MongoDB Inc (MDB) 2024 Q3 法說會逐字稿

Thank you for standing by, and welcome to MongoDB's Q3 Fiscal Year '24 Conference Call. (Operator Instructions). As a reminder, today's call is being recorded. I would now like to turn the call to your host, Mr. Brian Denyeau from ICR. Please go ahead.

感謝您的耐心等待，歡迎參加 MongoDB '24 財年第三季電話會議。 （操作員說明）。提醒一下，今天的通話正在錄音。現在我想將電話轉給主持人、來自 ICR 的 Brian Denyeau 先生。請繼續。

Great. Thank you, Valerie. Good afternoon, and thank you for joining us today to review MongoDB's Third Quarter Fiscal 2024 Financial Results, which we announced in our press release issued at the close of the market today. Joining me on the call today are Dev Ittycheria, President and CEO of MongoDB; and Michael Gordon, MongoDB's COO and CFO.

偉大的。謝謝你，瓦萊麗。下午好，感謝您今天與我們一起回顧 MongoDB 2024 年第三季財務業績，我們在今天收盤時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。

During this call, we will make forward-looking statements, including statements related to our market and future growth opportunities, 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 could cause our future 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, 2023 that was filed with the SEC on September 1, 2023. Any forward-looking statements made on this call reflect our views only as of today and we undertake no obligation to update them, except as required by law.

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、我們產品平台的優勢、我們的競爭格局、客戶行為、我們的財務指導和我們計劃的投資相關的陳述。這些陳述受到各種風險和不確定性的影響，包括可能導致我們未來業績與我們的預期有重大差異的經營業績和財務狀況。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 9 月 1 日向 SEC 提交的截至 2023 年 7 月 31 日的季度 10-Q 表格季度報告中描述的風險. 本次電話會議中所做的任何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。

Additionally, we will 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 their most directly comparable GAAP financial measure.

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的收益發布中的表格，以了解這些指標與其最直接可比較的公認會計準則財務指標的對帳情況。

With that, I'd like to turn the call over to Dev.

有了這個，我想把電話轉給 Dev。

Thank you, Brian, and thank you to everyone for joining us today. I'm pleased to report that we had another strong as we continue to execute well despite challenging market conditions. I will start by reviewing our third quarter results before giving you a broader company update.

謝謝你，布萊恩，也謝謝大家今天加入我們。我很高興地向大家報告，儘管市場條件充滿挑戰，但我們仍然表現出色，因此我們擁有了另一個強勁的表現。在向您提供更廣泛的公司最新情況之前，我將首先回顧我們第三季的業績。

We generated revenue of $433 million, a 30% year-over-year increase and above the high end of our guidance. Atlas revenue grew 36% year-over-year, representing 66% of total revenue. We generated non-GAAP operating income of $79 million for an 18% non-GAAP operating margin, and we had another solid quarter of customer growth, ending the quarter with over 46,400 customers. Overall, we delivered a strong Q3.

我們的收入達到 4.33 億美元，年增 30%，高於我們指導的上限。 Atlas營收年增36%，佔總營收的66%。我們的非 GAAP 營業收入為 7,900 萬美元，非 GAAP 營業利潤率為 18%，並且我們又一個季度實現了穩定的客戶成長，本季末客戶數量超過 46,400 名。整體而言，我們第三季表現強勁。

We had a healthy quarter of new business acquisition led by continued strength in new workload acquisition within our existing 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.

由於現有客戶新工作負載獲取的持續強勁，我們在新業務獲取方面取得了健康的季度表現。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。

Moving on to Atlas consumption trends. The quarter played out in line with our expectations. Michael will discuss consumption trends in more detail later. Finally, retention rates remained strong in Q3, reinforcing the mission criticality of our platform even in a difficult spending environment. This quarter, we held our most recent global Customer Advisory Board meeting, where customers across various geographies and industries came together to share feedback and insight about the experience using MongoDB. From these discussions as well as our ongoing C-suite dialogue with our customers, a few themes emerge.

接下來是 Atlas 消費趨勢。該季度的表現符合我們的預期。邁克爾稍後將更詳細地討論消費趨勢。最後，第三季的留任率仍然很高，即使在困難的支出環境下，也增強了我們平台的使命關鍵性。本季度，我們舉行了最近一次的全球客戶諮詢委員會會議，來自不同地區和行業的客戶齊聚一堂，分享有關使用 MongoDB 體驗的回饋和見解。從這些討論以及我們與客戶持續進行的高階主管對話中，我們得到了一些主題。

First, AI is in nearly every conversation with customers of all sizes. We're seeing great early feedback from our partnership with AWS' CodeWhisperer, the AI-powered coding companion that is now trained on MongoDB data to generate code suggestions based on MongoDB's best practices from over 15 years of history. Microsoft GitHub Copilot is also proficient at generating code suggestions that reflect best practices in aiding developers to build highly performed applications even faster on MongoDB.

首先，人工智慧幾乎存在於與各種規模的客戶的每一次對話中。我們從與 AWS 的 CodeWhisperer 的合作中看到了很好的早期反饋，CodeWhisperer 是一個人工智慧驅動的編碼伴侶，現在接受了 MongoDB 數據的培訓，可以根據 MongoDB 超過 15 年曆史的最佳實踐生成代碼建議。 Microsoft GitHub Copilot 也擅長產生程式碼建議，這些建議反映了幫助開發人員在 MongoDB 上更快建立高效能應用程式的最佳實踐。

And with the recent advances in Gen AI, building AI applications is no longer the sole domain of AI/ML experts. Increasingly, it's software developers who are being asked to build powerful AI functionality directly into their applications. We are well-positioned to help them do just that.

隨著新一代人工智慧的最新進展，建立人工智慧應用程式不再是人工智慧/機器學習專家的唯一領域。越來越多的軟體開發人員被要求將強大的人工智慧功能直接建置到他們的應用程式中。我們有能力幫助他們做到這一點。

We saw exceptional interest in our vector search public preview, and we announced general availability yesterday. Customers are building a range of AI use cases from semantic search to retrieval augmented generation or RAG, where organizations can leverage the use of their private data to increase the accuracy of LLMs. For example, UKG, a human capital and workflow management technology serves over 80,000 plus customers around the globe chose to use MongoDB Atlas Vector Search for an AI-powered assistant that helps guide their customers' employees, people managers and HR leaders.

我們看到人們對向量搜尋公共預覽版非常感興趣，並在昨天宣布全面上市。客戶正在建立一系列人工智慧用例，從語義搜尋到檢索增強生成或 RAG，組織可以利用其私有資料來提高法學碩士的準確性。例如，UKG 是一種人力資本和工作流程管理技術，為全球超過 80,000 多家客戶提供服務，選擇使用 MongoDB Atlas Vector Search 作為人工智慧助手，幫助指導客戶的員工、職能經理和人力資源主管。

They chose Atlas Vector search because of its minimal added architectural complexity, flexibility to handle rapidly changing data as applications evolve and the scale to handle large workloads. UKG is not alone. In a recent state of AI survey reported by retool, Atlas Vector Search received by far the highest Net Promoter Score from developers compared to all other vector databases available in the market.

他們選擇 Atlas Vector 搜尋是因為其增加的架構複雜性最小、能夠隨著應用程式的發展靈活地處理快速變化的資料以及能夠處理大量工作負載的規模。 UKG並不孤單。在 retool 最近報告的一項人工智慧調查中，與市場上所有其他向量資料庫相比，Atlas Vector Search 獲得了開發人員迄今為止最高的淨推薦值。

Moreover, developers can combine Vector Search with any other query capabilities available in MongoDB namely analytics, tech search, geospatial and time series. This provides powerful ways of defining additional filters on Vector-based queries that other solutions just cannot provide. For example, you can run complex AI and rich queries such as find pants, a shirt, shoes in my size that look like the outfit in this image within a particular price range and have free shipping. Or find real estate listings with houses that look like this image that were built in the last 5 years and are in an area within 7 miles west of downtown Chicago with top-rated schools.

此外，開發人員可以將向量搜尋與 MongoDB 中提供的任何其他查詢功能（即分析、技術搜尋、地理空間和時間序列）結合。這提供了在基於向量的查詢上定義其他過濾器的強大方法，這是其他解決方案無法提供的。例如，您可以執行複雜的 AI 和豐富的查詢，例如查找我尺寸的褲子、襯衫、鞋子，它們看起來像此圖片中的服裝，在特定的價格範圍內並且免運費。或查找房地產列表，其中包含與此圖片類似的房屋，這些房屋建於過去 5 年，位於芝加哥市中心以西 7 英里範圍內，擁有一流的學校。

Second, customers feel more pressured than ever to modernize their data infrastructure. They are aware that their legacy platforms are holding them back from building modern applications designed for an AI future. However, customers also tell us that they lack the skills and the capacity to modernize. They all want to become modern, but are daunted by the challenges as they are aware it's a complex endeavor that involves technology, process and people. Consequently, customers are increasingly looking to MongoDB to help them modernize successfully.

其次，客戶感受到比以往任何時候都更大的壓力來實現數據基礎設施的現代化。他們意識到，他們的遺留平台阻礙了他們建立專為人工智慧未來設計的現代應用程式。然而，客戶也告訴我們，他們缺乏現代化的技能和能力。他們都想變得現代化，但又被挑戰嚇倒了，因為他們意識到這是一項涉及技術、流程和人員的複雜努力。因此，客戶越來越希望 MongoDB 能夠幫助他們成功現代化。

We launched Relational Migrator earlier this year to help customers successfully migrate data from their legacy Relational databases to MongoDB. Now we're looking beyond data migration to the full life cycle of application modernization. At our local London event, we unveiled the Query Converter, which uses Generative AI to analyze existing SQL queries and store procedures and convert them to work with MongoDB's Query API.

我們在今年稍早推出了 Relational Migrator，幫助客戶成功地將資料從舊的關聯式資料庫遷移到 MongoDB。現在，我們的目光不再局限於資料遷移，而是應用程式現代化的整個生命週期。在我們當地的倫敦活動中，我們推出了查詢轉換器，它使用生成式 AI 來分析現有的 SQL 查詢和預存程序，並將它們轉換為與 MongoDB 的查詢 API 配合使用。

Customers already tooled successfully to convert decades-old procedures to modernize their back-end with minimal need for manual changes. While it's still early days, we're continuing to invest in the Query Converter and other AI features with the goal of significantly reducing the effort involved in monetizing legacy applications to run on MongoDB.

客戶已經成功地使用了工具來轉換幾十年前的程序，以實現後端現代化，幾乎不需要手動更改。雖然現在還處於早期階段，但我們將繼續投資查詢轉換器和其他 AI 功能，目標是大幅減少在 MongoDB 上運行的舊應用程式貨幣化所需的工作量。

To be clear, application modernization will take time to ramp, but is one of the largest long-term growth opportunities for our business.

需要明確的是，應用程式現代化需要一段時間才能實現，但這是我們業務最大的長期成長機會之一。

Third, our run anywhere strategy continues to be a real differentiator as customers greatly appreciate the optionality that our platform provides as they manage often conflicting priorities on the way to the cloud. On one hand, the movement to the cloud continues unabated. Customers in the industries and geographies were first hesitant to move to cloud, such as financial services in Southern Europe are now moving to the cloud with urgency to become more nimble and to reduce costs. Many of our customers find that the all-in cost of maintaining legacy workloads on-prem is higher than the cost of migrating them to the cloud.

第三，我們的隨處運作策略仍然是一個真正的差異化因素，因為客戶非常欣賞我們平台提供的可選性，因為他們在通往雲端的過程中管理經常相互衝突的優先順序。一方面，向雲端運算的發展有增無減。產業和地區的客戶最初對遷移到雲端猶豫不決，例如南歐的金融服務現在正在遷移到雲端，迫切需要變得更加靈活並降低成本。我們的許多客戶發現，在本地維護遺留工作負載的總成本高於將其遷移到雲端的成本。

On the other hand, our largest enterprise customers tell us they are planning to maintain a meaningful on-prem footprint for the foreseeable future. The reasons for keeping workloads on-prem include regulatory requirements, the desire to keep using their existing on-prem infrastructure or the enormity of the task of migrating all their apps to cloud. In the meantime, they still want a modern data platform to deploy new and existing applications. The continued outperformance of our EA business demonstrates that our customers value our ability to run anywhere and to future-proof their eventual move to the cloud by building on EA.

另一方面，我們最大的企業客戶告訴我們，他們計劃在可預見的未來保持有意義的在地足跡。將工作負載保留在本地的原因包括監管要求、繼續使用現有本地基礎設施的願望或將所有應用程式遷移到雲端的任務的艱鉅性。同時，他們仍然需要一個現代數據平台來部署新的和現有的應用程式。我們 EA 業務的持續出色表現表明，我們的客戶重視我們在任何地方運作的能力，以及透過建立 EA 來確保他們最終遷移到雲端的能力。

Finally, our customers remain focused on cost management. They are looking to do more with less by consolidating vendors and reducing the complexity of the data architecture. MongoDB dramatically increases developer productivity and supports a wide variety of use cases, eliminating the need for many point solutions. This combination resonates with customers in this macro environment.

最後，我們的客戶仍然專注於成本管理。他們希望透過整合供應商和降低資料架構的複雜性來事半功倍。 MongoDB 大大提高了開發人員的工作效率並支援各種用例，從而消除了對許多單點解決方案的需求。這種組合在這個宏觀環境下引起了客戶的共鳴。

For example, Atlas Search now powers the homepage of one of the most recognizable sports media brands in the world. The customer replaced an incumbent search technology with Atlas Search because they were drawn to the operational ease of running search queries alongside other queries on Atlas as well as the overall cost savings from consolidating functionality onto a single platform. In short, customers view MongoDB as a true partner, a partner that not only accelerates the pace of innovation, but also drives them to become more efficient. We are deepening investments in our products, partnerships and customer-facing teams to continue to enable customers to do both.

例如，Atlas Search 現在為世界上最知名的體育媒體品牌之一的主頁提供支援。該客戶用 Atlas Search 取代了現有的搜尋技術，因為他們被 Atlas 上運行搜尋查詢和其他查詢的操作簡便性以及將功能整合到單一平台所節省的總體成本所吸引。簡而言之，客戶將 MongoDB 視為真正的合作夥伴，一個不僅能加快創新步伐，還能推動他們變得更有效率的合作夥伴。我們正在深化對產品、合作夥伴關係和麵向客戶的團隊的投資，以繼續幫助客戶實現這兩點。

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 applications on Atlas, leveraging the full power of our developer data platform. These customers include AT&T, Fishbowl by Glassdoor and Trend Micro. AT&T selected Atlas as a key element of their modernization journey. The location management application validates 380 million unique customer addresses and handles about 40 million transactions per day, but the various disparate data management solutions led to technical depth and there were duplicative sources of information. The company turned to Atlas as a developer data platform to simplify their data infrastructure, merge their data into a single view and free their teams from managing database operations.

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 Atlas 上運行關鍵任務應用程序，充分利用我們開發者資料平台的全部功能。這些客戶包括 AT&T、Fishbowl by Glassdoor 和 Trend Micro。 AT&T 選擇 Atlas 作為其現代化之旅的關鍵要素。位置管理應用程式驗證 3.8 億個唯一的客戶地址，每天處理約 4000 萬筆交易，但各種不同的資料管理解決方案導致了技術深度，並且存在重複的資訊來源。該公司選擇 Atlas 作為開發人員資料平台，以簡化其資料基礎架構，將資料合併到單一視圖中，並使團隊從管理資料庫操作中解放出來。

Now they rely on Atlas chain streams to easily track changes with data as well as Atlas' native search capabilities and built-in geospatial functions to quickly identify location information and accelerate time to market for mission-critical products and services.

現在，他們依靠 Atlas 鏈流輕鬆追蹤資料變化，以及 Atlas 的本機搜尋功能和內建地理空間功能，以快速識別位置資訊並加快關鍵任務產品和服務的上市時間。

EY, Delivery Hero and ASAP log are examples of customers turning to MongoDB to free up the developers' time for innovation while achieving significant cost savings.

EY、Delivery Hero 和 ASAP log 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。

One of the 2023 MongoDB innovation award winners is EY. Ernst & Young LLP manages high volumes of transactional data and its clients and internal teams work under strict time lines to file taxes and meet regulatory deadlines. The cloud-based global bat reporting tool, or GVRT, automates and digitizes the preparation of 242 different types of returns across 79 countries. EY migrated from their previous nonrelational database solution to Atlas and experienced a significant performance boost, reduced cost by as much as 50%, and are able to scale without limitations to handle increased data volumes, transaction loads and concurrent user requests during peak periods.

安永是 2023 年 MongoDB 創新獎得主之一。安永會計師事務所管理大量交易數據，其客戶和內部團隊在嚴格的時間範圍內工作，以報稅並滿足監管期限。基於雲端的全球蝙蝠報告工具 (GVRT) 可自動化和數位化 79 個國家/地區 242 種不同類型申報表的準備工作。 EY 從先前的非關聯式資料庫解決方案遷移到 Atlas，效能顯著提升，成本降低了 50%，並且能夠無限制地擴展，以處理高峰期間增加的資料量、交易負載和並髮用戶請求。

Evernorth Health Services, a division of the Cigna Group, Manulife and Playwalks are turning to MongoDB to modernize applications. Manulife, one of the largest life insurance companies in the world migrates to Atlas when it became clear that their relational database caused a drag on innovation and increased the time to bring new digital products to market. Manulife selected Atlas because the flexible document model speeds up development, scales easily supports asset transactions and offer seamless data migration.

Cigna Group 旗下子公司 Evernorth Health Services、Manulife 和 Playwalks 正在轉向 MongoDB 來實現應用程式現代化。世界上最大的人壽保險公司之一宏利 (Manulife) 很明顯地發現他們的關係資料庫拖累了創新並增加了將新數位產品推向市場的時間，因此遷移到了 Atlas。宏利選擇 Atlas 是因為靈活的文件模型可加快開發速度、輕鬆擴展支援資產交易並提供無縫資料遷移。

Using Atlas Device Sync, they successfully launched one critical apps offline load to ensure uninterrupted app usage when off-line or in low connectivity areas to improve mobile data synchronization. Using Atlas allows Manulife to broaden its digital capabilities and enhance the personalization of customers' interactions cost effectively.

使用 Atlas Device Sync，他們成功啟動了一項關鍵應用程式的離線加載，以確保在離線或處於低連接區域時應用程式的使用不間斷，從而改善行動數據同步。使用 Atlas 可以讓宏利擴大其數位化能力，並以經濟高效的方式增強客戶互動的個人化。

In summary, I'm pleased with our third quarter results, our run anywhere strategy allows customers flexibility over where they deploy. And MongoDB is emerging as a platform of choice for their AI-powered applications. And customers are using MongoDB to modernize and become more efficient.

總而言之，我對我們第三季的業績感到滿意，我們的隨處運行策略使客戶能夠靈活地部署地點。 MongoDB 正在成為其人工智慧應用程式的首選平台。客戶正在使用 MongoDB 來實現現代化並提高效率。

Before I turn it over to Michael, I'm excited to share that Ann Lewnes, the former Chief Marketing Officer and Executive Vice President of Corporate Strategy and Development at Adobe just joined MongoDB's Board of Directors. Ann held leadership roles at Adobe from 2006 to 2023. She was instrumental in driving Adobe's transition from a perpetual to a subscription-based business model and has experienced marketing to creative professionals, whether they're in a small agency, a medium-sized business or a very large enterprise.

在將其交給 Michael 之前，我很高興地告訴大家，Adobe 前首席行銷長兼企業策略與發展執行副總裁 Ann Lewnes 剛加入 MongoDB 董事會。 Ann 於2006 年至2023 年期間在AdAdobe 擔任領導職務。她在推動AdAdobe 從永久業務模式向基於訂閱的業務模式的轉變中發揮了重要作用，並且在創意專業人士的營銷方面擁有豐富的經驗，無論他們是在小型機構還是中型企業或是一個非常大的企業。

If you replace creative professionals with developers, this strategy is very similar to what MongoDB is doing and Ann did it at the next level of scale. Prior to Adobe, Ann and held a variety of leadership positions at Intel during her 20-year tenure at the company, including Vice President of Sales and Marketing. We are thrilled for the exceptional perspective Ann will bring to the Board.

如果用開發人員取代創意專業人士，這種策略與 MongoDB 正在做的事情非常相似，而 Ann 在下一個規模層級上做到了這一點。在加入 Adob​​e 之前，Ann 在英特爾工作的 20 年期間擔任多個領導職位，包括銷售和行銷副總裁。我們對 Ann 將為董事會帶來的非凡視角感到興奮。

With that, here's Michael.

麥可就是這樣。

Thanks, Dev. As mentioned, we delivered a strong performance in the third quarter, both financially and operationally. I'll begin with a detailed view of our third quarter results and then finish with our outlook for the fourth quarter and full fiscal year 2024.

謝謝，德夫。如前所述，我們在第三季在財務和營運方面均取得了強勁的業績。我將首先詳細介紹我們第三季的業績，然後介紹我們對第四季和 2024 年整個財年的展望。

First, I'll start with our third quarter results. Total revenue in the quarter was $433 million, up 30% year-over-year and above the high end of our guidance. As Dev mentioned, we continue to see a healthy new business environment demonstrating our product market fit and the mission criticality of our platform.

首先，我將從我們的第三季業績開始。本季總營收為 4.33 億美元，年增 30%，高於我們指引的上限。正如 Dev 所提到的，我們繼續看到一個健康的新業務環境，展示了我們的產品市場契合度和我們平台的任務關鍵性。

Shifting to our product mix. Let's start with Atlas. Atlas grew 36% in the quarter compared to the previous year and represents 66% of total revenue compared to 63% in the third fiscal 2023 and 63% last quarter. As a reminder, 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, which can be impacted by macroeconomic factors.

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 36%，佔總營收的 66%，而 2023 年第三財季為 63%，上季為 63%。提醒一下，我們確認 Atlas 收入主要基於我們平台的客戶消費，而消費與應用程式的最終用戶活動密切相關，而最終用戶活動可能受到宏觀經濟因素的影響。

Let me provide some context on Atlas consumption in the quarter. Week-over-week consumption growth in Q3 was in line with our expectations and stronger than Q2. As a reminder, we were expecting an uptick in consumption in Q3 compared to Q2 based on what we've experienced and shared with you last year. We had forecast that seasonal improvement to be less pronounced this year compared to last year given that, overall, we've seen less consumption variability this year and that is exactly how the quarter played out.

讓我提供一些有關本季度 Atlas 消費的背景資訊。第三季消費季增符合我們的預期，並且強於第二季。提醒一下，根據我們去年的經驗並與您分享，我們預計第三季的消費量將比第二季有所上升。我們曾預測，與去年相比，今年的季節性改善不會那麼明顯，因為總體而言，我們今年的消費波動較小，而本季的情況正是如此。

Turning to non-Atlas revenues. EA exceeded our expectations in the quarter as we continue to have success selling incremental workloads into our existing EA customer base. Ongoing EA strength speaks to the appeal and the success of our run anywhere strategy. The EA revenue up 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 revenues from future years.

轉向非 Atlas 收入。 EA 在本季度超出了我們的預期，因為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 收入成長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，因此包括未來幾年的定期許可收入。

Turning to customer growth. During the third quarter, we grew our customer base by approximately 1,400 customers sequentially, bringing our total customer count to over 46,400, which is up from over 39,100 in the year ago period. Of our total customer count, over 6,900 are direct sales customers, which compares to over 5,900 in the year ago period. The growth in our total customer count is being driven primarily by Atlas, which had over 44,900 customers at the end of the quarter compared to over 37,600 customers in the year ago period. It is important to keep in mind that the growth in our Atlas customer count reflects new customers to MongoDB in addition to existing EA customers adding incremental Atlas workloads.

轉向客戶成長。第三季度，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 46,400 名，高於去年同期的 39,100 名。在我們的客戶總數中，超過 6,900 名是直銷客戶，而去年同期為 5,900 多名。我們客戶總數的成長主要是由 Atlas 推動的，該公司截至本季末擁有超過 44,900 名客戶，而去年同期擁有超過 37,600 名客戶。重要的是要記住，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。

During the quarter, we moved approximately 350 accounts, representing negligible ARR, out of our self-serve customer count because they're better classified as subsidiaries of other customers or they are now users of our free tier. Taking that into account, our self-serve net additions and overall net additions remain consistent with our historic healthy trends.

在本季度，我們從自助服務客戶數量中刪除了大約 350 個帳戶（ARR 可以忽略不計），因為他們更適合歸類為其他客戶的子公司，或者他們現在是我們免費套餐的用戶。考慮到這一點，我們的自助服務淨增量和整體淨增量仍然符合我們歷史上的健康趨勢。

In terms of our direct sales net additions, new sales activity remains healthy. Our reported direct sales net adds continue to reflect the dynamics we discussed last quarter related to leveraging cloud provider marketplaces to fulfill new direct sales customer additions, and the movement of some small mid-market direct sales accounts to self-serve.

就我們的直接銷售淨增量而言，新銷售活動保持健康。我們報告的直銷淨增加繼續反映了我們上季度討論的與利用雲端供應商市場來滿足新的直銷客戶增加以及一些小型中型市場直銷帳戶轉向自助服務相關的動態。

Moving on to ARR. We had another quarter with our net AR expansion rate above 120%. We ended the quarter with 1,972 customers with at least $100,000 in ARR and annualized MRR, which is up from 1,545 in the year ago period.

繼續討論 ARR。我們又一個季度的淨 AR 擴張率超過 120%。本季結束時，我們有 1,972 名客戶的 ARR 和年化 MRR 至少為 100,000 美元，高於去年同期的 1,545 名。

Moving down the income statement. I'll be discussing our results on a non-GAAP basis, unless wise noted. Gross profit in the third quarter was $335.3 million, representing a gross margin of 77% which is up from 74% in the year ago period. Our year-over-year margin improvement is primarily driven by improved efficiencies that we are realizing in Atlas. Our income from operations was $78.5 million or an 18% operating margin for the third quarter compared to a 6% margin in the year ago period.

將損益表向下移動。除非特別指出，我將在非公認會計原則的基礎上討論我們的結果。第三季毛利為3.353億美元，毛利率為77%，高於去年同期的74%。我們的利潤率年增主要是由於我們在 Atlas 中實現的效率提高。第三季我們的營運收入為 7,850 萬美元，營運利潤率為 18%，而去年同期的利潤率為 6%。

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 our operating income results versus guidance is our revenue outperformance. In addition, our operating income benefited from the timing of new hires.

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。我們的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。此外，我們的營業收入也受惠於新員工的時機。

Finally, Q3 benefited from the timing of marketing programs, internal events and other expenses, which we now expect to occur -- incur in Q4.

最後，第三季受益於行銷計劃、內部活動和其他費用的時機，我們現在預計這些費用將在第四季度發生。

Net income in the third quarter was $79.1 million or $0.96 per share based on 82.7 million diluted weighted average shares outstanding. This compares to a net income of $18.7 million or $0.23 per share on 80.4 million diluted weighted average shares outstanding in the year ago period.

第三季淨利為 7,910 萬美元，即每股 0.96 美元，基於 8,270 萬股稀釋加權平均流通股計算。相較之下，去年同期8,040萬股稀釋加權平均流通股的淨利為1,870萬美元，即每股0.23美元。

Turning to the balance sheet and cash flow. We ended the third quarter with $1.9 billion in cash, cash equivalents, short-term investments and restricted cash. Operating cash flow in the third quarter was $38.4 million. After taking into consideration approximately $3.5 million in capital expenditures and principal repayments of finance lease liabilities, free cash flow was $35 million in the quarter.

轉向資產負債表和現金流量。截至第三季末，我們擁有 19 億美元的現金、現金等價物、短期投資和限制性現金。第三季營運現金流為 3,840 萬美元。考慮到約 350 萬美元的資本支出和融資租賃負債的本金償還，本季自由現金流為 3,500 萬美元。

This compares to negative free cash flow of $8.4 million in the third quarter of fiscal 2023.

相較之下，2023 財年第三季自由現金流為負 840 萬美元。

I'd now like to turn to our outlook for the fourth quarter and full year fiscal year 2024. For the fourth quarter, we expect revenue to be in the range of $429 million to $433 million. We expect non-GAAP income from operations to be in the range of $35 million to $38 million and non-GAAP net income per share to be in the range of $0.44 to $0.46 based on 83.2 million estimated diluted weighted average shares outstanding. For the full year fiscal 2024, we are increasing our outlook across the board. We now expect revenue to be in the range of $1.654 billion to $1.658 billion; non-GAAP income from operations to be in the range of $236.3 million to $239.3 million; and non-GAAP net income per share to be in the range of $2.89 to $2.91 based on 82.5 million estimated diluted weighted average shares outstanding. Note that the non-GAAP net income per share guidance for the fourth quarter and full fiscal year 2024 includes a non-GAAP tax provision of approximately 20%.

現在我想談談我們對 2024 財年第四季和全年的展望。我們預計第四季的營收將在 4.29 億美元至 4.33 億美元之間。我們預計非 GAAP 營運收入將在 3,500 萬美元至 3,800 萬美元之間，非 GAAP 每股淨利潤將在 0.44 美元至 0.46 美元之間，基於 8,320 萬股估計稀釋加權平均流通股。對於 2024 財年全年，我們全面上調前景。我們現在預計收入在 16.54 億美元至 16.58 億美元之間；非公認會計原則營運收入將在 2.363 億美元至 2.393 億美元之間；根據估計的 8,250 萬股稀釋加權平均流通股，非 GAAP 每股淨利潤將在 2.89 美元至 2.91 美元之間。請注意，2024 年第四季和整個財年的非 GAAP 每股淨利潤指引包括約 20% 的非 GAAP 稅務撥備。

I'll now provide some context on our guidance. First, we expect Q4 Atlas consumption growth to be impacted by the seasonal slowdown around the holidays. Second, as you think about both sequential and year-over-year revenue growth of Atlas in Q4, keep in mind that in Q4 last year, we had several million dollars more of revenue coming from unused commitments, which we do not expect to occur this quarter. Third, as a result of our strong execution so far this year, we are again raising our non-Atlas revenue expectations for Q4. However, we expect that our non-Atlas revenues will decline sequentially Q4 versus Q3. This is different from our normal pattern as we usually see a seasonal uptick in Q4 due to greater renewal activity.

我現在將提供一些有關我們指導的背景資訊。首先，我們預計第四季度 Atlas 消費成長將受到假期前後季節性放緩的影響。其次，當您考慮 Atlas 在第四季度的環比和同比收入增長時，請記住，去年第四季度，我們的未使用承諾收入增加了數百萬美元，但我們預計這種情況不會發生本季度。第三，由於我們今年迄今的強勁執行力，我們再次提高了第四季度的非 Atlas 收入預期。然而，我們預計第四季度的非 Atlas 收入將比第三季連續下降。這與我們的正常模式不同，因為我們通常會看到由於更新活動增加而導致第四季度出現季節性上升。

The reason for the sequential decline this year is because of the strength we've seen in Q3, including the benefit of multiyear EA deals. Finally, thanks to the strong performance in Q3 and the increased revenue outlook, again -- we are again increasing our assumption for operating margins in fiscal to '24 to 14% at the midpoint of our guidance, an improvement of more than 900 basis points compared to fiscal '23.

今年連續下降的原因是我們在第三季看到的強勁勢頭，包括多年期 EA 交易的好處。最後，由於第三季的強勁表現和收入前景的提高，我們再次將財年營業利潤率的假設提高至 24％，達到指導中點的 14％，提高了 900 個基點以上與23 財年相比。

Our significant margin improvement this year is primarily driven by our revenue outperformance and the fact that we didn't increase our pace of investment as the revenue outlook improved until relatively late in the year. As a result, we achieved greater margin expansion this year that we think is desirable in the short term given the long-term market opportunity ahead of us.

我們今年利潤率的顯著改善主要是由於我們的收入表現出色，以及直到今年相對較晚的收入前景改善時我們才加大投資步伐。因此，我們今年實現了更大的利潤率擴張，鑑於我們面前的長期市場機會，我們認為這在短期內是可取的。

To summarize, MongoDB delivered excellent third quarter results in a difficult environment. We're pleased with our ability to win new business and are demonstrating the operating leverage inherent in our model. While we'll continue to monitor the macro environment, we remain incredibly excited about the opportunity ahead, and we'll continue to invest responsibly to maximize our long-term value.

總而言之，MongoDB 在困難的環境下取得了出色的第三季業績。我們對贏得新業務的能力感到滿意，並展示了我們模型中固有的營運槓桿。雖然我們將繼續監控宏觀環境，但我們仍然對未來的機會感到無比興奮，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。

With that, we'd like to open up to questions. Operator?

至此，我們願意提出問題。操作員？

(Operator Instructions). Our first question comes from Sanjit 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。

Congrats on the results in Q3. When you look at the Atlas growth this quarter, Michael, I know you mentioned that the consumption trends were better than expectations. In terms of the seasonality that you were anticipating and that's what showed in the business in the past 2 years, was that more pronounced than you expected? Or did that come in below in terms of the seasonal uplift that you've seen in Q3?

恭喜第三季的結果。邁克爾，當您查看阿特拉斯本季的成長時，我知道您提到消費趨勢好於預期。就您預期的季節性而言，這就是過去兩年業務中所表現出的情況，這是否比您預期的更加明顯？或者，就您在第三季看到的季節性成長而言，這是否低於預期？

Yes. So just to clarify, Q3 for Atlas came in line with our expectations. We had seen and called out last year seasonality for Q3. We had expected that and incorporated that into our forecast. What we have seen is less variability over the course of the year. And so we assume that, that Q3 seasonality would be more muted this year, and that's exactly what happened and how the quarter played out.

是的。需要澄清的是，Atlas 的第三季符合我們的預期。我們已經看到並指出了去年第三季的季節性。我們已經預料到了這一點，並將其納入我們的預測中。我們看到的是一年中的變化較小。因此，我們假設今年第三季的季節性將更加溫和，而這正是所發生的情況以及該季度的表現。

Understood. And then, Dev, I guess a much bigger picture question. I think the company was founded in 2007, so it's about 17 years into the journey. And if you compare that to some of the large incumbent to the players in the space like an Oracle, around this time, 17 to kind of 20 years in, they started to move away from like the data management database space and into like the application software market.

明白了。然後，Dev，我想這是一個更大的問題。我認為該公司成立於 2007 年，距今已有 17 年的歷史。如果你將其與 Oracle 等該領域的一些大型企業進行比較，大約在 17 到 20 年前，他們開始從資料管理資料庫領域轉向應用程式領域軟體市場。

Is that a vision, particularly within the dawn of the sort of new compute cycle with AI. Is that an analogy that applies to Mongo in terms of its long-term road map in your view?

這是一個願景嗎，尤其是在人工智慧新運算週期的黎明之際。在您看來，這個類比是否適用於 Mongo 的長期路線圖？

Yes. Thanks for your question, Sandeep. What I would say is we've been very clear that we're really pushing our developer data platform strategy, and we think the market is way larger today than it was for Oracle when they were essentially 17 years old. And our developer data platform strategy is really very simply enabling developers use MongoDB for a wide variety of use cases across a wide variety of deployment models, whether it's on-prem, on the cloud, multi-cloud or even at the edge.

是的。謝謝你的提問，桑迪普。我想說的是，我們非常清楚，我們確實在推動我們的開發者資料平台策略，我們認為今天的市場比 Oracle 17 歲時的市場大得多。我們的開發人員資料平台策略實際上非常簡單，使開發人員能夠將 MongoDB 用於各種部署模型的各種用例，無論是在本地端、雲端、多雲還是邊緣。

And so that's really our strategy. We don't see any need to get into the application space itself, and we think that we have a lot of runway ahead of us.

這確實是我們的策略。我們認為沒有必要進入應用程式領域本身，我們認為我們前面還有很多跑道。

Our next question comes from the line of Raimo Lenschow of Barclays.

我們的下一個問題來自巴克萊銀行的 Raimo Lenschow。

Congrats from me as well. I wanted to ask on EA first. Another very strong quarter there. Can you talk a little bit more on the drivers there? Because I do seem to remember you kind of doubled down on sales capacity. I think it was junior sales guys that you wanted to put on existing accounts. Is that kind of the main driver?

我也表示祝賀。我想先問一下EA。另一個非常強勁的季度。您能多談談那裡的司機嗎？因為我似乎確實記得你們的銷售能力加倍了。我認為您希望將初級銷售人員納入現有客戶。這是主要的驅動力嗎？

Or is it more like modernization are kind of picking up a lot more than what we thought would be possible? Can you speak to that because it's like the second quarter in a row where we kind of have better numbers there? And then I have one follow-up for Michael.

或者說，現代化的進展是否比我們想像的多很多？你能談談這一點嗎，因為這就像連續第二季我們的數據有所改善？然後我有一篇關於邁克爾的後續報導。

Yes. So Raimo, with regards to our EA outperformance, I think it really speaks to our run anywhere strategy, where customers really value the ability to build on MongoDB and for essentially future-proof their deployment model, whether they stay on-prem also move to the cloud or move from one cloud to another cloud. And the fact that they can do that without having to rewrite the application is very compelling for customers.

是的。因此，Raimo，就我們的EA 表現而言，我認為這確實說明了我們隨處運行的戰略，客戶真正重視在MongoDB 上構建的能力，以及本質上面向未來的部署模型，無論他們是留在本地還是遷移到雲端或從一個雲端移動到另一個雲端。事實上，他們無需重寫應用程式即可做到這一點，這對客戶來說非常有吸引力。

As you also said, a lot of customers still -- especially the largest customers still have a lot of sunk cost and they want to leverage their existing data infrastructure. So a lot of customers have told us that they will still deploy infrastructure on-prem for the foreseeable future. But what -- by building on MongoDB, they get the benefits of a modern platform and the optionality to also remove the cloud when they're ready to do so.

正如您還所說，許多客戶——尤其是最大的客戶仍然有大量的沉沒成本，他們希望利用現有的資料基礎設施。因此，許多客戶告訴我們，在可預見的未來，他們仍將在當地部署基礎架構。但是，透過在 MongoDB 上進行構建，他們可以獲得現代平台的優勢，並且可以選擇在準備好時刪除雲端。

Yes. The other thing, I know you know, Raimo, but just for the broader audience, we run the business on a channel basis, sales isn't oriented around products. And then also, as we've said before, EA tends to be -- the additional sales of EA tend to be to existing customers. We don't tend to have a ton of new -- brand new customers on EA.

是的。另一件事，我知道你知道，Raimo，但對於更廣泛的受眾來說，我們在通路的基礎上經營業務，銷售並不以產品為導向。然後，正如我們之前所說，EA 的額外銷售往往是針對現有客戶。我們通常不會在 EA 上擁有大量新客戶。

Okay. Perfect. And then the follow-up is more it's around AI. So if I look at the demos that you guys have around Vector Search and how Search is getting a lot better, that seems very compelling. And it seems like really straightforward for our clients to improve their customer experience that they use it for a customer facing up, for example.

好的。完美的。後續更多是圍繞人工智慧。因此，如果我看看你們圍繞向量搜尋進行的演示以及搜尋如何變得更好，這似乎非常引人注目。對於我們的客戶來說，改善客戶體驗似乎非常簡單，例如，他們將其用於面朝上的客戶。

What is the -- what are the implications for gross margins for you, Michael? Like do you have to do a lot more computer to be able to handle it? How should we think about that in terms of extra revenue, but then also extra cost coming through?

邁克爾，這對你的毛利率有什麼影響？就像你需要做更多的計算機才能處理它嗎？我們該如何看待額外收入和額外成本的問題？

Yes. So I think it's a little too early to tell. There's obviously plenty of variability in the workloads depending on the nature of what the underlying application is. So I think it's a little early to give a strong direction to that. I think more broadly on margins, we've certainly been very happy with the margin progress that we've made. I referenced the continued efficiencies that we're driving in Atlas is roughly 2/3 of the business. So as that continues to increase, Atlas still is lower margin overall. And so that will have some impact over the next several years, but we're really pleased on the margin front. But I think too early to make a specific call or quantification on the gross margin impacts of AI.

是的。所以我認為現在說還太早。顯然，根據底層應用程式的性質，工作負載存在很大的變化。所以我認為現在給出明確的方向還為時過早。我認為，從更廣泛的角度來看，我們對利潤率的進展當然感到非常滿意。我提到我們在 Atlas 中推動的持續效率大約佔業務的 2/3。因此，隨著這一數字的持續增加，阿特拉斯的整​​個利潤率仍然較低。因此，這將在未來幾年產生一些影響，但我們對利潤率感到非常滿意。但我認為對人工智慧對毛利率的影響做出具體的判斷或量化還為時過早。

Yes. And Raimo, just to add to that, one of the announcements you also made was that you can now do workload isolation. So for Search or Vector Search functionality, you can scale those nodes independently of your overall cluster. So what that really does is allow customers to really configure their clusters to have the right level of performance at the most efficient cost.

是的。 Raimo，補充一下，您也發布的公告之一是您現在可以進行工作負載隔離。因此，對於搜尋或向量搜尋功能，您可以獨立於整個叢集來擴展這些節點。因此，這真正的作用是允許客戶真正配置他們的集群，以最有效的成本獲得適當的性能水平。

So we've been very sensitive on making sure that based on the different use cases, you can scale up and down different nodes based on your application needs. So by definition, that will be a very compelling value proposition for customers.

因此，我們非常敏感地確保根據不同的用例，您可以根據應用程式的需求擴展和縮小不同的節點。因此，根據定義，這對客戶來說將是一個非常引人注目的價值主張。

One moment, please. Our next question comes from the line of Karl Keirstead of UBS.

稍等一會兒。我們的下一個問題來自瑞銀集團的 Karl Keirstead。

Maybe I'll direct this question to Dev. Dev, I think a lot of people on the line are hearing this refrain about customers, enterprises wanting to get their data estates in order -- in advance of moving forward on AI initiatives. And you even spoke about customers feeling pressure to modernize their data infrastructure.

也許我會把這個問題直接問 Dev。 Dev，我認為​​很多人都聽到了這樣的說法，即客戶、企業希望在推進人工智慧計劃之前整理好自己的數據資產。您甚至談到客戶感受到了實現數據基礎設施現代化的壓力。

I'd just like to ask where we are in that journey. Is this a conversation that your sales teams are having? Or do you feel like this is actually beginning to result in deals and revenue pull through? And if it isn't yet, roughly, when do you think that might start to translate to an actual revenue lift?

我只是想問我們現在處於這個旅程的哪個階段。這是您的銷售團隊正在進行的對話嗎？或者您覺得這實際上已經開始帶來交易和收入的成長？如果還沒有，那麼您認為這大概什麼時候可以開始轉化為實際的收入成長？

Yes. So I'll make a couple of points. Karl, you're absolutely right. There is a lot of focus on data because with AI, data in some way, it becomes a new code. You can train your models with your proprietary data that allows you to really drive much more value and build smarter applications.

是的。所以我會提出幾點。卡爾，你說得完全正確。人們非常關注數據，因為有了人工智慧，數據在某種程度上成為了一種新的程式碼。您可以使用專有資料訓練模型，從而真正推動更多價值並建立更聰明的應用程式。

Now the key thing is that it's operational data because with applications, this data is always constantly being updated. And for many customers, most of those applications are right now running on legacy platforms so that operational data is trapped in those legacy platforms. And you can't really do a batch process of e-tailing all that data into some sort of warehouse and then still able to leverage the real-time use of that data. That's why customers are now much more interested in potentially modernizing these legacy platforms than they ever have before.

現在關鍵是它是操作數據，因為對於應用程式來說，這些數據總是不斷更新。對於許多客戶來說，大多數應用程式現在都在舊平台上運行，因此操作資料被困在這些舊平台中。而且您無法真正進行批次處理，將所有資料透過電子方式儲存到某種倉庫中，然後仍然能夠即時使用該資料。這就是為什麼客戶現在比以往任何時候都對這些遺留平台的現代化更感興趣。

I would say, Karl, to your second part of your question, I would say it's still very, very early days. We definitely believe that this will be one of the largest long-term opportunities for our business. But we're in the very early days. And I've said in the past, there's a risk of overestimating the impact of the short term but underestimating the impact of the long term, we definitely think this is a long-term impact.

卡爾，我想說，對於你問題的第二部分，我想說現在還處於非常非常早期的階段。我們堅信這將是我們業務最大的長期機會之一。但我們還處於早期階段。我過去說過，有高估短期影響但低估長期影響的風險，我們肯定認為這是長期影響。

Okay. Great. And if I could ask a follow-up to my kind of subject. Mike, you had talked on the last call a little bit more about this mix shift away from multiyear Atlas commits. And you were pointing to that as a reason for some of your metrics like DR and I think even cash flow to come under a little pressure. This quarter, I see DR is still under pressure. Cash flow was a little bit better. Can you maybe revisit that phenomenon and describe how it's impacting some of these metrics?

好的。偉大的。如果我可以詢問我的主題的後續情況。麥克，您在上次電話會議上詳細討論了從多年 Atlas 提交中擺脫出來的混合轉變。您指出這是您的一些指標（例如災難復原）的原因，我認為甚至現金流也面臨一點壓力。本季度，我認為 DR 仍面臨壓力。現金流稍微好一點。您能否重新審視這一現象並描述它如何影響其中一些指標？

Yes, a couple of things. As we've said from the beginning, some of those like calculated billings or deferred revenue metrics aren't super helpful or don't provide a ton of insight in terms of how we run the business. We've also talked about how -- over the last couple of years, one of the things we've been trying to do is reduce friction for the sales force. Some of that includes reducing the emphasis around upfront commitments.

是的，有幾件事。正如我們從一開始就說過的，其中一些（例如計算的帳單或遞延收入指標）並不是很有幫助，或者不能提供有關我們如何經營業務的大量見解。我們也討論了在過去幾年中，我們一直在努力做的事情之一就是減少銷售人員的摩擦。其中一些包括減少對前期承諾的重視。

And so that helps accelerate landing new workloads and things like that, and that will flow through or does flow through the financial statements as less upfront deferred and things like that. And so it allows us to sort of synthetically cover more ground from a sales force perspective. And so you do see that continuing to go through.

因此，這有助於加速實現新的工作負載和類似的事情，並且這些工作量將通過或確實通過財務報表，作為較少的預付遞延和類似的事情。因此，它使我們能夠從銷售人員的角度綜合覆蓋更多領域。所以你確實看到這種情況繼續發生。

We shared the stat, the statistic last quarter. The Atlas revenue growth last quarter was 38%, but dollars of committed Atlas declined 15% year-over-year, just as one way to try and help dimensionalize it. We also talked, I think, earlier in the year about how roughly 80% of Atlas doesn't flow through deferred. And so I think all of those data points help kind of line up to explain the rest of what you're seeing and why that's not sort of a helpful forward-looking metric like it might be in other companies. It doesn't kind of give you the insight that maybe people are used to or hope that, that will provide.

我們分享了上個季度的統計數據。 Atlas 上一季的營收成長了 38%，但 Atlas 的承諾金額比去年同期下降了 15%，這只是嘗試幫助實現規模化的一種方法。我想，今年早些時候我們還討論過大約 80% 的 Atlas 沒有通過 deferred。因此，我認為所有這些數據點都有助於解釋您所看到的其餘內容，以及為什麼這不像其他公司那樣是一種有用的前瞻性指標。它並沒有提供你人們可能習慣或希望提供的洞察力。

One moment, please. Our next question comes from the line of Brad Reback of Stifel.

稍等一會兒。我們的下一個問題來自 Stifel 的 Brad Reback。

Michael, maybe following up on that last question in your commentary. At what point should DR stop being a headwind from a financial perspective? When should it stabilize or is this a multiyear trend as you kind of bleed it down?

邁克爾，也許會跟進你評論中的最後一個問題。從財務角度來看，災難復原何時應該停止成為不利因素？它什麼時候應該穩定下來，或者這是一個多年的趨勢，因為你有點讓它流血？

Yes. So I'd say there are a couple of things. Obviously, it's not something we guide to. It's not a key thing that we focus on, but I think the trends will be -- you've got sort of 2 factors. One is overall Atlas mix, right? And so to the extent that Atlas continues to grow, that will provide a headwind on this dynamic.

是的。所以我想說有幾件事。顯然，這不是我們所引導的。這不是我們關注的關鍵問題，但我認為趨勢將是——有兩個因素。一是總體 Atlas 組合，對吧？因此，只要 Atlas 繼續增長，這將為這種動態帶來阻力。

And then similarly, even within the current Atlas footprint, there's this historic commitments that we need to run through renewal cycles and everything else. And so I think this will take a little while still to play out.

同樣，即使在目前的 Atlas 足跡中，我們也需要履行更新週期和其他一切的歷史性承諾。所以我認為這還需要一段時間才能實現。

Great. And then switching gears, Dev, as customers began to trial some of these Copilot code tools will say, what type of feedback have you gotten from them as it relates to the pace with which they've been able to reduce net new workload time to market? How much faster or efficient are customers getting using these tools?

偉大的。然後，開發人員，當客戶開始試用其中一些 Copilot 程式碼工具時，他們會說，您從他們那裡得到了什麼類型的回饋，因為這與他們能夠將淨新工作負載時間減少到市場？客戶使用這些工具的速度或效率有多快？

Yes. We get different answers from a lot of different customers. It really depends on which tool they're using. Without commenting on who's better, who's worse, we definitely see a difference in the quality of the output between the different tools. I think it's going to take some time for these tools to mature. So I think you're seeing a lot of customers do a lot of testing and prototyping.

是的。我們從許多不同的客戶那裡得到了不同的答案。這實際上取決於他們使用的工具。在不評論誰更好、誰更差的情況下，我們確實看到不同工具之間輸出品質的差異。我認為這些工具需要一段時間才能成熟。所以我認為你會看到很多客戶進行了大量的測試和原型設計。

I would also tell you that they're doing a lot of this on internal-facing applications because there's still lots of questions about IP rights and what is potentially copyrightable and then also be licensable if they offer this as a shrink-wrap software or service to their end customers. So we're seeing more of this work on internally facing applications but the productivity gains really do vary by tool and also do vary by the sophistication of the app being built.

我還想告訴你，他們在面向內部的應用程式上做了很多這樣的事情，因為仍然存在很多關於知識產權的問題，以及什麼是潛在的版權，如果他們將其作為收縮包裝軟體或服務提供，那麼也可以獲得許可給他們的最終客戶。因此，我們在面向內部的應用程式上看到了更多的工作，但生產力的提高確實因工具而異，也因所建構的應用程式的複雜程度而異。

So it's hard for me to give you a real number. I know there's people out there quoting 30% or 40% improvement. But it really depends on the customer and the use case and the tool that they're trying to use. So it would be hard for me to give you a specific number.

所以我很難給你一個真實的數字。我知道有人說提高了 30% 或 40%。但這實際上取決於客戶、用例以及他們嘗試使用的工具。所以我很難給你一個具體的數字。

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)。

So earlier this quarter, you hired Mark Porter's replacement, Jim Scharf from AWS, who has a lot of experience in the database industry. Can you just talk about some of his priorities, what you're kind of accelerating in terms of the product road map to sell to larger enterprises?

因此，在本季度早些時候，您聘請了來自 AWS 的 Mark Porter 的繼任者 Jim Scharf，他在資料庫行業擁有豐富的經驗。您能否談談他的一些優先事項，以及您在向大型企業銷售的產品路線圖方面正在加速哪些方面？

Yes. So for those people who don't know Jim's background, he spent about 17 years at AWS. He's had a variety of roles, but last 2 meaningful roles he ran the DynamoDB business at AWS, which is AWS's fastest-growing and largest nonrelational database business. And then he ultimately then took over the Identity Access Management business, which, if you think about it, every AWS customer has to use. So it's a service that has to, not only perform, but perform at massive scale.

是的。對於那些不了解 Jim 背景的人來說，他在 AWS 工作了大約 17 年。他曾擔任過多種角色，但最後兩個有意義的角色是他在 AWS 負責 DynamoDB 業務，這是 AWS 成長最快、規模最大的非關聯式資料庫業務。然後他最終接管了身分存取管理業務，如果你仔細想想，每個 AWS 客戶都必須使用該業務。因此，這項服務不僅必須執行，而且必須大規模執行。

The fact that he's dealt and built 2 mission-critical services for AWS was very appealing to us given our ambitions to kind of -- and the level of scale that we expect our business to ultimately get to at some point in time. He obviously brings us very strong technical DNA. He obviously has a lot of network of relationships in the industry. So we expect him to help us grow the team around the world, leveraging his relationships.

鑑於我們的雄心壯志以及我們期望我們的業務最終在某個時間點達到的規模水平，他為 AWS 處理和構建了 2 項關鍵任務服務這一事實對我們非常有吸引力。顯然他為我們帶來了非常強大的技術DNA。他顯然在業界擁有很多關係網絡。因此，我們希望他能夠利用他的關係來幫助我們在世界各地發展團隊。

And in terms of priorities, I mean, right now, he's still kind of really assessing the current state of the business. He's been quite impressed with the quality of talent that we have, but he's really kind of -- what I encourage them to do is we need to go slow to go fast. So take his time in terms of really understanding the business, understanding the team, understanding the code base before he starts really prioritizing what to do. And it's not like this there's some things massively broken. It's really helping us set up to scale to the next level.

就優先事項而言，我的意思是，現在他仍在真正評估當前的業務狀況。他對我們擁有的人才品質印象深刻，但他真的很——我鼓勵他們做的是我們需要放慢腳步，才能走得快。因此，在開始真正確定要做什麼的優先事項之前，請花點時間真正了解業務、了解團隊、了解程式碼庫。並不是這樣的，有些東西已經嚴重損壞了。它確實幫助我們擴大規模到了新的水平。

Great. And a follow-up for Michael. I know you talked about how Atlas consumption during Q3 was in line with your expectations. I'm just curious, given there were a lot of volatility in, at least, the equity markets and the economy, did it -- was there any more variability within the quarter? In other words, did it start weaker and stronger? And then I'm just curious, throughout the month of November, had things kind of further improved ahead of the holiday seasonality? Just any additional color would be helpful.

偉大的。以及麥可的後續行動。我知道您談到了第三季 Atlas 的消費情況與您的預期相符。我只是很好奇，考慮到至少股市和經濟存在很大的波動性，本季內是否還有更多的波動？換句話說，它是開始變得越來越弱還是越來越強？然後我很好奇，整個 11 月，在假期到來之前，情況是否有進一步改善？只要任何額外的顏色都會有幫助。

Yes. So like you said, Q3 Atlas results were in line with our expectations. There was a seasonal benefit to Q3 relative to Q2. But given the fact that we've seen less variability in consumption in fiscal '24, we had expected that to be smaller than it was in fiscal '23. And that's exactly how it played out. The seasonal improvement, as it relates to Q3, is a little bit more in the back half of the quarter. As it relates to Q4, typically, the back half is weaker given the holiday slowdown. And so hopefully, that helps people understand a little bit.

是的。正如您所說，第三季 Atlas 的結果符合我們的預期。相對於第二季度，第三季度存在季節性優勢。但鑑於我們發現 24 財年的消費波動較小，我們預計變化將小於 23 財年。結果就是這樣。與第三季相關的季節性改善在本季後半段有所改善。就第四季而言，由於假期放緩，後半段通常會疲軟。希望這能幫助人們理解一點。

One moment, please. Our next question comes from the line of Kash Rangan of Goldman Sachs.

稍等一會兒。我們的下一個問題來自高盛的卡什·蘭根（Kash Rangan）。

Dev and Michael, happy holidays, congrats on the results. So going into calendar '24, how does the management team feel relative to going in to come to '23 with respect to how macro conditions are no longer impacting or maybe they are impacting some aspects of the business? Any verticals that stand out that you feel particularly excited about? So just wanted to understand how MongoDB is therefore fitting into customer priorities as you get into 2024?

Dev 和 Michael，節日快樂，祝賀結果。那麼，進入 24 日曆年，管理團隊相對於 23 日曆年的宏觀狀況不再產生影響或可能正在影響業務的某些方面有何感受？有哪些突出的垂直領域讓您感到特別興奮？那麼只是想了解 MongoDB 如何適應進入 2024 年的客戶優先事項？

Hi, Kash, thanks for the question. I think compared from last year, this year, we don't see things getting worse, but we don't see things getting better. Where I'd say last year with the Fed raising rates, you could really sense that people are getting much more cautious. And it was -- there was probably more negativity in terms of the outlook coming into calendar 2023.

嗨，卡什，謝謝你的提問。我認為與去年相比，今年我們沒有看到情況變得更糟，但我們也沒有看到情況變得更好。去年我想說，隨著聯準會升息，你真的可以感覺到人們變得更加謹慎。就 2023 年的前景而言，可能會有更多負面情緒。

So that being said, we definitely see innovation being a priority for customers. We clearly are, I would say, in the distinction between must-have and nice-to-have clearly in the first category. But customers also, as I mentioned in the prepared remarks, we remain focused on being sensitive to costs and ensuring that any investments, they may have a high ROI.

話雖這麼說，我們確實認為創新是客戶的首要任務。我想說，我們顯然在區分「必備」和「最好有」時屬於第一類。但正如我在準備好的演講中提到的那樣，客戶也仍然專注於對成本敏感並確保任何投資都可以獲得高投資回報。

So we feel that we're well-positioned in terms of use cases or segments. I would say, in general, there's no real kind of material change in any -- across any vertical industry or geography. We do see -- I mean we were at re:Invent last week, and we had an amazing set of conversations with lots of senior level customers. I think we're really viewed as a mission-critical platform by all our customers. And I think people view us as a platform that they can bet on long term.

因此，我們認為我們在用例或細分市場方面處於有利位置。我想說，總的來說，在任何垂直行業或地區，都沒有真正的實質變化。我們確實看到了——我的意思是我們上週參加了 re:Invent，我們與許多高級客戶進行了一系列令人驚嘆的對話。我認為我們確實被所有客戶視為關鍵任務平台。我認為人們將我們視為一個可以長期押注的平台。

And so we see less, I would say, focus on like point solutions and more about like trying to leverage MongoDB for more and more use cases. And I would say that, that's pretty consistent across industries and geographies.

因此，我想說的是，我們很少關注類似的點解決方案，而是更專注於嘗試利用 MongoDB 來實現越來越多的用例。我想說的是，這在各個行業和地區都是非常一致的。

Yes. The only other thing I'd add, Kash, is clearly, things have stabilized. We are not guiding fiscal '25. But just looking out, there's clearly a difficult EA and non-EA compare that people should sort of keep in mind. And I think the big assumption or the big determiner will be people's macro outlook in terms of how that affects the fiscal '25 numbers. But those are probably the key things to keep in mind.

是的。卡什，我要補充的唯一一件事是，情況顯然已經穩定下來。我們不是在指導 25 財年。但仔細觀察，顯然人們應該牢記 EA 和非 EA 之間的困難比較。我認為，重大假設或重大決定因素將是人們對 25 財年數據的宏觀前景的影響。但這些可能是需要記住的關鍵事項。

Our next question comes from the line of Ittai Kidron of Oppenheimer.

我們的下一個問題來自奧本海默的 Ittai Kidron。

Nice numbers. Michael, I want to go back to one of the comments in your prepared remarks. I think you talked about how you expect non-Atlas business to be down quarter-over-quarter in the fourth quarter. Because I think the third quarter had multiple multiyear deals, correct me if I've got this wrong, I guess my question is why would that affect 4Q unless there was a pull forward also on just multiyears? Is there a pull forward element from 4Q into 3Q in your non-Atlas business?

不錯的數字。邁克爾，我想回到你準備好的發言中的其中一條評論。我想您談到了您預計第四季度非 Atlas 業務將環比下降。因為我認為第三季度有多項多年期交易，如果我弄錯了，請糾正我，我想我的問題是為什麼這會影響第四季度，除非也只有多年期交易有所提前？您的非 Atlas 業務是否存在從第四季度到第三季度的拉動因素？

No. It's not about a pull forward. It's just when you take into account the 606 impact of a multiyear deal, you wind up recognizing a lot of upfront license revenue. And so when you think about what that means on a sequential basis, you see the difference of the delta there.

不，這不是向前推進。只是當您考慮到多年協議的 606 影響時，您最終會認識到大量的預付許可收入。因此，當您按順序思考這意味著什麼時，您會看到其中的增量差異。

I think the only other thing, Ittai, just for people is, given the strength that we've seen of EA throughout the year, but including Q3, we effectively raised our outlook, if you will, in Q4, in part given the strength of EA even though we don't guide to product, Atlas was in line with our expectations. EA outperformed in Q3. And our full year raise was more than the beat in Q3. And I think that shows the kind of continued strength within EA.

我認為唯一的另一件事，Ittai，對人們來說是，考慮到我們全年看到EA 的實力，但包括第三季度，我們有效地提高了我們的前景，如果你願意的話，在第四季度，部分考慮到實力儘管我們不提供產品指導，但 EA 的 Atlas 符合我們的預期。 EA 在第三季的表現優於大盤。我們全年的加薪幅度超過了第三季的水準。我認為這顯示了 EA 內部的持續實力。

Got it. Helpful. And then, Dev, on Vector Search, I know this is kind of a fresh out of the oven here, but maybe you can talk about the opportunity here on a per customer basis, how do I think about the dollar potential here. And is there one common vendor out there that you expect to see more in competition for those types of use cases?

知道了。有幫助。然後，Dev，關於向量搜索，我知道這有點新鮮，但也許你可以在每個客戶的基礎上談論這裡的機會，我如何看待這裡的美元潛力。您是否希望看到有一個常見供應商在這些類型的用例方面展開更多競爭？

Yes. So let me start with the second question first. I would say that I think 6, 9 months ago, there was a lot of interest in Vector databases and there were some point solutions that got a lot of name recognition and a lot of people are wondering, is there a risk that we could be disrupted by them? And at that point in time, we made it clear that we believe Vectors were really another form of an index and that every database platform would ultimately incorporate Vectors into their architecture.

是的。那我先從第二個問題開始。我想說的是，我認為 6、9 個月前，人們對 Vector 資料庫很感興趣，並且有一些單點解決方案得到了很多人的認可，很多人都想知道，我們是否存在可能被他們打擾了？那時，我們明確表示，我們相信向量實際上是索引的另一種形式，並且每個資料庫平台最終都會將向量合併到其架構中。

And the winner really would be the technology that made the Vector functionality very integrated and cohesive as part of the developer workflow. I would argue that it's really played out. As I said in the prepared remarks, there was a recent analysis done by a consultancy firm called Retool that really spoke to lots of customers, and we came out of top on -- in terms of NPS.

獲勝者確實是使 Vector 功能非常整合且具有凝聚力的技術，作為開發人員工作流程的一部分。我認為這真的已經結束了。正如我在準備好的演講中所說，一家名為 Retool 的顧問公司最近進行了一項分析，該分析確實與許多客戶進行了交流，我們在 NPS 方面名列前茅。

And by the way, our product was a preview product. It wasn't even the GA product. We've seen a lot of demand from customers. And we feel like this is a big, big opportunity. Again, it's early days. It's going to take time to materialize, but this is, again, one of the other big growth opportunities for our business.

順便說一句，我們的產品是預覽產品。它甚至不是 GA 產品。我們看到了客戶的大量需求。我們覺得這是一個非常非常大的機會。再說一遍，現在還為時過早。這需要時間才能實現，但這又是我們業務的其他重大成長機會之一。

That being said, in terms of the revenue opportunity, it's really hard to quantify now because the use cases that customers are starting with are still kind of, I would say, early event. Because people are still playing around with the technology.

話雖這麼說，就收入機會而言，現在確實很難量化，因為客戶開始使用的用例仍然是早期事件。因為人們仍在玩弄這項技術。

But we are seeing, as I mentioned, UKG is using it to essentially provide an AI-powered assistant for its people. One Energy, European energy company is using terabytes of geospatial data and is using Vectors to basically get better insights in terms of the images that they're getting from the work they're doing in terms of drilling for oil.

但正如我所提到的，我們看到 UKG 正在使用它本質上為其員工提供人工智慧助理。歐洲能源公司 One Energy 正在使用數 TB 的地理空間數據，並使用向量來從石油鑽探工作中獲得的圖像中獲得更好的見解。

So it's still very, very early days. So hard to give you like an exact numbers. Even today, even in our general non-AI workloads, the workload variety can vary a lot depending on the customer, the number of users, the amount of data. So I think it's going to be similar to our core business, which is that just really depends on the use case.

所以現在還處於非常非常早期的階段。很難給你一個確切的數字。即使在今天，即使在我們一般的非人工智慧工作負載中，工作負載的種類也會根據客戶、使用者數量、資料量的不同而有很大差異。所以我認為這將與我們的核心業務類似，這實際上取決於用例。

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。

Wanted to ask a question around the customer count greater than 100,000. It looks like a real nice result this quarter. Is there any change going on there in terms of the trajectory or the path for customers to get to that level? In other words, are they starting bigger? Are they landing bigger? Or are they just getting to that point faster? And what would be driving those 2 things?

想問一個關於客戶數量超過100,000的問題。看起來本季的結果非常好。客戶達到這一水平的軌跡或路徑是否有任何變化？換句話說，他們開始變得更大了嗎？他們著陸更大嗎？或者他們只是更快地達到這一點？驅動這兩件事的因素是什麼？

Yes, I'm glad you called that out, Brad. Yes, we're -- I think we added 117 -- 100,000 customers this quarter, which is the largest add, I think, in the company's history. What I think it really speaks to is that customers are increasingly viewing MongoDB as a mission-critical platform. They're going to run more and more workloads on MongoDB. So by definition, it's rare that one workload on its own will drive that kind of revenue.

是的，我很高興你這麼說，布拉德。是的，我認為本季我們增加了 117 名客戶 10 萬名，我認為這是公司歷史上增加最多的客戶。我認為它真正說明的是，客戶越來越多地將 MongoDB 視為任務關鍵型平台。他們將在 MongoDB 上運行越來越多的工作負載。因此，根據定義，一項工作負載本身很少能帶來這種收入。

So the multiple workloads and really viewing us as a standard part of their infrastructure stack is what's really driving that number. And we're obviously happy to see the results of that. And we think that, that's just indication, as I said earlier, where people are consolidating onto a few vendors. They recognize that we offer support for a broad set of use cases. We are truly a general-purpose, mission-critical platform and that their developers really love using MongoDB.

因此，多種工作負載以及真正將我們視為其基礎設施堆疊的標準部分才是推動這一數字的真正原因。我們顯然很高興看到這樣做的結果。我們認為，正如我之前所說，這只是表明人們正在整合到少數供應商。他們認識到我們為廣泛的用例提供支援。我們是一個真正的通用、關鍵任務平台，他們的開發人員非常喜歡使用 MongoDB。

Wonderful to hear. And then one more, if I may, please. On the commentary around customers viewing Mongo as that platform. With some of these newer workloads besides Search, like Relational Migrator Atlas streaming, do you -- are you finding that, that receptivity for customers who want to run search within one single solution, is that also the case for streaming and Relational? I'm just trying to get a sense for those cycles and how those might ramp on that platform capability?

很高興聽到。如果可以的話，請再來一張。關於將 Mongo 作為該平台的客戶的評論。除了搜尋之外，還有一些較新的工作負載（例如Relational Migrator Atlas 串流），您是否發現，對於想要在單一解決方案中運行搜尋的客戶的接受度，串流和關係也是如此？我只是想了解這些週期以及它們如何增強該平台功能？

Yes. So actually, yes, one of the reasons we actually built search is because we got feedback from our customers. In many instances, a lot of our customers were dual homing data to MongoDB and to some sort of search database. So consequently, not only had to manage 2 databases, keep that data in sync, but also manage the plumbing that connected those 2 database platforms. And customers told us they much would -- it's like we don't understand why you're not offering a solution because we much rather have it all in one platform with one API.

是的。所以實際上，是的，我們實際建立搜尋的原因之一是因為我們收到了客戶的回饋。在許多情況下，我們的許多客戶都將資料雙歸到 MongoDB 和某種搜尋資料庫。因此，不僅需要管理 2 個資料庫、保持資料同步，還要管理連接這 2 個資料庫平台的管道。客戶告訴我們，他們非常願意 - 就像我們不明白為什麼您不提供解決方案一樣，因為我們更願意將所有內容集中在一個平台上，並使用一個 API。

And that ultimately drove our desire to build out our search functionality, which is really becoming more and more popular. So the point for customers is that if you can remove friction in terms of how they can use the platform, leverage the platform, have one set of kind of semantics in terms of -- to address a broad set of use cases, it really simplifies the data architecture. And the more you simplify data architecture, the more nimble you can be and the more cost-effective you can be. And I think that's what's really resonating with customers.

這最終推動了我們建立搜尋功能的願望，該功能確實變得越來越流行。因此，對於客戶而言，如果您能夠消除他們如何使用平台、利用平台、擁有一套語義來解決廣泛的用例方面的摩擦，那麼它確實會簡化資料架構。資料架構越簡化，您就越靈活，並且更具成本效益。我認為這才是真正引起客戶共鳴的原因。

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

我們的下一個問題來自 RBC 的 Rishi Jaluria。

Maybe I want to start by diving a little bit into Relational Migrator. Dev, I know you said it's definitely early days. But where you are seeing usage of it, maybe you can give us a little bit of color, what sort of workloads are these that customers are utilizing the tool for. What does kind of that time line look like? Any color you can give there in terms of early adoption would be really helpful. And then I've got a quick follow up.

也許我想先深入了解關係遷移器。 Dev，我知道你說過現在還太早。但是，在您看到它的使用情況時，也許您可以給我們一些信息，即客戶正在使用該工具執行哪些類型的工作負載。那條時間線是什麼樣的？您可以在早期採用方面提供的任何顏色都會非常有幫助。然後我得到了快速跟進。

Yes. So again, as you can imagine, given the -- a lot of these legacy platforms have been around for between 30 to 40 years, a lot of people have a large repository of legacy apps. And migrating off a legacy platform to another platform does require work. It requires essentially 3 things. One, you have to map the schema of the old platform onto the new platform.

是的。因此，正如您可以想像的那樣，鑑於許多遺留平台已經存在了 30 到 40 年，許多人擁有大量遺留應用程式儲存庫。從舊平台遷移到另一個平台確實需要工作。它基本上需要三件事。第一，您必須將舊平台的架構映射到新平台。

You then have to move the data and then you have to rewrite the application code. And those 3 things took some time. So we heard feedback. When we took the company public, you might remember that 30% of our net new business at the time went public was actually Relational Migration.

然後您必須移動數據，然後必須重寫應用程式程式碼。這三件事花了一些時間。所以我們聽到了回饋。當我們將公司上市時，您可能還記得，我們​​當時上市的淨新業務中有 30% 實際上是關係遷移。

So customers were undertaking the heavy lifting because they were in such pain and wanted to move to a more modern platform. But clearly, that pain can basically be a bit of a tax on switching costs. And so essentially, we build tooling based on feedback from customers to start automating the schema mapping and the data movement.

因此，客戶正在承擔繁重的工作，因為他們感到非常痛苦，並且希望遷移到更現代的平台。但顯然，這種痛苦基本上可能會增加轉換成本。因此，本質上，我們根據客戶的回饋建立工具，以開始自動化模式映射和資料移動。

Now with the availability of Gen AI, you can also now start automating the cogeneration associated with rebuilding or rebuilding an application. And essentially, what -- rather than thinking about just moving the app in one lock step, we can actually break down a monolithic relational app into micro services and start cleaving off different parts of the services first, so it can be a much more efficient and also more ROI, quicker ROI in some of the investments they're making.

現在，隨著 Gen AI 的推出，您現在還可以開始自動化與重建或重建應用程式相關的熱電聯產。從本質上講，我們實際上可以將一個整體的關係應用程式分解為微服務，然後首先開始分割服務的不同部分，而不是僅僅考慮以一個鎖定步驟移動應用程序，這樣它就可以變得更加高效他們正在進行的一些投資也能獲得更高的投資報酬率、更快的投資報酬率。

So there's a big, big opportunity here for us to get. But again, I want to be very clear, we view this as a long-term growth opportunity. We're still in the very early days. You've got some really interested customers, who are doing some interesting things in working with us on pilots. Our engineering and product and field teams are really focused on this, but we're in the very, very early days of really automating Relational Migrator to the next level, leveraging Gen AI.

所以我們有一個非常非常大的機會。但我想再次明確，我們認為這是一個長期成長機會。我們仍處於早期階段。你們有一些非常感興趣的客戶，他們在與我們合作進行試點時做了一些有趣的事情。我們的工程、產品和現場團隊確實專注於這一點，但我們正處於利用 Gen AI 將關係遷移器真正自動化到新水平的非常非常早期的階段。

All right. Wonderful. That's really helpful. And then I wanted to ask about MongoDB serverless. I know this is something you've kind of had -- at least has been talking about for a while. Given a lot of the concerns around cloud optimization and rationalization and customers overpaying and having to figure out how to optimize our footprint, it feels like that could be a natural tailwind for MongoDB serverless, especially because you were early to embrace it.

好的。精彩的。這真的很有幫助。然後想問MongoDB Serverless。我知道這是你曾經經歷過的事情——至少已經談論了一段時間了。考慮到對雲端優化和合理化的許多擔憂，以及客戶支付過高的費用以及必須弄清楚如何優化我們的足跡，感覺這可能是MongoDB 無伺服器的自然推動力，特別是因為您很早就接受了它。

Can you talk a little bit about what you're seeing in terms of adoption there, how we should be thinking about that opportunity? And maybe just kind of what this could look like over the next several years in terms of serverless adoption versus traditional consumption adoption in Atlas.

您能否談談您在採用方面所看到的情況，我們應該如何考慮這個機會？就 Atlas 中的無伺服器採用與傳統消費採用而言，也許這就是未來幾年的情況。

Yes. So just to be clear, when we talk about serverless, basically, what customers think about is that they don't have to start thinking about capacity planning, that the workload can scale up and scale down based on the needs of whatever the use case is and what the compute and other resource needs are. And so there's been a lot of interest from customers.

是的。因此，需要明確的是，當我們談論無伺服器時，基本上，客戶想到的是他們不必開始考慮容量規劃，工作負載可以根據任何用例的需求擴展和縮減以及計算和其他資源需求是什麼。因此，客戶對此表現出了極大的興趣。

At first stage, it was a lot of the ephemeral femoral workloads, where they didn't want to go provision a dedicated cluster. They wanted to be able to leverage our serverless functionality. We think long term that almost every workload will become serverless. Because over time, that will be the way most applications are provisioned. But we're in the early days and the receptivity and use of our service functionality has been very high.

在第一階段，有許多短暫的股骨工作負載，他們不想配置專用叢集。他們希望能夠利用我們的無伺服器功能。我們認為從長遠來看，幾乎所有工作負載都將變成無伺服器。因為隨著時間的推移，這將成為大多數應用程式的配置方式。但我們還處於早期階段，我們服務功能的接受度和使用率都非常高。

And you're right, it's -- for those legacy platforms that they can't offer similar solutions, MongoDB becomes that much more attractive because a development team and architecture team doesn't have to worry about capacity planning. They can just build the app, and they know in the background our infrastructure can scale up and down as their usage -- as the usage goes up and down.

你是對的，對於那些無法提供類似解決方案的遺留平台，MongoDB 變得更具吸引力，因為開發團隊和架構團隊不必擔心容量規劃。他們只需建立應用程序，並且在後台知道我們的基礎設施可以隨著其使用量的增加和減少而擴展和縮小——隨著使用量的增加和減少。

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。

This is Hannah on for Brent. Just one for me. Subscription gross margins remained above 80% for the second straight quarter, even with that continued mix shift to Atlas. I know you mentioned efficiency improvement to Atlas, but are we at a structural point, Michael, where the scale of gross margins can remain at that 80%-plus range into the next year?

這是布倫特的漢娜。只給我一個。即使繼續向 Atlas 進行組合轉移，訂閱毛利率仍連續第二季維持在 80% 以上。我知道您向 Atlas 提到了效率提升，但邁克爾，我們是否正處於一個結構點，毛利率規模可以在明年保持在 80% 以上的範圍？

Yes. So what I would say is I do not think -- I think if you think about it, Atlas gross margins continue to be lower than Enterprise Advanced gross margins. And while we're very pleased with the 80% margin performance on a subscription margin basis in Q3. Atlas is "only 2/3". And so there is still a delta between the two. And so I think that, that will have a slightly dilutive effect origins as Atlas increases as a percent of overall revenue.

是的。所以我想說的是，我不認為 - 我認為如果你仔細想想，Atlas 的毛利率仍然低於 Enterprise Advanced 的毛利率。雖然我們對第三季認購利潤率達到 80% 的利潤率表現感到非常滿意。阿特拉斯「只有2/3」。因此兩者之間仍然存在差異。因此，我認為，隨著 Atlas 佔總收入百分比的增加，這將產生輕微的稀釋效應。

Our next question comes from the line of Patrick Colville of Scotiabank.

我們的下一個問題來自豐業銀行的派崔克·科爾維爾。

This is Joe Vandrick on for Patrick Colville. As of 3Q, it looks like about 29% of direct sales customers are spending over $100,000 on the platform. Just curious where you think that percentage can trend over the longer term. And kind of how big the opportunity is within these existing direct sales customer accounts.

我是帕特里克·科爾維爾的喬·範德里克。截至第三季度，大約 29% 的直銷客戶在該平台上的支出超過 10 萬美元。只是好奇您認為該百分比的長期趨勢如何。這些現有的直銷客戶帳戶中的機會有多大。

Yes, Joe. I would say that we still believe that we have a very small percentage of wallet share in most accounts. And so obviously, the smaller customer, the bigger the wallet share, but in most direct sales customers, our percent of wallet share is still quite small. So we see a big opportunity there.

是的，喬。我想說的是，我們仍然相信我們在大多數帳戶中所佔的錢包份額很小。顯然，客戶越小，錢包份額就越大，但在大多數直銷客戶中，我們的錢包份額所佔的百分比仍然很小。所以我們在那裡看到了一個巨大的機會。

And as we talked about in terms of our new business, a big part of our new business came from acquiring new workloads with existing customers. And that is a big focus for our go-to-market teams. And the runway is quite long for that trend to continue.

正如我們談到的新業務一樣，我們新業務的很大一部分來自於從現有客戶那裡獲取新的工作負載。這是我們的市場推廣團隊關注的重點。而且這種趨勢要持續下去還有很長的路要走。

Great. And just one more for me. I mean you kind of touched on this, but what's the feedback been from those customers, who have used Vector Search in preview? And then obviously, with Vector Search comes quite a bit more data. So how are you making sure that customers don't receive a surprise bill and end up unhappy?

偉大的。還給我一個。我的意思是您有點觸及這一點，但是那些在預覽版中使用過向量搜尋的客戶的回饋是什麼？顯然，向量搜尋帶來了更多的數據。那麼，您如何確保客戶不會收到意外帳單並最終感到不高興呢？

Yes. So as we mentioned earlier, the feedback on our Vector Search has been very high, even when it was in public preview, we were getting a lot of feedback. And then with this report that came out. Obviously, we don't talk to people, who are using alternatives. We just talk to folks, our own customers. But we're pleased to see that out of all the products available in the marketplace, our own preview product had the highest NPS score.

是的。正如我們之前提到的，我們的向量搜尋的回饋非常高，即使在公開預覽版中，我們也收到了很多回饋。然後這份報告就出來了。顯然，我們不會與正在使用替代方案的人交談。我們只是與人們、自己的客戶交談。但我們很高興地看到，在市場上的所有產品中，我們自己的預覽產品具有最高的 NPS 分數。

So then if you unpack that, why do customers like using MongoDB? Because it's one tightly integrated solution. You can tightly integrate capturing Vector data, Metadata data and then data regarding the particular use case. And that becomes very, very attractive. It just becomes much more seamless and easier to use versus either using point solutions or some [cloggy] solution that's been put together.

那如果你仔細分析一下，為什麼客戶喜歡使用 MongoDB？因為它是一種緊密整合的解決方案。您可以緊密整合式擷取向量資料、元資料資料以及有關特定用例的資料。這變得非常非常有吸引力。與使用單點解決方案或某些組合在一起的[堵塞]解決方案相比，它變得更加無縫且更易於使用。

So I think that's the big reason about how we remove friction from a developer's workflow and why the MongoDB approach makes us so much better to use than, say, any other alternative approach. In terms of your question around the amount of data and the data builds, obviously, Vectors can be memory-intensive. And the amount of Vectors you generate will obviously drive the amount of usage on those nodes.

因此，我認為這就是我們如何消除開發人員工作流程中的摩擦以及為什麼 MongoDB 方法使我們比任何其他替代方法更好使用的重要原因。就您關於資料量和資料建構的問題而言，顯然，向量可能是記憶體密集型的。您產生的向量數量顯然會驅動這些節點上的使用量。

That's one of the reasons we also introduced dedicated search nodes so you can asymmetrically scale particular nodes of your application, especially your search nodes without having to increase the overall size of your cluster. So you're not, to your point, soft for the big bill for underlying usage, for nonusage.

這就是我們還引入專用搜尋節點的原因之一，以便您可以不對稱地擴展應用程式的特定節點，尤其是搜尋節點，而無需增加叢集的整體大小。因此，就您的觀點而言，您不會對基礎使用或不使用的巨額帳單心軟。

So you only scale the nodes that are -- really need that incremental compute and memory versus nodes that don't. And that becomes a much more cost-effective way for people to do this. And obviously, that's another differentiator for MongoDB.

因此，您只需擴展真正需要增量計算和記憶體的節點，而不是不需要的節點。對人們來說，這成為一種更具成本效益的方式。顯然，這就是 MongoDB 的另一個與眾不同之處。

Thank you. That is all the time that we have today for today's conference. I'd like to turn the call back over to Dev Ittycheria, CEO, for any closing remarks.

謝謝。這就是我們今天會議的全部時間。我想將電話轉回給執行長 Dev Ittycheria，讓其發表結束語。

Thank you. I appreciate everyone joining the call today. I just want to reiterate that we had another strong quarter of new business performance, validating the value proposition of our developer data platform and our run anywhere strategy.

謝謝。我感謝今天大家加入電話會議。我只是想重申，我們的新業務業績又一個強勁的季度，驗證了我們的開發人員資料平台的價值主張和我們隨處運作策略的價值。

We are seeing strong momentum on our AI strategy, especially Atlas Vector Search, which is emerging as a best-in-class solution for building powerful AI applications. And we continue to help customers drive greater efficiency while also accelerating their pace of innovation.

我們看到人工智慧策略的強勁勢頭，尤其是 Atlas Vector Search，它正在成為建立強大人工智慧應用程式的一流解決方案。我們持續幫助客戶提高效率，同時加快創新步伐。

So with that, I appreciate your time, and we'll talk to you soon. Take care.

因此，非常感謝您抽出時間，我們很快就會與您交談。小心。

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

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。