始真正推動對您最適合的資料庫類型的潛在需求？

One for Michael. In your assumptions, when I take away the $40 million of the upfront, I mean, that's like a couple of percentage points of growth. I'm just trying to understand what kind of consumption trends you are using to build guidance? Was it average of fiscal '24 consumption trends or weighted more towards second half or exiting fourth quarter? Any color there would be tremendously useful. And I also want to ensure the sales force is still selling EA and can get comp for EA because it does not look like you've [see] much weight for EA in your forecast. That's it for me.

一張是給麥可的。在你的假設中，當我扣除 4000 萬美元的預付款時，我的意思是，這相當於增長了幾個百分點。我只是想了解您使用什麼樣的消費趨勢來建立指導？這是 24 財年消費趨勢的平均值，還是下半年或第四季結束時的權重較大？任何顏色都會非常有用。我還想確保銷售人員仍在銷售 EA，並且可以獲得 EA 的補償，因為您在預測中似乎沒有[看到]太多 EA 的權重。對我來說就是這樣。

Thanks, Kash. I'll take the first question. In regards to when we see enterprises deploying AI [apps] in production, I think it's a combination of customers getting comfortable with the technology. And also these technologies maturing, but from both the performance and from a cost point of view, if you played with ChatGPT or any of the other chatbots out there or large language models, you'll know that the performance of these applications you get a response time in the 1 to 2 to 3 seconds, depending on the type of question you're asking. And so naturally, a chatbot is a very simple but easy to understand use case. But to embed that technology into a sophisticated application, making real-time decisions based on real-time data, the performance and to some degree, the cost of these architectures are still not there.

謝謝，卡什。我來回答第一個問題。當我們看到企業在生產中部署人工智慧[應用程式]時，我認為這是客戶對這項技術感到滿意的結果。這些技術也在日趨成熟，但從效能和成本的角度來看，如果您使用過 ChatGPT 或任何其他聊天機器人或大型語言模型，您就會知道這些應用程式的效能回應時間在1 到2 到3 秒之間，取決於您提出的問題類型。自然地，聊天機器人是一個非常簡單但易於理解的用例。但要將這項技術嵌入複雜的應用程式中，根據即時數據、效能以及在某種程度上做出即時決策，這些架構的成本仍然不存在。

Also, customers are still in the learning phase. They're experimenting, they're prototyping. But I would say you're not seeing a lot of customers really deploy AI applications at scale. So I think it's going to take them -- I would say, this year is a year where they're going to do -- probably roll out a few applications, learn. And then as we get more experienced, become more comfortable in rolling out more and more applications as they get -- as both these technologies mature and the costs come down. We feel very good about our positioning because from an architecture point of view, the document model, the flexible schema, the ability to handle real-time data, performance at scale, the unified platform, the ability to handle data, metadata and vector data with the same query language, same semantics, et cetera, is something that makes us very, very attractive.

此外，客戶仍處於學習階段。他們正在試驗，他們正在製作原型。但我想說的是，你並沒有看到很多客戶真正大規模部署人工智慧應用程式。所以我認為他們會——我想說，今年是他們要做的一年——可能會推出一些應用程序，學習。然後，隨著我們經驗的積累，隨著這些技術的成熟和成本的下降，我們會更輕鬆地推出越來越多的應用程式。我們對自己的定位感覺非常好，因為從架構的角度來看，文檔模型、靈活的模式、處理即時資料的能力、大規模效能、統一的平台、處理資料、元資料和向量資料的能力使用相同的查詢語言、相同的語意等等，這讓我們非常非常有吸引力。

The other thing that we're finding is unlike a typical sale where someone is deciding to either build a new workload or modernize a workload, the AI decision is more of a central decision -- centralized decision more than ever. So it allows us to actually go higher in the organization. So we're actually engaging with customers at much more senior levels because, obviously, this is coming down as a top-down initiative. And so this allows us to position us as a very modern platform designed for these new modern use cases and workloads. So we feel good about our positioning. But as I said, this year I think is going to be continued experimentation and rollout of some individual applications.

我們發現的另一件事與類型的銷售不同，在典型的銷售中，有人決定建立新的工作負載或現代化工作負載，人工智慧決策更多的是中央決策——比以往任何時候都更集中的決策。因此，它使我們能夠在組織中真正走得更高。因此，我們實際上正在與更高級別的客戶進行接觸，因為顯然，這是一項自上而下的舉措。因此，這使我們能夠將自己定位為一個非常現代的平台，專為這些新的現代用例和工作負載而設計。所以我們對自己的定位感覺良好。但正如我所說，我認為今年將繼續試驗並推出一些單獨的應用程式。

And then on the consumption questions, Kash, thanks for that. Overall, if you look at the guidance and the piece parts that we've tried to share with you, when you take into account the $80 million of impact from the unused commitments and the multiyear outperformance, you'll see at the top line level around 500 basis points of a headwind. And then we also walked you through our expectations that the non-Atlas will be modestly down, given the $40 million of that part that isn't recurring. So when you kind of piece all those together, you'll wind up probably coming to a conclusion that Atlas looks consistent from a consumption growth standpoint. And that's in line with the stable trends we've seen over the course of fiscal '24, so we're using those fiscal '24 numbers. Obviously, there's some seasonal adjustments that we have factored in there, but that's really what we're seeing there.

然後關於消費問題，卡什，謝謝你。總體而言，如果您查看我們試圖與您分享的指南和各個部分，當您考慮到未使用承諾和多年表現所帶來的 8,000 萬美元的影響時，您將在頂線看到逆風約500個基點。然後我們也向您介紹了我們的預期，即考慮到非 Atlas 部分的 4000 萬美元不是經常性的，我們的預期將小幅下降。因此，當您將所有這些整合在一起時，您可能最終會得出這樣的結論：從消費成長的角度來看，Atlas 看起來是一致的。這與我們在 24 財年看到的穩定趨勢一致，因此我們使用 24 財年的數據。顯然，我們已經考慮了一些季節性調整，但這確實是我們所看到的。

And then to the last part of your question around EA. We are -- we do still sell EA. We don't tend to sell EA into new accounts, it tends to be into an existing account, expanding their MongoDB footprint. Sellers do get compensated on EA. Part of it goes back to the comment from the earlier question that our sales rep really can't dictate the IT deployment environment at a customer. And so yes, they get paid on that. And to your comment about the sort of EA results or expectations, that's really just as a result of the difficult compare in part given that multiyear dynamic.

然後是關於 EA 問題的最後一部分。我們仍然出售 EA。我們不傾向於將 EA 出售給新帳戶，而是傾向於將其出售給現有帳戶，從而擴大他們的 MongoDB 足跡。賣家確實可以透過 EA 獲得補償。部分原因可以追溯到先前問題中的評論，即我們的銷售代表確實無法決定客戶的 IT 部署環境。是的，他們因此獲得報酬。至於你對 EA 結果或預期的評論，這實際上只是由於多年動態而進行的困難比較的結果。

Our next question comes from the line of Brent Bracelin of Piper Sandler.

我們的下一個問題來自 Piper Sandler 的 Brent Bracelin。

Michael, we're going to stick with the guide seen here. If I look at last year, you guided to, I think, 16% growth. You ended up doing 31% for the full year. Even if I take out the $80 million tailwind, you talked about, that's still 25% growth. You're guiding to 14% growth this year, again 5% headwind, so closer to 19% organically. Are you more confident kind of going into this year than last year just as you think about the trends? Is the 14% comparable to the 16% initial guide last year? Is it really more like 19% adjusted basis comparing to 16%? I know it's a little confusing, but getting a lot of questions on it.

邁克爾，我們將堅持使用這裡看到的指南。如果我看看去年，我認為你們指導了 16% 的成長。您最終全年完成了 31%。即使我去掉了你所說的 8000 萬美元的順風車，這仍然是 25% 的增長。您預計今年的成長率為 14%，同樣是 5% 的逆風，因此有機成長更接近 19%。當您考慮趨勢時，您是否比去年更有信心進入今年？ 14% 與去年 16% 的初始指引值相當嗎？與 16% 相比，它真的更像是 19% 調整後的基礎嗎？我知道這有點令人困惑，但有很多問題。

Yes. No, it's fine. I go back to what I said in response, I think it was to Sanjeet's question. There's been no fundamental change or approach in terms of how we're looking and determining our guidance. I do think to the confidence point, I think that, that is correct. We do have more confidence. We have more data. We -- if you think back a year ago, as one of the questions indicated, there was much more macro uncertainty. I think over the course of fiscal '24, we saw narrower variability. We saw more consistent results that does give us increased confidence. I think we also have another year under our belt in terms of understanding the seasonality trends of Atlas.

是的。不，還好。我回到我的回答，我認為這是針對桑吉特的問題。在我們如何看待和確定我們的指導方面，沒有根本性的變化或方法。我確實認為有信心，我認為這是正確的。我們確實更有信心了。我們有更多數據。我們——如果你回想起一年前，正如其中一個問題所表明的那樣，宏觀不確定性要多得多。我認為在 24 財年期間，我們看到了較小的變異性。我們看到了更一致的結果，這確實給了我們更大的信心。我認為，在了解 Atlas 的季節性趨勢方面，我們還有新的一年。

I know Atlas is a big business, but it's still a relatively young one, especially when you think about giving quarterly data points. And so I think we have more confidence and better handle on that. And then lastly, while there is a difficult compare on EA -- I think we talked about this in the second half of last year where we were -- at some point, you could only be -- continue to be surprised by EA so much. And so as we looked at our -- I think it was in our third quarter call, we talked about how we were upping our views on what EA could do. And so all that's sort of baked into the guide.

我知道 Atlas 是一家大企業，但它仍然是一個相對年輕的企業，尤其是當你考慮提供季度數據點時。所以我認為我們對此更有信心並能更好地處理。最後，雖然對 EA 進行了一個困難的比較——我想我們在去年下半年就討論過這個問題——在某個時候，你只能——繼續對 EA 感到驚訝。因此，當我們審視我們的——我認為是在第三季的電話會議時，我們討論了我們如何提高對 EA 可以做什麼的看法。所以所有這些都被納入了指南中。

Helpful color there. And then just, Dev. As you think about the million dollar question, when do you think these AI tailwinds, the interest in vector starts to really impact your business.? It sounded like you think another -- you will see another year of more experimentation before we see big production moves. Is that the right take? Just walk us through your current thinking on when AI really starts to show up in your business.

那裡有有用的顏色。然後就是，Dev。當您思考百萬美元的問題時，您認為這些人工智慧順風車何時開始對向量的興趣開始真正影響您的業務。聽起來你好像又想到了——在我們看到大規模的生產變化之前，你會看到另一年的更多實驗。這是正確的做法嗎？請向我們介紹您目前對人工智慧何時真正開始出現在您的業務中的想法。

Yes, I think it's going to show up in a business when people are deploying AI apps at scale, right? So I think that's going to be at least another year. But that being said, we do see some really interesting start-ups who are building on top of MongoDB. So it gives us confidence about our platform fit for these sophisticated workloads. But given all the noise around AI, you have to remember, we're still in the very, very early days. The performance of some of these systems is -- I would classify as okay, not great. The cost of inference is quite expensive. So people have to be quite careful about the types of applications they deploy. There's some debate about open versus close-sourced LLMs. Do they use case-specific LLMs or more general purpose LLM? So there's a lot of learnings going on.

是的，我認為當人們大規模部署人工智慧應用程式時，它就會出現在企業中，對嗎？所以我認為這至少還需要一年。但話雖這麼說，我們確實看到一些非常有趣的新創公司正在 MongoDB 上建置。因此，它讓我們對適合這些複雜工作負載的平台充滿信心。但考慮到人工智慧周圍的所有噪音，你必須記住，我們仍處於非常非常早期的階段。其中一些系統的性能——我認為還可以，不是很好。推理的成本相當昂貴。因此，人們必須非常小心他們部署的應用程式類型。關於開放法學碩士與閉源法學碩士存在一些爭論。他們使用特定案例的法學碩士還是更通用的法學碩士？因此，有很多學習正在進行。

And obviously, there was an announcement today that yet another company had delivered better performance than GPT4. So people are -- there's a lot going on in this space. So for people to really get comfortable in picking a stack and deploying workloads en masse, it's going to take a bit of time. There are obviously some outliers who are obviously being far more aggressive. But that's essentially what we see across our customer base. But the good news is that we feel like we're well positioned. We feel that people really resonate with the unified platform, one way to handle data, metadata and vector data that we are open and composable, that we integrate to not only all the different LLMs, we integrate to different embedding models, and we also -- essentially also integrate with some of the emerging application frameworks that developers want to use. So we think we're well positioned, and you'll see us continue to expand and broaden our reach in this category, but I do think it's going to take a little bit of time.

顯然，今天有消息指出又有一家公司提供了比 GPT4 更好的性能。所以人們——這個領域發生了很多事情。因此，要讓人們真正熟悉選擇堆疊並集體部署工作負載，需要一些時間。顯然有一些異常者顯然更加激進。但這基本上就是我們在客戶群中看到的情況。但好消息是我們感覺自己處於有利位置。我們覺得人們確實對統一平台產生了共鳴，這是一種開放且可組合的處理資料、元資料和向量資料的方式，我們不僅整合到所有不同的法學碩士，還整合到不同的嵌入模型，而且我們 - - 本質上也與開發人員想要使用的一些新興應用程式框架整合。因此，我們認為我們處於有利位置，您會看到我們繼續擴大和擴大我們在這一類別中的影響力，但我確實認為這需要一些時間。

Our next question comes from the line of Karl Keirstead of UBS.

我們的下一個問題來自瑞銀集團的 Karl Keirstead。

Okay. Great. Maybe one for Dev and one for Mike. Dev, just because my first question follows on that, I'll go to you first. There are certainly some voices in the industry that would argue that even in advance of AI applications being deployed at scale, which you just said might take a year. Enterprises might look to spend more to modernize their existing data stack and on data readiness in advance of those AI apps going into production. Are you seeing any of that type of behavior that could precede the in-production deployment time frame?

好的。偉大的。也許一份給 Dev，一份給 Mike。 Dev，正因為我的第一個問題隨之而來，所以我會先問你。業內肯定有一些聲音認為，即使在人工智慧應用程式大規模部署之前，你剛才說這可能需要一年的時間。在這些人工智慧應用程式投入生產之前，企業可能會希望花費更多資金來實現現有資料堆疊的現代化和資料準備。您是否看到任何可能在生產部署時間範圍之前出現的此類行為？

Yes. We -- I touched a little bit about relational migrations. I mean that's one way where a lot of people have -- feel like they have a lot of data trapped in these legacy platforms. As we've shared, I mean we've always had customers migrate from legacy SQL apps to MongoDB, but the hardest part was basically rewriting the application. Generative AI essentially lowers the cost to do so. We are running a bunch of pilots with customers. Customers are very aligned. We have access to senior level decision-makers. And we're learning a lot. Obviously, we're learning about the effectiveness of some of these AI technologies. We're learning about how you have to handle old languages, old libraries, old packages, the different versions.

是的。我們──我接觸了一些關係遷移。我的意思是，這是很多人感覺他們有大量資料被困在這些遺留平台中的一種方式。正如我們所分享的，我的意思是我們總是讓客戶從舊版 SQL 應用程式遷移到 MongoDB，但最困難的部分基本上是重寫應用程式。生成式人工智慧本質上降低了這樣做的成本。我們正在與客戶一起進行一系列試點。客戶非常一致。我們可以接觸高層決策者。我們學到了很多。顯然，我們正在了解其中一些人工智慧技術的有效性。我們正在學習如何處理舊語言、舊程式庫、舊套件和不同版本。

And so the variability in all that makes it clear that this will require a mix of product and services. Product alone today will not solve the problem. So we do think this is a big opportunity, but we're in the early days. And as I said in the past, even -- when I actually talked to investors about this, pre-AI, it was -- there was no big red easy button to press to kind of migrate a SQL app to MongoDB. And while Gen AI makes that easier, it's still going to take a little bit of time. But it's definitely exciting and there's a lot of customers leaning in. And so we're excited about the opportunity, but there's a lot of work to do.

因此，所有這些的可變性清楚地表明，這將需要產品和服務的組合。今天僅靠產品並不能解決問題。所以我們確實認為這是一個很大的機會，但我們還處於早期階段。正如我過去所說，即使是——當我實際上與投資者談論這個問題時，在人工智慧出現之前——也沒有一個大的紅色簡單按鈕可以按下將 SQL 應用程式遷移到 MongoDB。雖然 Gen AI 讓這一切變得更容易，但仍需要一些時間。但這絕對令人興奮，並且有很多客戶願意加入。因此，我們對這個機會感到興奮，但還有很多工作要做。

Yes. Thanks, Dev. And then for Mike. Mike, could you just because we're all trying to set up our models by quarter for fiscal '25. Is there any way to be more descriptive about how that $80 million the sum of those 2 pieces tracked by quarter? And in particular, how much of the $80 million landed in the fourth quarter you just reported?

是的。謝謝，德夫。然後是麥克。麥克，你可以嗎？因為我們都在努力為 25 財年按季度建立模型。有什麼方法可以更詳細地描述這兩部分的總和 8,000 萬美元是如何按季度追蹤的？特別是，您剛剛報告的 8000 萬美元中有多少是在第四季度落地的？

Yes. So I don't have a quarterly breakdown. I guess what I would offer is throughout our life as a public company, including over the 3 prior quarters of this year, when there have been unusual trends, we've tried to call them out so that people could understand both what was driving the results and looking forward, what would impact the compares. And so I think our historic comments should sort of leave a pretty good breadcrumb trail relative to things. I think we've been very clear on the multiyear deals and the EA outperformance and when that happened. And if you needed sort of a rule of thumb, credits would typically -- unused credits or unused commitments would typically -- they map to the renewal cycle, and we've called out the various seasonality as it relates to that.

是的。所以我沒有季度細目。我想我會提供的是在我們作為一家上市公司的整個生命週期中，包括今年前三個季度，當出現不尋常的趨勢時，我們試圖將它們指出來，以便人們能夠了解推動這一趨勢的因素。結果和展望，什麼會影響比較。因此，我認為我們的歷史評論應該留下相對於事物相當好的麵包屑痕跡。我認為我們對於多年交易和 EA 的出色表現以及這種情況發生的時間都非常清楚。如果您需要某種經驗法則，信用通常會 - 未使用的信用或未使用的承諾 - 通常會映射到續訂週期，並且我們已經指出了與此相關的各種季節性。

So those would probably be the big things. On the EA and other non-Atlas, obviously, Q2 last year was a big quarter. We talked about Alibaba and other deals that hit in Q2. And so I think you can -- it's not -- I wouldn't just divide by 4. There are some differences quarter-to-quarter. And then lastly, we did call out the -- for folks who look at the business on a sequential basis, the impact of Atlas -- on the Atlas numbers for Q1, given that there'll be a much more pronounced effect given this is the first quarter where we'll see the impact of that change.

所以這些可能是大事。顯然，對於 EA 和其他非 Atlas 來說，去年第二季是一個重要的季度。我們討論了阿里巴巴和第二季發生的其他交易。所以我認為你可以——但事實並非如此——我不會只除以 4。季度與季度之間存在一些差異。最後，對於那些按順序查看業務的人來說，我們確實指出了 Atlas 對第一季度 Atlas 數據的影響，因為考慮到這一點，將會產生更明顯的影響我們將在第一季度看到這一變化的影響。

(inaudible).

（聽不清楚）。

Can you hear me because the line is cutting out s bit.

你聽得到我說話嗎，因為線路中斷了。

Yes, we can hear you. Unfortunately, we can't hear the moderator, but we can hear you.

是的，我們能聽到你的聲音。遺憾的是，我們聽不到主持人的聲音，但我們可以聽到您的聲音。

Terrific. Okay. I'd like to ask about Atlas stream processing. So that was announced in June 2023. I guess, can you just remind us of like what is Mongo's reason to win in that segment of the market? And then any idea of when that product will likely go GA?

了不起。好的。我想問一下Atlas流處理的問題。這是在 2023 年 6 月宣布的。我想，您能否提醒我們 Mongo 在該市場領域獲勝的原因是什麼？那麼您知道該產品何時會正式上市嗎？

Yes. So we announced -- as you said, we announced the private preview of stream processing and where we ended up having hundreds of development teams use the product. Now we're in a public preview. So if customers are interested, they can actually start using the product today. Why are we in a position to win? Well, for a couple of reasons. One, this is purely focused on the developer market. The data is mainly in JSON, it requires a flexible schema and is for real-time applications. Given all those things are kind of in our coordinating, we feel really well positioned because most of the alternatives have a very rigid or fixed schema.

是的。因此，我們宣布 - 正如您所說，我們宣布了流處理的私人預覽版，最終我們有數百個開發團隊使用該產品。現在我們處於公開預覽階段。因此，如果客戶有興趣，他們今天就可以開始使用該產品。為什麼我們能夠獲勝？嗯，有幾個原因。第一，這純粹是針對開發者市場。數據主要是JSON，它需要靈活的模式並且適用於即時應用程式。鑑於所有這些事情都在我們的協調中，我們感覺自己處於有利位置，因為大多數替代方案都有非常嚴格或固定的模式。

And with the variability of the data coming from these kind of events, that becomes much more problematic for customers to manage. So we feel very good about our position there. In terms of timing of when we're going to go GA, we're just candidly getting feedback and responding to feedback, and we want to be very sure that we've addressed kind of the low-hanging fruit before we go generally available, but we're really excited about the opportunity that stream processing offers us.

由於此類事件資料的可變性，客戶的管理變得更加困難。所以我們對我們在那裡的地位感覺非常好。就我們何時進行正式發布的時間而言，我們只是坦率地獲取反饋並回應反饋，並且我們希望確保在正式發布之前我們已經解決了一些容易實現的目標，但我們對流處理為我們提供的機會感到非常興奮。

Mike, just a little follow on to that and then add in my kind of proper second question. The follow-on is that -- is stream processing embedded in the guidance for fiscal '25? And then the question I had is about the bottom line. The guidance if I'm not mistaken is a 10% op margins in fiscal '25, assuming the same beat as you guys did this year. So it was 6 points of beat, would put us at about 16 points of op margin exiting fiscal '25. So kind of net-net, flat year-on-year. Is that due to this kind of putting the kind of foot on the gas in terms of hiring and really trying to be aggressive at kind of adding headcount?

麥克，稍微跟進一下，然後添加我的第二個問題。後續問題是──流處理是否嵌入到 25 財年的指南中？然後我的問題是關於底線的。如果我沒記錯的話，指導意見是 25 財年的營運利潤率為 10%，假設與你們今年的成長率相同。因此，這是 6 個百分點的領先，這將使我們在 25 財年退出時的營運利潤率約為 16 個百分點。淨值同比持平。這是因為在招募方面加強了力度，並真正嘗試積極增加員工人數嗎？

Yes. So a couple of different questions there. Let me try and get them all. So obviously, our plans related to stream processing are included in our guidance. But we don't -- most of that will show up in Atlas overall when you think about the results. And certainly, whether it's new workloads or anything else, they tend to start off small and grow quickly in those first couple of quarters. But I wouldn't think of it as a major move -- needle mover in the context of the fiscal '25 results, but we're very excited about it over the long term.

是的。這裡有幾個不同的問題。讓我嘗試把它們全部拿到。顯然，我們與流處理相關的計劃包含在我們的指南中。但我們不會——當你考慮結果時，大部分都會顯示在 Atlas 中。當然，無論是新的工作負載還是其他任何東西，它們往往從小規模開始，並在前幾個季度快速成長。但我不認為這是一個重大舉措——在 25 財年業績背景下的重大舉措，但從長遠來看，我們對此感到非常興奮。

In terms of the op margin, yes, our guidance is to go backwards on operating margin relative to fiscal '24. It will result in 500 basis points improvement over the 2-year basis. And the thinking and the rationale related to that is the fact that if you take a step back and you look at us relative to the IPO, we had mapped out needing around 55 points of margin improvement to get to our target margins.

就營業利潤率而言，是的，我們的指導是相對於 24 財年的營業利潤率有所倒退。與 2 年相比，這將帶來 500 個基點的改善。與此相關的想法和理由是，如果你退後一步，看看我們相對於 IPO 的情況，我們已經計劃需要將利潤率提高大約 55 個百分點才能達到我們的目標利潤率。

With the fiscal '24 results, we effectively delivered 50 of those 55 points and yet are still at 2% market share. And so it makes sense to continue investing in the opportunity, particularly on the sales productive capacity as we talked about, but also to execute against the product road map. And so we will continue to do that, and that will take us backwards relative to last year, but positive 500 basis points on a 2-year basis.

根據 24 財年的業績，我們有效地實現了這 55 個點中的 50 個點，但市佔率仍為 2%。因此，繼續投資機會是有意義的，特別是我們談到的銷售生產能力，但也要根據產品路線圖執行。因此，我們將繼續這樣做，這將使我們相對於去年倒退，但在兩年基礎上正增長 500 個基點。

Our next question comes from the line of Brad Sills of Bank of America.

我們的下一個問題來自美國銀行的布拉德·希爾斯。

I wanted to ask a question around the sales capacity. It sounds like at some point last year, you realized that you had underinvested, maybe pivoted too much towards margin expansion and then are now catching up. In the guidance, if you could assume you had the sales capacity that you would prefer to be at this point given the demand that you're seeing, would we be at a higher level of growth? I'm just trying to parse out how much of the guide is factoring in those constraints on sales capacity that you've talked about.

我想問一個關於銷售能力的問題。聽起來好像去年的某個時候，您意識到自己投資不足，可能過度轉向利潤擴張，然後現在正在迎頭趕上。在指南中，如果您可以假設根據您所看到的需求，您目前擁有您希望的銷售能力，那麼我們會處於更高的成長水平嗎？我只是想弄清楚指南中有多少內容考慮了您所談到的對銷售能力的限制。

Yes. So thanks for your question. Yes, given the macro uncertainty, especially coming out off Q4 of last year, we did slow down hiring quite meaningfully. And obviously, that showed up in our numbers, to the point that Michael talked about in our op margin as well. We obviously know that we have a big opportunity in front of us. So we are growing our head count between the mid- and high teens. We think that's appropriate relative to the opportunities we see. And yes, if we had more productive sales capacity, the guidance would probably be higher. There's no question about that.

是的。謝謝你的提問。是的，考慮到宏觀不確定性，特別是去年第四季的不確定性，我們確實相當有意義地放慢了招募速度。顯然，這也體現在我們的數據中，以至於麥可也在我們的營運利潤中談到了這一點。我們顯然知道我們面前有一個巨大的機會。因此，我們正在增加中十幾歲的員工人數。我們認為這相對於我們看到的機會是合適的。是的，如果我們擁有更高的生產銷售能力，指導可能會更高。毫無疑問。

Yes. I would just -- Brad, I would just make sure it's clear. The slowing down in hiring was really macro-related, and just sort of concerns about the environment. If you think back then, there were broad-scale layoffs happening across the industry and everything else. And obviously, we successfully weathered the storm. I think we talked about on the last call, how with the benefit of hindsight and the results that we put up and how quickly, at least for us things stabilized, we could have started investing sooner.

是的。我只是——布拉德，我只是確保一切都清楚。招聘放緩確實與宏觀有關，只是對環境的擔憂。如果你回想一下當時，整個產業和其他所有領域都發生了大規模裁員。顯然，我們成功地度過了這場風暴。我想我們在上次電話會議上談到瞭如何利用事後諸葛亮和我們提出的結果，以及如何快速地（至少對我們而言）情況穩定下來，我們可以更早地開始投資。

And so I think in the call -- the year ago call, we talked about adding single-digit headcount growth relative to, I think, 30% headcount growth in the prior year. We wound up adding 9%, so obviously, at the high end of what would constitute single digits, in part because of the stabilization that we did see. But to the comments that affect the op income guide and everything else that was back-end loaded, right? So those investments will much more affect the fiscal '25 P&L, and that's really what we're reflecting into.

因此，我認為在一年前的電話會議中，我們討論了相對於前一年 30% 的員工人數增長，增加個位數的員工人數增長。顯然，我們最終增加了 9%，達到了個位數的上限，部分原因是我們確實看到了穩定性。但是對於影響操作收入指南和後端加載的其他所有內容的評論，對吧？因此，這些投資將對 25 財年的損益產生更大的影響，而這正是我們所反映的。

And then one more, if I may, please. You guys have such broad exposure to different industries. With the advent of AI coming into your business and some of the early progress you're seeing, are there any verticals that you would point to where you're seeing more activity perhaps than others? Any use cases you might point to just to give us a sense for where that early adopter might come from?

如果可以的話，請再來一張。你們對不同行業的接觸如此廣泛。隨著人工智慧進入您的業務以及您所看到的一些早期進展，您是否會指出哪些垂直領域的活動可能比其他垂直領域更多？您可能會指出任何用例，只是為了讓我們了解早期採用者可能來自哪裡？

Yes. In regards to use cases, we're seeing most customers focus on driving efficiencies in their business because their existing baseline of costs are well known. So it's much easier for them to determine how much value they can derive by using some of these new AI technologies. So I see the first wave of applications being around reducing costs. You've seen some announcements by some customers that are saying, focusing on things like customer support and customer service, they really have been -- they have found ways to dramatically reduce their cost. That's not surprising to me. I think cogeneration and this increasing developer productivity is another area.

是的。在用例方面，我們看到大多數客戶都專注於提高業務效率，因為他們現有的成本基準是眾所周知的。因此，他們可以更輕鬆地確定透過使用其中一些新的人工智慧技術可以獲得多少價值。所以我認為第一波應用是圍繞著降低成本。您已經看到一些客戶發布的一些聲明，他們說，專注於客戶支援和客戶服務等事情，他們確實已經找到了大幅降低成本的方法。這對我來說並不奇怪。我認為熱電聯產和不斷提高的開發人員生產力是另一個領域。

I think those are going to be kind of 2 areas where there's low-hanging fruit. But then I think you're going to see customers focus on delivering better experiences for their customers and then find new streams of growth. And so I think it will be -- come in phases. And so in terms of across industries, I think it's -- obviously, there's some constraints on some customers based on the regulated nature of their industry. But in general, we see basically high interest across almost every industry that we operate in.

我認為這兩個領域都是容易實現的目標。但我認為你會看到客戶專注於為客戶提供更好的體驗，然後找到新的成長動力。所以我認為這將是分階段進行的。因此，就跨行業而言，我認為顯然，基於行業的監管性質，某些客戶受到一些限制。但總的來說，我們幾乎在我們經營的每個行業都看到了很高的興趣。

Our next question comes from the line of Rishi Jaluria of RBC Capital.

我們的下一個問題來自 RBC Capital 的 Rishi Jaluria。

Wonderful. I wanted to first start with Relational Migrator. Dev, can you talk a little bit about kind of what demand for that looks like? And when customers are talking to you, are they more focused around the value prop being around cost savings that they get from moving from legacy relational databases over to MongoDB? Maybe it's just more about the flexibility around the technology itself. And maybe if you could tie in how you expect now with Gen AI as an accelerator, how that can impact the time line of migrating workloads from relational over to MongoDB. Then I've got a quick follow-up for Michael.

精彩的。我想先從關係遷移器開始。 Dev，您能談談對此的需求是什麼樣的嗎？當客戶與您交談時，他們是否更專注於從傳統關係型資料庫遷移到 MongoDB 所帶來的成本節約這一價值支柱？也許更多的是關於技術本身的靈活性。也許如果您可以將 Gen AI 作為加速器與您現在的期望結合起來，這會如何影響將工作負載從關係型遷移到 MongoDB 的時間軸。然後我會快速跟進邁克爾。

Sure. When we talk to customers -- and remember, even for IPO, we had a meaningful number of customers migrating off relational to MongoDB. So the tend come in 3 categories of reasons why. First is that the data model has become so brittle with their relational architecture that it's very hard to build new features and be responsive to their customers. And so they just feel like their ability to innovate has slowed down. The second reason is that the system is just not scaling or performing, given the increased number of users or the large amount of data that they have to process, that they realize that they have to get off a legacy platform. And the third reason is just the cost of the underlying platform and relative to the ROI that application is providing.

當然。當我們與客戶交談時，請記住，即使是 IPO，我們也有大量客戶從關聯式資料庫遷移到 MongoDB。因此，原因往往分為三類。首先，資料模型因其關係架構而變得如此脆弱，以至於很難建立新功能並回應客戶。所以他們只是覺得自己的創新能力已經放緩。第二個原因是，考慮到用戶數量的增加或他們必須處理的大量數據，系統無法擴展或執行，他們意識到必須擺脫遺留平台。第三個原因是底層平台的成本以及相對於應用程式提供的投資報酬率。

So it typically falls in one of those 3 buckets. Sometimes customers may have all 3 or maybe 2 of the 3 that are driving that demand. And then there's typically some compelling event. Maybe there's some milestones they want to hit. Maybe there's a renewal coming up with the incumbent vendor that's driving them to potentially move off that vendor as quickly as possible. As I said, with Relational Migrator, there's 3 parts to it. There's mapping of the schema from a tabular, relational schema to a document-based schema in MongoDB. Then it's actually moving the data and mapping to the new schema and then there's the rewriting of the application. And so we have done lots of those already pre-Gen AI and some customers take a -- I want to rewrite everything. Some customers take a, I'll do it on a micro services basis, where I'll start peeling off functionality off the existing application and move that functionality to the new application and do that over time.

所以它通常屬於這三個類別之一。有時，客戶可能擁有全部 3 個或可能 3 個中的 2 個來驅動該需求。然後通常會發生一些引人注目的事件。也許他們想要達到一些里程碑。也許現有供應商即將進行續約，這促使他們盡快離開該供應商。正如我所說，關係遷移器由 3 個部分組成。 MongoDB 中存在從表格關係模式到基於文件的模式的模式對應。然後，它實際上將資料移動並映射到新模式，然後重寫應用程式。因此，我們已經做了很多前一代人工智慧的工作，一些客戶認為——我想重寫一切。一些客戶認為，我將在微服務的基礎上進行，我將開始從現有應用程式中剝離功能，並將該功能轉移到新應用程式中，並隨著時間的推移執行此操作。

It really depends on the customer's use case and their business needs. And yes, with Gen AI, we do expect that rewriting the application has become easier and hence, lower the cost of essentially switching, which by definition, then expands the amount of customers and workloads you can go after. The other -- I would say, on top of the 3 reasons I gave you in terms of why people move, there's now an emerging fourth reason, which is enabling their data and their applications to be more AI-enabled. And so it's not just moving to a more modern platform, but making them more AI enabled. And so that's also something that's getting customers' interest. And to your question on timing, as I said, I think this year that we're going to see a lot of pilots and people trying out these new AI capabilities. And I think as the technology improves, as we learn more, I think you're going to see that scale much more quickly after that.

這實際上取決於客戶的用例及其業務需求。是的，借助 Gen AI，我們確實希望重寫應用程式變得更加容易，從而降低本質上切換的成本，根據定義，這會擴大您可以追求的客戶數量和工作負載。另一個——我想說，除了我給大家提供的關於人們為何搬家的三個原因之外，現在出現了第四個原因，即使他們的數據和應用程式更加支援人工智慧。因此，這不僅是轉向更現代的平台，而且使它們更加支援人工智慧。這也是引起客戶興趣的原因。至於你關於時機的問題，正如我所說，我認為今年我們將看到很多飛行員和人們嘗試這些新的人工智慧功能。我認為隨著技術的進步，隨著我們了解更多，我認為在那之後你會更快看到這種規模。

Wonderful, really helpful. And then Michael, just quickly, you put up your first free cash flow positive year in public company history. Just as we think about the margin guidance for next year, how should we be thinking about cash conversion going forward?

太棒了，真的很有幫助。然後邁克爾，很快，你就實現了上市公司歷史上第一個自由現金流為正的年份。正如我們考慮明年的利潤指導一樣，我們應該如何考慮未來的現金轉換？

Yes. So I think the 2 factors to think about in terms of cash conversion are -- within Atlas, there's this dynamic where we are reducing and continuing to see less upfront Atlas. Obviously, we're hitting the anniversary of that, and that's what's creating the headwind on the revenue front and the tough compare. But that's with Atlas at 68% of revenue. And so if you assume that Atlas is going to increase as a percent of revenue, I think that will sort of further drive the divergence.

是的。因此，我認為在現金轉換方面需要考慮的兩個因素是——在 Atlas 內部，我們正在減少並繼續減少 Atlas 的預付款。顯然，我們即將迎來週年紀念日，這就是為什麼在收入方面造成阻力和進行艱難比較的原因。但這是 Atlas 佔收入的 68%。因此，如果你假設 Atlas 佔收入的百分比將會增加，我認為這將進一步加劇這種差異。

And then the only other big delta is things related to SBC and stuff like that. But I think it's the Atlas dynamic when you think about potential changes from a cash conversion standpoint, I think, is where I'd focus. And the impact, if you assume that Atlas is going to be a larger percent of the business.

然後唯一的其他大三角洲是與 SBC 相關的東西以及類似的東西。但我認為，當你從現金轉換的角度考慮潛在的變化時，我認為，阿特拉斯的動態才是我關注的焦點。如果您假設 Atlas 將在業務中佔據更大的比例，那麼也會產生影響。

Our next question comes from the line of Tyler Radke of Citi.

我們的下一個問題來自花旗銀行的泰勒拉德克 (Tyler Radke)。

Can you hear me okay?

你聽得到我說話嗎？

Yes, Tyler.

是的，泰勒。

The line was a little choppy. Dev, I wanted to ask you just a question as it relates to competition. Obviously, it's been a busy week at both Snowflake and Databricks with Frank Slootman retiring, and I hope you're not going anywhere soon. But -- and Databricks announcing pretty impressive growth. I guess how do you kind of think about your positioning relative to those 2 vendors? Especially with the new CEO, kind of more of a technical focus at Snowflake and the Unistore product coming out later this year. Do you expect it more -- just frame for us how you're thinking about it, especially as the Gen AI momentum increases over the coming years?

線路有點不穩定。 Dev，我想問你一個與競爭有關的問題。顯然，隨著 Frank Slootman 的退休，Snowflake 和 Databricks 度過了忙碌的一周，我希望你們不會很快離開。但是——Databricks 宣布了相當令人印象深刻的成長。我想您如何看待您相對於這兩家供應商的定位？尤其是新任 CEO 上任後，Snowflake 的技術重點更加突出，Unistore 產品將於今年稍後推出。您是否對此更有期待——請告訴我們您是如何看待它的，尤其是隨著未來幾年人工智慧勢頭的增強？

Yes. So first of all, I'm very committed to MongoDB. I'm very excited about the opportunity here, so I have no plans to go anywhere. Second, in regards to Snowflake and Databricks, we don't typically compete with them, right? Because they're focused on analytical workloads. We're focused on operational workloads. So those are 2 very different sets of use cases. The big difference in terms of how customers buy, typically data warehouses and data lakes tends to be a centralized decision. Organizations standardize on one platform and then basically move their existing data to those platforms. Where, I would say, operational platforms tend to be a more decentralized decision where different development teams, different lines of businesses, et cetera, based on the requirements for their application will choose -- will make their own independent decision about what they think they need to do. And we've always talked about how we start with one team and then try and expand from there, and why there's so much focus on expanding with the accounts and becoming a standard with an account because then that accelerates the amount of workloads we capture.

是的。首先，我非常致力於 MongoDB。我對這裡的機會感到非常興奮，所以我沒有去任何地方的計劃。其次，對於 Snowflake 和 Databricks，我們通常不會與他們競爭，對吧？因為他們專注於分析工作負載。我們專注於營運工作負載。所以這是兩組非常不同的用例。客戶購買方式（通常是資料倉儲和資料湖）的巨大差異往往是集中決策。組織在一個平台上進行標準化，然後基本上將其現有資料轉移到這些平台。我想說的是，營運平台往往是一個更加去中心化的決策，不同的開發團隊、不同的業務線等等，根據他們的應用程式的要求進行選擇——將做出他們自己的獨立決定。需要做。我們總是談論我們如何從一個團隊開始，然後嘗試從那裡開始擴展，以及為什麼如此多地關注帳戶擴展並成為帳戶標準，因為這會加速我們捕獲的工作負載量。

But those are two very different kind of customer buying behaviors in terms of analytical versus operational. With regards to the potential overlap, we are embedding more analytics capabilities. We have a very sophisticated aggregation framework, so people can do real-time processing of analytics on our platform with real-time data. Remember, data lakes and data warehouses have some batch process to get that data into their platforms. So they're not dealing with the real-time data.

但就分析與營運而言，這是兩種截然不同的客戶購買行為。關於潛在的重疊，我們正在嵌入更多的分析功能。我們有一個非常複雜的聚合框架，因此人們可以在我們的平台上使用即時數據進行即時分析處理。請記住，資料湖和資料倉儲有一些批次過程來將資料輸入到其平台中。所以他們不處理即時數據。

And then with regards to Unistore, listen, there's like over 300 databases in the marketplace. So not sure -- I have a lot of respect for the Snowflake people. I'm not sure. We've heard noises about Unistore for a long time, but we feel very comfortable and confident of our position just given the investments we've made in our platform and the large customers we have and frankly, the popularity of our platform with developers. And remember, developers are not a persona that these other players typically go after, they for more than analysts and the data scientist community. We're very, very focused on developers.

然後是 Unistore，聽著，市場上有 300 多個資料庫。所以不確定——我非常尊敬雪花人。我不知道。我們長期以來一直聽到有關Unistore 的聲音，但考慮到我們在平台上所做的投資和我們擁有的大客戶，以及坦率地說，我們平台在開發人員中的受歡迎程度，我們對我們的地位感到非常放心和自信。請記住，開發人員並不是這些其他參與者通常追求的角色，他們不僅僅是分析師和資料科學家社群。我們非常非常關注開發人員。

That's helpful. Michael, just a quick follow-up for you on the overage comments you made. I guess a couple of questions. I mean, first of all, the $40 million is what I think you called out. That seems pretty high for last year, just considering we haven't really heard about it. Since Q4 of last year where you called out only several million of overage credit, I guess. Can you just frame for us, was that consistent with what you've seen in prior years? And I guess, you're obviously embedding that, that doesn't continue next year. Is that a change in the way that you're recognizing overage revenue? Or is that just -- you don't expect that to happen because all your contracts have been reset.

這很有幫助。邁克爾，我只是對您發表的過多評論進行快速跟進。我想有幾個問題。我的意思是，首先，我認為您所說的就是 4000 萬美元。考慮到我們還沒有真正聽說過這個數字，這對去年來說似乎相當高。我猜，自從去年第四季以來，你們只撥出了幾百萬的超額信貸。您能否為我們介紹一下，這與您前幾年所看到的一致嗎？我想，你顯然是在嵌入這一點，這種情況明年不會繼續下去。您確認超額收入的方式是否改變了？或者這只是——你不希望發生這種情況，因為你的所有合約都已重置。

Yes. So just 2 quick things in the interest of time. So a reminder, the several was the incremental amount over and above the normal amount that we experienced. So that's the sort of to the principle that we take where we try and call out differences or variations from sort of the normal behavior. And so it was several million more than what we would normally see. The $40 million is the amount that was recognized in fiscal '24. We do see that going to 0 effectively. And you're right, that's directly as a result of the changes that we've made in the go-to-market and the fact that we are not prioritizing commitments and haven't since the start of last fiscal year. And so the result of that is that you have many fewer commitments and unused -- the revenue from unused credits simply just reflects the revenue at the end of that contract period that you haven't realized or recognized through consumption. And so we expect that to go away because we've taken a different approach to the market to drive greater adoption of workloads and all the other things that we've talked about, which is the rationale for sort of doing that in the first place. So hopefully that helps put all that in context.

是的。所以為了節省時間，只做兩件事。所以提醒一下，這幾個是超出我們經歷的正常數量的增量。這就是我們嘗試指出與正常行為的差異或變化時所採取的原則。所以它比我們通常看到的多了幾百萬。 4000 萬美元是 24 財年確認的金額。我們確實看到，這一數字實際上已變為 0。你是對的，這直接是我們在進入市場方面所做的改變的結果，而且我們沒有優先考慮承諾，自上一財年開始以來就沒有這樣做。因此，這樣做的結果是，您的承諾和未使用的資金要少得多——來自未使用積分的收入僅僅反映了合約期結束時您尚未透過消費實現或確認的收入。因此，我們預計這種情況會消失，因為我們對市場採取了不同的方法來推動工作負載和我們討論過的所有其他事情的更多採用，這就是首先這樣做的理由。希望這有助於將所有這些放在上下文中。

Thank you That does conclude our conference for today. I'd like to turn the call back over to Dev, CEO, for any closing remarks.

謝謝大家 今天的會議到此結束。我想將電話轉回給執行長 Dev，讓其發表結束語。

Thank you. Again, I thank everyone for joining us today. I just want to reiterate that we had a strong quarter and year, as we execute on our opportunity. We do expect fiscal '25 to play out similarly to fiscal '24 with a healthy new business and a stable consumption -- and stable consumption trends. We are very excited about the long-term AI opportunity, but still believe it's early days as customers are mainly in the experimentation and prototyping stages of building AI applications. And our priorities for fiscal '25 are to invest in deepening our product advantage while remaining focused on acquiring new workloads and establishing ourselves as the standard for building modern applications.

謝謝。我再次感謝大家今天加入我們。我只想重申，我們在抓住機會的過程中取得了強勁的季度和年度表現。我們確實預期 25 財年的業績將與 24 財年類似，新業務健康發展，消費穩定，消費趨勢穩定。我們對人工智慧的長期機會感到非常興奮，但仍然認為現在還處於早期階段，因為客戶主要處於建立人工智慧應用程式的實驗和原型設計階段。我們 25 財年的首要任務是投資深化我們的產品優勢，同時繼續專注於獲取新的工作負載並將我們自己打造為建立現代應用程式的標準。

So thank you again for joining us, and we'll talk to you soon. Take care. Bye-bye.

再次感謝您加入我們，我們很快就會與您聯繫。小心。再見。

Thank you. Ladies and gentlemen, this does conclude today's conference. Thank you all for participating. You may now disconnect. Have a great day.

謝謝。女士們、先生們，今天的會議到此結束。感謝大家的參與。您現在可以斷開連線。祝你有美好的一天。