MongoDB Inc (MDB) 2025 Q3 法說會逐字稿

Good day. And thank you for standing by. Welcome to the MongoDB third-quarter fiscal year 2025 conference call. (Operator Instructions)

再會。感謝您的支持。歡迎參加 MongoDB 2025 財政年度第三季電話會議。（操作員說明）

Please be advised that today's conference is being recorded. I would now like to turn the call over to your speaker for today, Brian Denyeau, please go ahead.

請注意，今天的會議正在錄製中。現在我想將電話轉給今天的發言人 Brian Denyeau，請繼續。

Thank you, Lisa. Good afternoon and thank you all for joining us today to review MongoDB's third-quarter fiscal 2025 financial results, which we announced in our press release issued after the close of the market today. Joining me the call today are Dev Ittycheria, President and CEO of MongoDB; and Michael Gordon, MongoDB's COO and CFO.

謝謝你，麗莎。下午好，感謝大家今天與我們一起回顧 MongoDB 的 2025 財年第三季財務業績，我們在今天收盤後發布的新聞稿中宣布了這一結果。今天加入我的電話會議的是 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, our expectations for the macroeconomic environment in fiscal 2025 and the impact of AI, the benefits of our product platform, our competitive landscape, customer behaviors, our financial guidance, and our planned investments and growth opportunities in AI. These statements are subject to a variety of risks and uncertainties, including the results of operations and financial condition that cause actual results to differ materially from our expectations.

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在人工智慧方面的規劃投資和成長機會。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經營績效和財務狀況。

For a discussion of material risks and uncertainties that could affect our actual results, please refer to the risks described in our quarterly report on Form 10-Q for the quarter ended July 31, 2024, that we filed with the SEC on August 30, 2024. Any forward-looking statements made on this call reflect our views only as of today, and we undertake no obligation to update them, except as required by law.

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 2024 年 8 月 30 日向 SEC 提交的截至 2024 年 7 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 in the Investor Relations portion of our website for a reconciliation of these measures to the most directly comparable GAAP financial measure. With that, I'd like to turn the call over to Dev. Dev?

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。開發？

Thanks, Brian, and thank you to everyone for joining us today. I'm pleased to report that we had a strong quarter of new business and executed well against our large market opportunity. Let's begin by reviewing our third quarter results before giving you a broader company update.

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，我們季度的新業務表現強勁，並且在巨大的市場機會中表現出色。讓我們先回顧一下我們第三季的業績，然後再向您提供更廣泛的公司最新情況。

We generated revenue of $529 million, a 22% year-over-year increase and above the high end of our guidance. Atlas revenue grew 26% year over year, representing 68% of total revenue. We generated non-GAAP operating income of $101 million for a 19% non-GAAP operating margin, and we ended the quarter with over 52,600 customers.

我們的收入為 5.29 億美元，年成長 22%，高於我們指導的上限。Atlas營收年增26%，佔總營收的68%。我們的非 GAAP 營業收入為 1.01 億美元，非 GAAP 營業利潤率為 19%，本季末我們擁有超過 52,600 名客戶。

Overall, we are pleased with our performance in the third quarter. We had a strong new business quarter, and we're happy with our new workload acquisition on Atlas.

總體而言，我們對第三季的表現感到滿意。我們的新業務季度表現強勁，我們對 Atlas 上新的工作負載收購感到滿意。

Our non-Atlas business significantly exceeded expectations, in part because we benefited from a few large multiyear deals as customers continue to value our run anywhere strategy, and want to build a deeper, longer-term relationship with MongoDB. Atlas consumption was slightly better than expected in a macro environment that we would characterize as largely consistent with what we saw in the first half of the year. Michael will cover consumption trends in more detail.

我們的非 Atlas 業務大大超出了預期，部分原因是我們受益於一些大型的多年期交易，因為客戶繼續重視我們的 Run Anywhere 策略，並希望與 MongoDB 建立更深入、更長期的關係。在宏觀環境下，阿特拉斯消費略好於預期，我們認為與上半年的情況大致一致。麥可將更詳細地介紹消費趨勢。

Retention rates remained strong in Q3, demonstrating the mission-criticality of our platform. On our Q1 earnings call, we shared with you the three major strategic initiatives that we believe will enable us to maximize our long-term opportunity. I want to give you an update on the progress we're making on those initiatives.

第三季的保留率仍然很高，這證明了我們平台的任務關鍵性。在第一季財報電話會議上，我們與您分享了三項主要策略舉措，我們相信這些舉措將使我們能夠最大限度地發揮長期機會。我想向您介紹我們在這些舉措上取得的最新進展。

First, we are increasing our investment in the enterprise channel since we see the strongest returns in this part of the market. Specifically, we're expanding our strategic account program going to next year as we see more accounts that will benefit from incremental investment.

首先，我們正在增加對企業通路的投資，因為我們看到這部分市場的回報最為強勁。具體來說，我們將把我們的策略客戶計劃擴展到明年，因為我們看到更多的客戶將從增量投資中受益。

In addition, we're investing time and resources to educate developers in large enterprise accounts and up-level their MongoDB skills. These organizations have thousands of developers and as we penetrate them more deeply, we encounter developers who have historically only built SQL applications and simply do not know how to use MongoDB to its full potential.

此外，我們還投入時間和資源來培訓大型企業帳戶的開發人員並提高他們的 MongoDB 技能。這些組織擁有數千名開發人員，隨著我們更深入地了解它們，我們遇到的開發人員歷史上只建置過 SQL 應用程序，根本不知道如何充分利用 MongoDB 的潛力。

In our experience, educating these developers on the benefits of MongoDB drives significant incremental adoption of our platform. To fund these upmarket investments, we are reallocating a portion of our mid-market investments.

根據我們的經驗，讓這些開發人員了解 MongoDB 的好處可以推動我們平台的顯著增量採用。為了為這些高端投資提供資金，我們正在重新分配部分中端市場投資。

The mid-market remains an attractive opportunity for us, but we believe that prioritizing investment upmarket would deliver strong returns in the current environment. We also believe there are additional ways to serve the mid-market more efficiently through our self-serve channel and other scaled technology-enabled sales and customer service motions.

中端市場對我們來說仍然是一個有吸引力的機會，但我們相信，優先投資高端市場將在當前環境下帶來豐厚的回報。我們也相信，透過我們的自助服務管道和其他規模化的技術支援的銷售和客戶服務活動，還有其他方法可以更有效地服務中端市場。

Second, we are optimistic about the opportunity to accelerate legacy app modernization using AI and are investing more in this area. As you recall, we ran a few successful pilots earlier in this year, demonstrating that AI tooling combined with professional services and our relational migrator product, can significantly reduce the time, cost and risk of migrating legacy applications on to MongoDB. While it's early days, we have observed a more than 50% reduction in the cost to modernize.

其次，我們對利用人工智慧加速遺留應用程式現代化的機會持樂觀態度，並在這一領域加大投資。您還記得，我們​​在今年早些時候進行了一些成功的試點，證明人工智慧工具與專業服務和我們的關係遷移器產品相結合，可以顯著減少將遺留應用程式遷移到MongoDB 的時間、成本和風險。雖然現在還處於早期階段，但我們已經觀察到現代化成本降低了 50% 以上。

On the back of these strong early results, additional customer interest is exceeding our expectations. Large enterprises in every industry and geography are experiencing acute pain from their legacy infrastructure and are eager for more agile performance and cost-effective solutions. Not only our customers excited to engage with us, they also want to focus on some of the most important applications in their enterprise, further demonstrating the level of interest and size of the long-term opportunity.

在這些強勁的早期業績的支持下，客戶的興趣超出了我們的預期。每個行業和地區的大型企業都在經歷遺留基礎設施帶來的嚴重痛苦，並且渴望更靈活的性能和更具成本效益的解決方案。我們的客戶不僅興奮地與我們合作，他們還希望專注於其企業中的一些最重要的應用程序，進一步展示長期機會的興趣程度和規模。

As relational applications encompass a wide variety of database types, programming languages, versions, and other customer-specific variables, we expect modernization projects to continue to include meaningful services engagements in the short and medium term. Consequently, we are increasing our professional services delivery capabilities, both directly and through partners.

由於關係應用程式包含各種資料庫類型、程式語言、版本和其他特定於客戶的變量，因此我們預計現代化專案將在中短期內繼續包括有意義的服務活動。因此，我們正在直接或透過合作夥伴增強我們的專業服務交付能力。

In the long run, we expect to automate and simplify large parts of the modernization process. To that end, we are leveraging the learnings from early service engagements to develop new tools to accelerate future monetization efforts. Although it's early days and scaling our legacy app monetization capabilities will take time, we have increased conviction that this motion will significantly add to our growth in the long term.

從長遠來看，我們期望實現現代化過程的大部分自動化和簡化。為此，我們正在利用早期服務合作的經驗來開發新工具，以加速未來的貨幣化工作。儘管現在還處於早期階段，擴展我們的遺留應用程式獲利能力還需要時間，但我們更加相信，這項舉措將顯著促進我們的長期成長。

Third, we are investing to capitalize on our inherent technical advantages as a key component of the emerging AI tech stack. As a reminder, MongoDB is uniquely equipped to query rich and complex data structures typical of AI applications. The ability of a database to query rich and complex data structures is crucial because AI applications often rely on highly detailed, interrelated, and nuanced data to make accurate predictions and decisions.

第三，我們正在投資利用我們固有的技術優勢作為新興人工智慧技術堆疊的關鍵組成部分。提醒一下，MongoDB 具有獨特的能力來查詢人工智慧應用程式典型的豐富而複雜的資料結構。資料庫查詢豐富且複雜的資料結構的能力至關重要，因為人工智慧應用程式通常依賴高度詳細、相互關聯和細緻入微的資料來做出準確的預測和決策。

For example, a recommendation system doesn't just analyze a single customer's purchase but also considers their browsing history, peer group behavior, and product categories requiring a database that can query and ensuring these complex data structures. In addition, MongoDB's architecture unified source data, metadata, operational data, and vector data in all one platform, updating the need for multiple database systems and complex back-end architectures. This enables a more compelling developer experience than any other alternative.

例如，推薦系統不僅分析單一客戶的購買行為，還考慮他們的瀏覽歷史、同儕群體行為和產品類別，需要一個能夠查詢和確保這些複雜資料結構的資料庫。此外，MongoDB的架構將來源資料、元資料、操作資料和向量資料統一在一個平台上，更新了對多個資料庫系統和複雜後端架構的需求。與任何其他替代方案相比，這可以提供更引人注目的開發人員體驗。

From what we see in the AI market today, most customers are still in the experimental stage as they work to understand the effectiveness of the underlying tech stack and build early proof-of-concept applications. However, we are seeing an increasing number of AI apps in production.

從我們今天在人工智慧市場上看到的情況來看，大多數客戶仍處於實驗階段，因為他們致力於了解底層技術堆疊的有效性並建立早期的概念驗證應用程式。然而，我們看到越來越多的人工智慧應用程式投入生產。

Today, we have thousands of AI apps on our platform. What we don't yet see is many of these apps actually achieving meaningful product market fit and therefore, significant traction. In fact, as you take a step back and look at the entire universe of AI apps, a very small percentage of them have achieved the type of scale that we commonly see with enterprise-specific applications.

如今，我們的平台上有數千個人工智慧應用。我們還沒有看到的是，其中許多應用程式實際上實現了有意義的產品市場契合，因此具有巨大的吸引力。事實上，當你退後一步看看整個人工智慧應用程式時，你會發現其中只有很小一部分已經達到了我們在企業特定應用程式中常見的規模。

We do have some AI apps that are growing quickly, including one that is already a seven-figure workload that has grown 10x since the beginning of the year. Similar to prior platform shifts as the usefulness of AI tech improves and becomes more cost-effective, we will see the emergence of many more AI apps that do nail product market fit. But it's difficult to predict when that will happen more broadly.

我們確實有一些正在快速增長的人工智慧應用程序，其中一個工作負載已經達到七位數，自今年年初以來已經增長了 10 倍。與先前的平台轉變類似，隨著人工智慧技術的實用性提高並變得更具成本效益，我們將看到更多適合產品市場的人工智慧應用程式的出現。但很難預測這種情況何時會更廣泛地發生。

We remain confident that we will capture our fair share of these successful AI applications as we see that our platform is popular with developers building more sophisticated AI use cases. We continue investing in our product capabilities, including enterprise-grade Atlas Vector Search functionality to build on this momentum and even better position MongoDB to capture the AI opportunity.

我們仍然相信，我們將在這些成功的人工智慧應用程式中獲得公平的份額，因為我們看到我們的平台受到構建更複雜的人工智慧用例的開發人員的歡迎。我們繼續投資我們的產品功能，包括企業級 Atlas Vector Search 功能，以鞏固這一勢頭，甚至更好地定位 MongoDB 來抓住人工智慧機會。

In addition, as previously announced, we are bringing search and vector service to our community and EA offerings, leveraging our run-anywhere competitive advantage in the world of AI. Finally, we are expanding our MongoDB AI Applications program, or MAAP, which helps enterprise customers build and bring AI applications into production by providing them with reference architectures, integrations with leading tech providers, and coordinated services and support.

此外，正如先前宣布的，我們正在將搜尋和向量服務引入我們的社群和 EA 產品，利用我們在人工智慧領域的隨處運作的競爭優勢。最後，我們正在擴展 MongoDB AI 應用程式 (MAAP)，該計劃透過為企業客戶提供參考架構、與領先技術提供商的整合以及協調的服務和支持，幫助他們建立 AI 應用程式並將其投入生產。

Last week, we announced a new cohort of partners, including McKinsey, Confluent, CapGemini, and Unstructured as well as the collaboration with Meta to enable developers to build AI enriched applications on MongoDB using Llama.

上週，我們宣布了一批新的合作夥伴，包括 McKinsey、Confluence、CapGemini 和 Unstructed，以及與 Meta 的合作，讓開發人員能夠使用 Llama 在 MongoDB 上建立人工智慧豐富的應用程式。

Next, I'd like to provide you with a brief product update. At our local developer conference in London October, we announced the general availability of MongoDB 8.0, the fastest and most performant version of MongoDB ever. MongoDB 8.0 performs 20% to 60% better against common industry benchmarks compared to our prior version and is built to exceed our customers' most stringent security, resiliency, availability, and performance requirements.

接下來，我想為您提供一個簡短的產品更新。在 10 月於倫敦舉行的當地開發者大會上，我們宣布全面推出 MongoDB 8.0，這是有史以​​來最快、效能最強的 MongoDB 版本。與我們先前的版本相比，MongoDB 8.0 的效能比常見產業基準提高了 20% 到 60%，並且旨在超越客戶最嚴格的安全性、彈性、可用性和效能要求。

To best serve our customers, we regularly review and reprioritize investments in our product portfolio to ensure we're allocating our resources to products with the highest demand from our customers. And to do that, we also deprecate products that are not showing results we desire. Consequently, we made the decision to consolidate our Atlas serverless offerings with our smallest dedicated tiers to create Atlas Flex customers, a new offering with a simpler architecture that provides the elasticity features akin to service. We will begin migrating effective customers to the single, simple entry-level solution in Q4.

為了最好地服務我們的客戶，我們定期審查我們的產品組合投資並重新確定優先順序，以確保我們將資源分配給客戶需求最高的產品。為此，我們也會棄用那些未顯示出我們想要的結果的產品。因此，我們決定將 Atlas 無伺服器產品與最小的專用層進行整合，以創建 Atlas Flex 客戶，這是一種具有更簡單架構的新產品，可提供類似於服務的彈性功能。我們將在第四季開始將有效客戶遷移到單一、簡單的入門解決方案。

We also decided to deprecate Atlas Device Sync and other capabilities not widely adopted in order to focus our engineering resources on the core platform. While these reprioritization decisions are not made lightly, they allow us to deliver the most value to the largest number of customers, reinforcing our commitment to being the best modern database and helping us to grow faster.

我們也決定棄用 Atlas Device Sync 和其他未廣泛採用的功能，以便將我們的工程資源集中在核心平台上。雖然這些重新調整優先順序的決定並不是輕易做出的，但它們使我們能夠為最多數量的客戶提供最大的價值，強化我們成為最好的現代資料庫的承諾，並幫助我們更快地發展。

Now, I'd like to spend a few minutes reviewing the adoption trends of MongoDB across our customer base. Customers across industries and around the world are running mission-critical projects in MongoDB Atlas, leveraging the full power of our developer data platform, including Financial Times, Car Gurus and Victoria's Secret.

現在，我想花幾分鐘回顧 MongoDB 在我們客戶群中的採用趨勢。世界各地各行業的客戶正在 MongoDB Atlas 中運行關鍵任務項目，充分利用我們開發者資料平台的全部功能，包括《金融時報》、《汽車大師》和《維多利亞的秘密》。

As part of the digital transformation journey, global specialty retailer Victoria's Secret & Company migrate its e-commerce platform to MongoDB Atlas. As a fully managed platform, MongoDB Atlas allowed the company to simplify its architecture and improve performance, supporting the retail to provide a resilient, secure, and fast web and mobile e-commerce experience for their millions of customers around the world.

作為數位轉型之旅的一部分，全球專業零售商 Victoria's Secret & Company 將其電子商務平台遷移到 MongoDB Atlas。作為一個完全託管的平台，MongoDB Atlas 使該公司能夠簡化其架構並提高效能，支援零售業為其全球數百萬客戶提供彈性、安全、快速的 Web 和行動電子商務體驗。

Allianz Alpha Mod, Swiss Post, and Paylocity are turning to MongoDB to modernize applications. Paylocity, a leading provider of cloud-based payroll and human capital management software selected MongoDB to power proprietary application, aimed at fostering employee connections and engagement.

Allianz Alpha Mod、Swiss Post 和 Paylocity 正在轉向 MongoDB 來實現應用程式現代化。Paylocity 是基於雲端的薪資和人力資本管理軟體的領先提供商，選擇 MongoDB 來支援專有應用程序，旨在促進員工聯繫和參與。

When traffic increased and the original SQL-based solution was unable to keep up with the required performance metrics, Paylocity migrates to MongoDB Atlas to take advantage of the flexible schema architecture, performance, and scalability. MongoDB costs 5 times less than the previous SQL database solution, and the company's developers can now create an application with a minute, something that used to take weeks.

當流量增加且原始基於 SQL 的解決方案無法滿足所需的效能指標時，Paylocity 會遷移到 MongoDB Atlas 以利用靈活的架構架構、效能和可擴展性。MongoDB 的成本比以前的 SQL 資料庫解決方案低 5 倍，而且該公司的開發人員現在只需一分鐘即可創建一個應用程序，而這在過去需要幾週的時間。

Mature companies and startups alike are using MongoDB to help deliver the next wave of AI-powered application to the customers, including NerdWallet, Cisco and TealBook. TealBook, a supplier intelligence platform migrated from Postgres, PG vector, and Elasticsearch to MongoDB to eliminate technical debt and consolidate their tech stack. The company experienced workload isolation and scalability issues in PG vector and were concerned with the search index inconsistencies, which were all resolved with the migration to MongoDB.

成熟的公司和新創公司都在使用 MongoDB 來幫助向客戶交付下一波由人工智慧驅動的應用程序，包括 NerdWallet、Cisco 和 TealBook。TealBook 是一個供應商情報平台，它從 Postgres、PG Vector 和 Elasticsearch 遷移到 MongoDB，以消除技術債務並整合其技術堆疊。該公司在 PG 向量中遇到了工作負載隔離和可擴展性問題，並擔心搜尋索引不一致，這些問題在遷移到 MongoDB 後得到了解決。

With Atlas Vector Search and Dedicated Search Nodes, TealBook has realized improved cost efficiency and increased scalability for the supplier data platform, an application that uses GenAI to collect, verify and enrich supplier data across various sources.

借助 Atlas 向量搜尋和專用搜尋節點，TealBook 提高了供應商資料平台的成本效率和可擴展性，該應用程式使用 GenAI 來收集、驗證和豐富各種來源的供應商資料。

In summary, we had a healthy Q3 with both Atlas and EA exceeding expectations. We saw a strong new business quarter and we remain confident in our ability to become an increasing strategic provider in our large and growing market. Looking forward, we see a great opportunity to grow our adoption in the enterprise through new workloads, modernizing legacy applications and winning the next generation of AI powered application.

總而言之，我們的第三季表現良好，Atlas 和 EA 都超出了預期。我們看到了一個強勁的新業務季度，我們仍然對我們在龐大且不斷增長的市場中成為日益增長的策略提供者的能力充滿信心。展望未來，我們看到了透過新的工作負載、現代化遺留應用程式和贏得下一代人工智慧驅動的應用程式來提高我們在企業中的採用率的絕佳機會。

I would like to finish by providing an update on our senior leadership. First, as we announced early in the press release, after nearly 10 years, Michael Gordon has made the decision to leave MongoDB. Michael has been instrumental in MongoDB's success over the past decade, leading our successful IPO, helping us grow our revenue nearly fiftyfold and scaling -- and successfully scaling our business model to generate meaningful operating leverage. He has been a trusted advisor and business partner to the Board and me over the years and also has become a personal friend. Michael is excited to take a well-deserved break.

最後，我想介紹一下我們高階領導層的最新情況。首先，正如我們在新聞稿中早些時候宣布的那樣，在工作近 10 年後，Michael Gordon 做出了離開 MongoDB 的決定。Michael 在過去十年中對MongoDB 的成功發揮了重要作用，領導了我們成功的IPO，幫助我們將收入增長了近50 倍並進行了擴展，並成功擴展了我們的業務模式以產生有意義的運營槓桿。多年來，他一直是董事會和我值得信賴的顧問和業務合作夥伴，也成為了我的私人朋友。麥可很高興能好好休息一下。

We have commenced the search for Michael's replacement and will be evaluating both internal and external candidates. One of Michael's proudest accomplishments has been building a world class finance team under his leadership, and I'm confident that we will not miss a beat during this transition.

我們已經開始尋找邁克爾的繼任者，並將評估內部和外部候選人。麥可最值得驕傲的成就之一是在他的領導下建立了一支世界一流的財務團隊，我相信我們在這段過渡期間不會錯過任何一個節拍。

Michael will continue to serve as CFO through January 31 to help us finish the fiscal year and then will transition to an advisor to the company to ensure a seamless process. If you have not named Michael's successor by fiscal year end, Serge Tanjga, our SVP of Finance will serve as Interim CFO of beginning on February 1.

Michael 將繼續擔任財務長至 1 月 31 日，以協助我們完成本財年，然後將轉任公司顧問以確保流程順利進行。如果您在財年結束前尚未指定 Michael 的繼任者，我們的財務高級副總裁 Serge Tanjga 將從 2 月 1 日開始擔任臨時財務長。

Second, we are promoting Cedric Pech, currently our Chief Revenue Officer to the newly created role of President Worldwide Field Operations. In this new position, Cedric will oversee all our field-based customer facing and go to market enablement teams, including professional services.

其次，我們將現任首席營收長 Cedric Pech 提拔為新設立的全球現場營運總裁。在這個新職位上，塞德里克將監督我們所有面向​​現場的客戶並進入市場支援團隊，包括專業服務。

We believe this org structure will best enable us to execute on some of the key strategic initiatives I discussed earlier, in particular, our increased focus on upmarket and the app monetization opportunity. I would like to congratulate Cedric on this well-deserved promotion. With that, let me turn the call over to Michael.

我們相信，這種組織結構將使我們能夠最好地執行我之前討論的一些關鍵策略舉措，特別是我們對高端市場和應用程式貨幣化機會的更多關注。我謹祝賀塞德里克當之無愧的晉升。現在，讓我把電話轉給麥可。

Thanks, Dev, and thanks for the kind words and our incredible partnership over the past decade. The past 10 years have been the most rewarding in my professional career, and I'm extremely proud of what we've achieved together and of course, with the whole MongoDB team. With as much success as we had, I still believe that MongoDB is in the early stages of realizing its full potential as it continues to take share in one of the largest markets in software.

謝謝 Dev，感謝您的客氣話以及我們在過去十年中令人難以置信的合作夥伴關係。過去的 10 年是我職業生涯中最有價值的十年，我對我們共同取得的成就感到非常自豪，當然還有整個 MongoDB 團隊。儘管我們取得了巨大的成功，但我仍然相信 MongoDB 正處於充分發揮其潛力的早期階段，因為它繼續在最大的軟體市場之一中佔據份額。

Now, turning to results for the quarter. I'll begin with a detailed review of our third-quarter results and then finish with our outlook for the fourth quarter and full fiscal year 2025. First, I'll start with our third-quarter results. Total revenue in the quarter was $529.4 million, up 22% year over year and above the high end of our guidance.

現在，轉向本季的業績。我將首先詳細回顧我們的第三季業績，然後展望第四季和 2025 財年。首先，我將從我們的第三季業績開始。本季總營收為 5.294 億美元，年增 22%，高於我們指引的上限。

Shifting to our product mix. Atlas grew 26% in the quarter compared to the previous year and now represent 68% of total revenue compared to 66% in the third quarter of fiscal 2024 and 71% last quarter. We recognized Atlas revenue primarily based on customer consumption of our platform and that consumption is closely tied to end user activity of their applications.

轉向我們的產品組合。Atlas 本季較上年成長 26%，目前佔總營收的 68%，而 2024 財年第三季為 66%，上季為 71%。我們主要根據我們平台的客戶消費來確認 Atlas 收入，而該消費與其應用程式的最終用戶活動密切相關。

Let me provide some context on Atlas consumption in the quarter. In Q3, consumption was slightly ahead of our expectations. This year's Q3 seasonal improvement was more muted than in years past as expected. On a year-over-year basis, consumption growth remains below that of the prior year period.

讓我提供一些有關本季度 Atlas 消費的背景資訊。第三季度，消費略超我們預期。正如預期的那樣，今年第三季的季節性改善比往年更加溫和。與去年同期相比，消費成長率仍低於去年同期。

Turning to non-Atlas revenue. Non-Atlas came in significantly ahead of our expectations. As Dev mentioned, EA new business was strong, and we continue to have successfully incremental workloads into our existing customer base.

轉向非 Atlas 收入。非 Atlas 的表現明顯超出了我們的預期。正如 Dev 所提到的，EA 新業務很強勁，我們繼續成功地將工作負載增加到現有的客戶群。

In addition, our Q3 non-Atlas revenue benefited from a few large multiyear deals. As you know, due to ASC 606, we recognized the entire term license component of a multiyear contract at the start of that contract. Compared to Q3 of last year, the multiyear license component of non-Atlas revenues was over $15 million higher.

此外，我們第三季的非 Atlas 收入受益於一些大型的多年期交易。如您所知，根據 ASC 606，我們在多年合約開始時就認可了該合約的整個期限許可部分。與去年第三季相比，非 Atlas 收入的多年許可部分增加了 1500 萬美元以上。

Turning to customer growth. During the third quarter, we grew our customer base by approximately 1,900 customers sequentially, bringing our total customer count to over 52,600 which is up from over 46,400 in the year ago period. Of our total customer count, over 7,400 are direct sales customers, which compares to over 6,900 in the year ago period.

轉向客戶成長。第三季度，我們的客戶群連續增加了約 1,900 名客戶，使我們的客戶總數超過 52,600 名，高於去年同期的 46,400 名。在我們的客戶總數中，有 7,400 多名直銷客戶，而去年同期為 6,900 多名。

The growth in our total customer count is being driven primarily by Atlas which had over 51,100 customers at the end of the quarter compared to over 44,900 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 their first Atlas work.

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 51,100 名客戶，而去年同期為 44,900 多名。重要的是要記住，Atlas 客戶數量的成長反映了 MongoDB 的新客戶以及添加第一個 Atlas 工作的現有 EA 客戶。

Continuing on, in Q3, our net ARR expansion rate was approximately 120%. We ended the quarter with 2,314 customers with at least $100,000 in ARR and annualized MRR, up from 1,972 in the year ago period.

接下來，在第三季度，我們的淨 ARR 擴張率約為 120%。本季末，我們有 2,314 名客戶的 ARR 和年化 MRR 至少為 10 萬美元，高於去年同期的 1,972 名。

Moving down the income statement. I'll be discussing our results on a non-GAAP basis unless otherwise noted. Gross profit in the third quarter was $405.7 million, representing a gross margin of 77%, which is flat versus the year ago period.

將損益表向下移動。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結果。第三季毛利為4.057億美元，毛利率為77%，與去年同期持平。

Our income from operations was $101.5 million or a 19% operating margin for the third quarter, compared to an 18% operating margin in the year ago period. The primary reason for a more favorable operating income results versus guidance is our revenue outperformance, including the very high-margin multiyear license revenue benefit.

第三季我們的營運收入為 1.015 億美元，營運利潤率為 19%，而去年同期營運利潤率為 18%。與指導相比，營業收入結果更有利的主要原因是我們的收入表現出色，包括利潤率非常高的多年授權收入收益。

Net income in the third quarter was $98.1 million or $1.16 per share based on 84.2 million diluted weighted average shares outstanding. This compares to a net income of $79.1 million or $0.96 per share on 83.7 million diluted weighted average shares outstanding in the year ago period.

第三季淨利為 9,810 萬美元，即每股 1.16 美元，基於 8,420 萬股稀釋加權平均流通股計算。相較之下，去年同期8,370萬股稀釋加權平均流通股的淨利為7,910萬美元，即每股0.96美元。

Turning to the balance sheet and cash flow, we ended the third quarter with $2.3 billion in cash, cash equivalents, short-term investments, and restricted cash. Operating cash flow in the third quarter was $37.4 million. After taking into consideration approximately $2.9 million in capital expenditures and principal repayments of finance lease liabilities, free cash flow was $34.6 million in the quarter. This compares to free cash flow of $35 million in the year ago period.

談到資產負債表和現金流，第三季末我們的現金、現金等價物、短期投資和限制性現金為 23 億美元。第三季營運現金流為 3,740 萬美元。考慮到約 290 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 3,460 萬美元。相比之下，去年同期的自由現金流為 3,500 萬美元。

In Q3, we did not incur capital expenditures to purchase IPV4 addresses as we previously expected. But we did start making those purchases in November and still expect a total outlay of $20 million to $25 million this fiscal year, as we've previously communicated.

第三季度，我們沒有像我們之前預期的那樣產生購買 IPV4 位址的資本支出。但我們確實在 11 月開始進行這些採購，並且正如我們之前所傳達的那樣，預計本財年的總支出為 2000 萬至 2500 萬美元。

I'd now like to turn to our outlook for the fourth quarter and full fiscal year 2025. For the fourth quarter, we expect revenue to be in the range of $515 million to $519 million. We expect non-GAAP income from operations to be in the range of $55 million to $58 million, and non-GAAP net income per share to be in the range of $0.62 to $0.65 based on 84.9 million estimated diluted weighted average shares outstanding.

我現在想談談我們對第四季和 2025 財年的展望。我們預計第四季的營收將在 5.15 億美元至 5.19 億美元之間。我們預計非 GAAP 營運收入將在 5,500 萬美元至 5,800 萬美元之間，非 GAAP 每股淨利潤將在 0.62 美元至 0.65 美元之間（基於 8,490 萬股估計稀釋加權平均流通股）。

For the full fiscal year 2025, we expect revenue to be in the range of $1.973 billion to $1.977 billion, non-GAAP income from operations to be in the range of $242 million to $245 million and non-GAAP net income per share to be in the range of $3.01 to $3.03 based on 84 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 2025 include a non-GAAP tax provision of approximately 20%.

對於 2025 年整個財年，我們預計收入將在 19.73 億美元至 19.77 億美元之間，非 GAAP 營運收入將在 2.42 億美元至 2.45 億美元之間，非 GAAP 每股淨利潤將在範圍為3.01 至3.03 美元，基於8400 萬股估計稀釋加權平均已發行股票。請注意，2025 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 more context around our updated guidance. First, in terms of Atlas consumption, we expect to see a typical seasonal slowdown in Q4 driven by underlying application usage moderating during the holiday season. Second, since Atlas consumption remained lower on a year-over-year basis in Q3, we expect to see continued deceleration of Atlas year-over-year growth in Q4.

我現在將提供有關我們更新的指南的更多背景資訊。首先，就 Atlas 消費而言，我們預計第四季度將出現典型的季節性放緩，原因是假期期間基礎應用程式使用量放緩。其次，由於Atlas第三季的消費量比去年同期仍然較低，我們預期Atlas第四季的年增率將持續放緩。

Third, we expect to see a sequential decline in non-Atlas revenue in Q4, which is contrary to our normal pattern. The reason for this is that we experienced a significant additional benefit from multiyear deals in Q3 and which we do not expect to recur in Q4. In addition, I want to provide some incremental color on some of our recent product -- how some of our recent product and go-to-market changes will impact the growth of our reported customer count going forward.

第三，我們預計第四季非 Atlas 收入將連續下降，這與我們的正常模式相反。原因是我們在第三季從多年期交易中獲得了顯著的額外收益，但我們預計第四季不會再發生這種情況。此外，我想為我們最近的一些產品提供一些增量資訊——我們最近的一些產品和上市變化將如何影響我們報告的客戶數量的未來成長。

First, as Dev explained, we are reallocating a portion of our go-to-market resources from the mid-market to the enterprise channel. As a result, we expect to see significantly fewer mid-market direct sales customer net additions and, as a result, slower direct sales customer growth going forward. We believe this reallocation of investment dollars will drive higher revenue growth over time, so it's a trade-off that makes sense.

首先，如 Dev 所解釋的，我們正在將部分上市資源從中端市場重新分配到企業通路。因此，我們預期中階市場直銷客戶淨增量將大幅減少，導致未來直銷客戶成長放緩。我們相信，隨著時間的推移，這種投資資金的重新分配將推動更高的收入成長，因此這是一個有意義的權衡。

Second, as we introduce Atlas Flex clusters in Q4 and automatically migrate customers in Q1, we expect to see a onetime negative impact to our customer count since we have approximately 4,000 serverless customers who are very low spending, and we do not expect them to transition over to Flex. These customers have a negligible impact on our revenue but will impact our reported customer count.

其次，當我們在第四季度引入Atlas Flex 叢集並在第一季自動遷移客戶時，我們預計會對我們的客戶數量產生一次性負面影響，因為我們有大約4,000 個無伺服器客戶，他們的支出非常低，而且我們預計他們不會遷移交給 Flex。這些客戶對我們的收入影響可以忽略不計，但會影響我們報告的客戶數量。

To summarize, we're pleased with our third quarter results and especially our ability to win new business. We have a small share, one of the largest and fastest-growing markets in all of software, with a number of secular tailwinds, including AI at our back. We'll continue investing judiciously and focusing on our execution to capture this long-term opportunity. With that, we'd like to open it up to questions. Operator?

總而言之，我們對第三季的業績，特別是我們贏得新業務的能力感到滿意。我們的份額很小，是所有軟體中最大、成長最快的市場之一，有許多長期的推動因素，包括人工智慧在我們的支持下。我們將繼續明智地投資並專注於我們的執行力，以抓住這一長期機會。至此，我們願意接受提問。操作員？

(Operator Instructions) Sanjit Singh, Morgan Stanley.

（操作員指令）Sanjit Singh，摩根士丹利。

Thank you for taking the questions and congrats, Michael, on a solid career. You had an absolutely fantastic run at MongoDB. I'm excited to see what you do next or excited if you just take a breather. So congrats, Michael. I guess, to take the question to start off with the questions.

感謝您提出問題，並祝賀邁克爾，職業生涯發展順利。您在 MongoDB 的表現非常出色。我很高興看到你接下來會做什麼，或者如果你休息一下也很興奮。恭喜你，麥可。我想，要從問題開始。

When we look at what Atlas has been doing in the past two quarters -- correct me if I'm wrong, but I think consumption is coming in at least modestly ahead of your expectations. Relative to what we've seen at the beginning of the year, what sort of -- is it a function of sales execution? Is it a function of the end user activity sort of improving? What's driving at least the improvement in Atlas consumption the past two quarters?

當我們看看阿特拉斯在過去兩個季度所做的事情時——如果我錯了，請糾正我，但我認為消費至少略微超出了你的預期。相對於我們在年初看到的情況，它是銷售執行的函數嗎？這是最終用戶活動有改善的結果嗎？是什麼至少推動了過去兩個季度 Atlas 消費的改善？

Yeah. So a few different things. So I think if you look at our outlook at the beginning of the year, we had indicated that we thought we would see stable Atlas growth from a consumption standpoint. What we've seen and what we've talked about is we've actually seen a lower year-over-year growth based off of the underlying consumption. And so -- and that's incorporated into our Q4 guide.

是的。所以有一些不同的事情。因此，我認為，如果你看看我們年初的前景，我們曾表示，從消費的角度來看，我們將看到 Atlas 的穩定成長。我們所看到和談論的是，我們實際上看到基於基礎消費的同比增長較低。所以——這已納入我們的第四季指南。

We have seen the Q3 and Q4 -- Q2 and Q3, excuse me, be better than our expectations, but it's still down on a year-over-year basis. And so I want to make sure that we're not sort of confusing the comparative set of year-over-year versus relative to our expectations. And the core of it, Sanjit, to your question, is really the underlying usage of the applications.

我們已經看到第三季和第四季——對不起，第二季和第三季比我們的預期要好，但比去年同期仍然下降。因此，我想確保我們不會混淆同比與相對於我們預期的比較。Sanjit，對於你的問題，它的核心實際上是應用程式的底層用法。

Yeah, that makes total sense. And then Dev, I have to ask you the AI agent question. In terms of an AI agent needing more context, it has going to have a set of tools to take its actions. What does it mean for MongoDB as an operational data store as customers start to roll out more agentic applications?

是的，這完全有道理。然後 Dev，我必須問你人工智慧代理的問題。就需要更多上下文的人工智慧代理而言，它必須擁有一套工具來採取行動。隨著客戶開始推出更多代理應用程序，這對於 MongoDB 作為營運資料儲存意味著什麼？

Yeah. So just to talk about agents, I think when you think about agents, there's jobs -- there's a job, this project and then this task. Right now, the agents that are being rolled out are really focused on task, like, say, something from Sierra or some other companies that are rolling out agents. But you're right, what they deem to do is to deal with being able to create a rich and complex data structure.

是的。就談一下代理，我認為當你想到代理時，有工作——有工作、這個項目，然後是這個任務。目前，正在推出的代理商確實專注於任務，例如 Sierra 或其他一些正在推出代理商的公司的產品。但你是對的，他們認為要做的是能夠創造豐富而複雜的資料結構。

Now why is this important for in AI is that AI models don't just look at isolated data points, but they need to understand relationships, hierarchies and patterns within the data. They need to be able to essentially get real-time insights. For example, if you have a chat bot where someone's clearing customers kind of trying to get some update on the order they placed 5 minutes ago because they may have not gotten any confirmation, your chatbot needs to be able to deal with real-time information.

為什麼這對人工智慧很重要，因為人工智慧模型不僅查看孤立的資料點，還需要理解資料內的關係、層次結構和模式。他們需要能夠本質上獲得即時洞察。例如，如果您有一個聊天機器人，其中某人的清算客戶試圖獲取他們 5 分鐘前下的訂單的一些更新，因為他們可能沒有得到任何確認，那麼您的聊天機器人需要能夠處理即時資訊。

You need to be able to deal with basically handling very advanced use cases, understanding like -- do things like fraud detection, to understand behaviors on supply chain, you need to understand intricate data relationships. All these things are consistent with MongoDB offers. And so we believe that at the end of the day, we are well positioned to handle this.

您需要能夠處理非常高級的用例，理解諸如詐欺檢測之類的事情，要了解供應鏈上的行為，您需要了解複雜的資料關係。所有這些都與 MongoDB 提供的內容一致。因此，我們相信最終我們有能力處理這個問題。

And the other thing that I would say is that we've embedded in a very natural way, search and vector search. So we're just not an OLTP database. We do tech search and vector search, and that's all one experience and no other platform offers that, and we think we have a real advantage.

我要說的另一件事是，我們以一種非常自然的方式嵌入了搜尋和向量搜尋。所以我們不是 OLTP 資料庫。我們進行技術搜尋和向量搜索，這只是一種體驗，沒有其他平台提供這種體驗，我們認為我們擁有真正的優勢。

And so we're integrated with the leading AI frameworks and platforms. We have enterprise-grade security and compliance, and customers can run us anywhere, either on 118 cloud regions or on-prem. And that again is a huge differentiator for us.

因此，我們與領先的人工智慧框架和平台整合。我們擁有企業級安全性和合規性，客戶可以在任何地方運行我們，無論是在 118 個雲端區域還是本地。這對我們來說又是一個巨大的差異化因素。

Awesome. I appreciate the thought. Thanks

驚人的。我很欣賞這個想法。謝謝

Thanks, Sanjit.

謝謝，桑吉特。

Tyler Radke, Citi.

泰勒·拉德克，花旗銀行。

Alright, thank you very much for taking the question and Michael, all the best, and congratulations on 10 years. Going back to the sales execution, I mean one of the things that you talked about earlier this year was some challenges just in terms of the recently acquired workloads ramping. And I think a lot of those were from the past fiscal year.

好的，非常感謝您提出問題，邁克爾，祝您一切順利，並祝賀您 10 週年。回到銷售執行，我的意思是您今年早些時候談到的一件事是最近獲得的工作負載增加方面的一些挑戰。我認為其中很多來自上一財年。

So curious how the quality of workload acquisition has trended this year? And as you think about the ramp in consumption, potential into next year, how does that sort of look versus this time a year ago?

很好奇今年工作負載獲取的品質趨勢如何？當你考慮明年的消費成長和潛力時，與一年前的這個時候相比，情況如何？

Yeah, maybe I'll just talk about what we're doing and the changes we made, and then Michael can talk a little bit about the consumption trends. So we did make some changes at the beginning of the year, and we really wanted to focus on both the volume and the quality of the workloads. And there were some slight adjustments that we made. We think those changes are having a reasonable positive impact.

是的，也許我只會談談我們正在做的事情和我們所做的改變，然後麥可可以談談消費趨勢。因此，我們確實在年初做出了一些改變，我們確實希望同時專注於工作負載的數量和品質。我們做了一些細微的調整。我們認為這些變化正在產生合理的正面影響。

Again, it's too early to declare victory because these workloads usually start small and grow over time, but we're really pleased with the results we're seeing so far. But again, it's early days. And obviously, we'll know about the fiscal '25 workloads as we go into fiscal '26, but so far, so good. Michael, in consumption?

同樣，現在宣布勝利還為時過早，因為這些工作負載通常一開始很小，然後會隨著時間的推移而增加，但我們對迄今為止看到的結果感到非常滿意。但話又說回來，現在還太早。顯然，當我們進入 26 財年時，我們就會知道 25 財年的工作負載，但到目前為止，情況還不錯。邁克爾，在消費嗎？

Yeah. Just a couple of things, and thanks, Tyler. The fiscal 2024 cohorts that we called out earlier, that slower growth does continue, they've been in line with our revised expectations. We made some changes that we talked about earlier in the year that should affect the fiscal 2025 cohorts, but it's just too early to tell.

是的。只是幾件事，謝謝泰勒。我們先前提到的 2024 財年群體，成長放緩確實會持續，這符合我們修改後的預期。我們做了一些我們在今年早些時候討論過的改變，這些改變應該會影響 2025 財年的群體，但現在下結論還為時過早。

On those, we need a few more quarters of data before you can really see if we're how we're seeing those behave differently. I will say we've talked about the new business environment and our success in new business. We have been pleased with that, but that just shows kind of the initial piece and we need to see how they grow and how those cohorts evolve.

在這些方面，我們還需要幾個季度的數據，然後才能真正了解我們是否看到這些行為有所不同。我想說的是，我們已經討論了新的商業環境以及我們在新業務方面的成功。我們對此感到滿意，但這只是展示了最初的作品，我們需要看看他們如何成長以及這些群體如何發展。

Great. And follow-up on the EA side. You talked about the outsized strength in non-Atlas business this quarter. Maybe if you could unpack like the relative upside that was driven by simply duration versus new business? I know you called out the duration impact year-over-year.

偉大的。以及EA方面的跟進。您談到了本季度非 Atlas 業務的強勁勢頭。也許您可以分析一下由簡單的持續時間與新業務驅動的相對優勢？我知道您指出了同比持續時間的影響。

But do you feel like this was sort of a one-off? Or do you feel like maybe some of your bigger customers are indexing more towards EA? And how does that impact the way you think about the product and introducing things like vector search and stream processing onto the on-prem product?

但你是否覺得這只是一次性的？或者您覺得您的一些大客戶對 EA 的索引更多？這如何影響您對產品的思考方式以及將向量搜尋和串流處理等內容引入本地產品的方式？

Yeah, thank you. So overall, we continue to find the EA product resonate with customers. It's an important part of the run anywhere strategy, and we've continued to see successful there and people wanting to increase their investment in MongoDB.

是的，謝謝。總的來說，我們繼續發現 EA 產品能夠引起客戶的共鳴。這是隨處運行策略的重要組成部分，我們不斷看到該領域的成功以及人們希望增加對 MongoDB 的投資。

There's always been a multiyear component, and we continue to see that. We talked about that at the beginning of the year as to how fiscal '24 had an abnormally high amount of multiyear benefit. And therefore, we were anticipating that being a headwind, and we quantified that in roughly the $40 million range.

一直有一個多年的組成部分，我們繼續看到這一點。我們在今年年初討論過 24 財年如何獲得異常高額的多年期福利。因此，我們預計這將是一個不利因素，我們將其量化為約 4000 萬美元的範圍。

What we talked about on this call earlier is we saw from a few large accounts, a surprising amount of multiyear that positively benefited Q3 at a little more than $15 million in revenue compared to what we saw Q3 a year ago. So not as much of a headwind as we had been expecting.

我們之前在這次電話會議上談到的是，我們從一些大客戶中看到，與一年前第三季相比，第三季的收入為第三季帶來了積極的收益，數量令人驚訝，其收入略高於1500 萬美元。因此，逆風並不像我們預期的那麼大。

Obviously, with the 606 dynamics, some of these things, especially for a large deal, can be kind of media and chunky and lumpy, which is why we try and call it out and sort of help people understand. But there's a pretty healthy kind of baseline flow, not just the EA, but also multiyear. And when we see spikes, we just try and call it out for you.

顯然，在 606 的動態下，其中一些東西，特別是對於大宗交易來說，可能是一種媒體，並且是厚重的、塊狀的，這就是為什麼我們嘗試將其大聲疾呼並幫助人們理解。但有一個相當健康的基線流程，不僅是 EA，而且還有多年。當我們看到峰值時，我們只是嘗試為您指出。

Yeah. I just want to add, Tyler, that we are investing in our what we call our EA business. First, we're starting by investing with Search and Vector Search and a community product. That does a couple of things for us. One, whenever anyone starts with MongoDB with the open-source product, they need get all the benefits of that complete and highly integrated platform.

是的。Tyler，我只想補充一點，我們正在投資我們所謂的 EA 業務。首先，我們首先投資搜尋和向量搜尋以及社群產品。這對我們來說有幾件事。第一，每當任何人開始使用 MongoDB 這個開源產品時，他們都需要獲得這個完整且高度整合的平台的所有好處。

Two, those capabilities will then migrate to EA. So EA for us is an investment strategy. We definitely see lots of large customers who are very, very committed to running workloads on-prem. We even see some customers want who are on to run AI workloads on-prem. So the optionality they get by using MongoDB to not just be on-prem in the cloud, but also cross cloud is a very compelling one.

第二，這些功能隨後將遷移到 EA。所以EA對我們來說是一種投資策略。我們確實看到許多大客戶非常非常致力於在本地運行工作負載。我們甚至看到一些客戶希望在本地運行人工智慧工作負載。因此，透過使用 MongoDB 不僅可以在雲端中本地部署，還可以跨雲，他們獲得的選擇性是非常引人注目的。

Brad Reback, Stifel.

布拉德雷巴克、斯蒂菲爾。

Great. Michael, best of luck. It's been a great run. Dev, you started the call talking about a bunch of investments, which are great given the growth of the business. And obviously, you talked about reallocating some expenses. But net-net, should we think about this incremental investment phase next year as gating margin upside?

偉大的。邁克爾，祝你好運。這是一次很棒的跑步。開發人員，您在電話會議開始時談到了一系列投資，考慮到業務的成長，這些投資非常好。顯然，您談到了重新分配一些費用。但是，我們是否應該將明年的增量投資階段視為限制利潤率上升的因素？

I think that's something that we obviously are not ready to talk about next year just now, but I would say that the reason we're looking to invest and just to summarize again, going up market on legacy app monetization, where we see very large workloads potentially at play and being the ideal database for GenAI apps, which is the future as important investments to drive long-term growth. And we're quite energized by those investments, and that's something that we have high conviction on.

我認為這顯然是我們現在還沒有準備好在明年討論的事情，但我想說的是，我們尋求投資的原因是再次總結一下，進入遺留應用程序貨幣化市場，我們看到了非常大的市場工作負載可能發揮作用，並成為GenAI 應用程式的理想資料庫，這是未來推動長期成長的重要投資。這些投資讓我們充滿活力，我們對此充滿信心。

That's great. And then on the MAAP program, are most of those workloads going to wind up in Atlas? Or will that be a healthy combination of EA and Atlas?

那太棒了。然後，在 MAAP 計劃中，大部分工作負載是否會在 Atlas 中結束？或者這會是 EA 和 Atlas 的健康組合嗎？

I think it's, again, early days. I would say -- I would probably say more on the side of Atlas than EA in the early days. I think once we introduce Search and Vector Search into the EA product, you'll see more of that on-prem.

我認為現在還為時過早。我想說的是——在早期，我可能會更多地支持 Atlas，而不是 EA。我認為，一旦我們將搜尋和向量搜尋引入 EA 產品中，您就會在本地看到更多此類功能。

Obviously, people can use MongoDB for AI workloads using other technologies as well in conjunction with MongoDB for on-prem AI use cases. But I would say you're probably going to see that happen first in Atlas.

顯然，人們可以使用其他技術將 MongoDB 用於 AI 工作負載，也可以與 MongoDB 結合用於本機 AI 用例。但我想說你可能會首先在 Atlas 中看到這種情況發生。

Great. Thanks very much.

偉大的。非常感謝。

Jason Ader, William Blair.

傑森·阿德，威廉·布萊爾。

Yeah. Thank you. I'm not going to belabor congratulating Michael, but it has been fun working with you and best of luck. The question I had is on the strength in EA. Do you think, Dev, it represents a comment on how enterprises might be rethinking or reassessing the kind of on-prem versus cloud workload placement decision?

是的。謝謝。我不會過多地祝賀邁克爾，但與你一起工作很有趣，祝你好運。我的問題是關於 EA 的實力。Dev，您認為這是否代表了企業可能如何重新思考或重新評估本地與雲端工作負載放置決策的評論？

Well, when I think about large enterprises, I think large enterprises have meaningful workloads that are still running on-prem. I think the belief that everything would go to the cloud was probably something that was really popular in the good old days of [ZURP]. But I think now as customers assess their investments that they already have in place, they're being much more judicious about where they run those workloads and if they think they can leverage there's existing investments in their own infrastructure then they're going to do so.

好吧，當我想到大型企業時，我認為大型企業擁有仍在本地運行的有意義的工作負載。我認為在過去的美好時光裡，一切都將轉移到雲端的信念可能非常流行。[ZURP]。但我認為，現在當客戶評估他們已經到位的投資時，他們對於在哪裡運行這些工作負載會更加明智，如果他們認為可以利用自己基礎設施中的現有投資，那麼他們就會這樣做。

Also, for a bunch of other reasons, like regulatory reasons, some customers are quite -- not moving as aggressively to the cloud, we see that particularly in Europe, where we see a lot of the European banks still running majority of the workloads on-prem. So it also varies by region where conversely, in Asia, we're seeing people much move much more aggressively to the cloud.

此外，由於許多其他原因，例如監管原因，一些客戶並沒有積極地轉向雲，我們看到這一點尤其是在歐洲，我們看到許多歐洲銀行仍然在雲端上運行大部分工作負載-prem。因此，它也因地區而異，相反，在亞洲，我們看到人們更加積極地轉向雲端。

So I think it really depends on industry, on geography, and on the personal dynamics of what's happening in that particular account. I mean we see some large US banks are also very committed to running things on-prem. So it really varies, and that's why we feel really good about our run anywhere strategy because it gives customer optionality they can build something and run on-prem. And if and when they choose to move to the cloud, it's very easy to do so with MongoDB.

所以我認為這實際上取決於行業、地理位置以及特定帳戶中發生的情況的個人動態。我的意思是，我們看到一些大型美國銀行也非常致力於在當地經營業務。所以它確實有所不同，這就是為什麼我們對我們的隨處運行策略感到非常滿意，因為它為客戶提供了選擇權，他們可以建立一些東西並在本地運行。如果他們選擇遷移到雲，使用 MongoDB 可以非常輕鬆地做到這一點。

All right. And then just as a follow-up also on the investments you're making in strategic sales in enterprise. Could you just get a little more specific on what those investments might be? Is it hiring a lot of new salespeople? Is it working more with SIs, investing more in SIs? Any additional detail would be helpful. Thanks.

好的。然後，作為您在企業策略銷售方面所做投資的後續行動。您能否更具體地說明這些投資可能是什麼？是否正在招募大量新銷售人員？是否更多地與系統整合商合作，對系統整合商進行更多投資？任何額外的細節都會有幫助。謝謝。

Yeah. So just for everyone's benefit, we've identified a number of accounts, which we call strategic accounts, which we think that have high upside for us. We've seen a number of accounts that grow very quickly when we deploy the right mix of resources. Now they're all not necessarily quota-carrying resources, there could be additional technical sales resources, additional PS resources, additional customer service resources to better service and support those accounts.

是的。因此，為了每個人的利益，我們確定了一些帳戶，我們稱之為策略帳戶，我們認為這些帳戶對我們有很大的好處。我們發現，當我們部署正確的資源組合時，許多帳戶成長得非常快。現在它們不一定都是配額資源，可能會有額外的技術銷售資源、額外的 PS 資源、額外的客戶服務資源，以便更好地服務和支援這些客戶。

We even do things like run education sessions for developers of the accounts. They're called either hackathons or like what we call developer days or even design reviews where we'll meet with the development teams that are looking to build an application, help them think about how they would potentially use MongoDB to build that particular app.

我們甚至會為帳戶開發人員舉辦教育課程等活動。它們被稱為黑客馬拉松，或者像我們所說的開發者日，甚至是設計評審，我們將與希望建立應用程式的開發團隊會面，幫助他們思考如何使用 MongoDB 來建立特定的應用程式。

And what we find is that because many of these developers that experience with MongoDB is quite limited, the more we can engage with them, the more we can educate them, and the more we can show them how simple and easy it is. Like, for example, most customers today think like they have to use an OLTP database search database, maybe a vector database and then like a cashing database and all that is integrated in MongoDB.

我們發現，由於許多開發人員使用 MongoDB 的經驗非常有限，因此我們與他們接觸的越多，我們就越能教育他們，我們就越能向他們展示 MongoDB 是多麼簡單和容易。例如，如今大多數客戶認為他們必須使用 OLTP 資料庫搜尋資料庫，也許是向量資料庫，然後是現金資料庫，所有這些都整合在 MongoDB 中。

So all of a sudden, customers can say, wow, I can simplify my life, simplify my back-end infrastructure, build this app far more quickly and it will be much more easier to manage long term if I do everything on MongoDB. And it's really a function of just educating them on the power of MongoDB that really opens up a lot of opportunities for us.

所以突然之間，客戶會說，哇，我可以簡化我的生活，簡化我的後端基礎設施，更快地構建這個應用程序，如果我在 MongoDB 上做所有事情，長期管理會更容易。這實際上是讓他們了解 MongoDB 的強大功能，這確實為我們帶來了許多機會。

So that's why we're doubling down, and the mix of resources is really predicated on the accounts. But it's not just quota counting resources, it's the whole suite of resources that we bring to the table.

這就是我們加倍努力的原因，資源的組合實際上取決於帳戶。但這不僅僅是配額運算資源，而是我們提供的整套資源。

Thank you.

謝謝。

Andrew Nowinski, Wells Fargo.

安德魯諾溫斯基，富國銀行。

Okay. Good afternoon. Thank you very much for taking the question and congrats on a nice quarter. You gave an example of a customer that migrated off Postgres. And I think you said they had issues with their PG vector function.

好的。午安.非常感謝您提出問題，並祝賀您度過了一個愉快的季度。您提供了一個從 Postgres 遷移的客戶範例。我想你說過他們的 PG 向量函數有問題。

I was wondering how long is that customer using Postgres before they decided to make a change to Mongo, meaning was this some sort of like a rebound type customer where they chose or PG or Postgres and it didn't work? And then how frequently are you seeing this type of transition?

我想知道該客戶在決定更改為 Mongo 之前使用 Postgres 多久了，這意味著這有點像反彈型客戶，他們選擇了 PG 或 Postgres，但不起作用？那麼您多久會看到這種類型的轉變？

Yeah. So I can't give you the specifics on how long they were using Postgres, but this is not -- this is a trend that we're seeing in our business. You have to remember, Postgres is a 40-year-old technology. And they've been the beneficiary of people lifting and shifting from other types of relational databases, Oracle, SQL Server, MySQL, et cetera. And they're an open-source database.

是的。因此，我無法向您提供他們使用 Postgres 多長時間的具體信息，但這不是——這是我們在業務中看到的趨勢。你必須記住，Postgres 是一項已有 40 年歷史的技術。它們是人們從其他類型的關聯式資料庫（Oracle、SQL Server、MySQL 等）中遷移出來的受益者。它們是一個開源資料庫。

But as part -- because they're an open source and relational database, they have the same inherent challenges, all relational databases do. They're quite inflexible. So once you build the scheme, it's very hard to change the schema. It's hard to scale and hard to distribute data. And if you have large data volumes, you have to do were things like, for example, resort to off-road storage for large data objects, which creates performance bottlenecks.

但作為一部分，因為它們是開源的關聯式資料庫，所以它們面臨著所有關聯式資料庫所面臨的相同的固有挑戰。他們非常不靈活。因此，一旦建構了方案，就很難更改方案。難以擴展且難以分發資料。如果您有大量數據，則必須採取諸如對大型數據物件採取越野儲存之類的措施，這會造成效能瓶頸。

And so again, people default to Postgres because they don't know anything better because all they know is relational and everyone is kind of moving off those other relational platforms. And that's the whole point I was saying earlier, once we educate developers on the flexibility of schema, how easily or horizontally scale, the rich query language where you can do aggregations and do sophisticated geospatial indexes, the productivity gains by using the document model and how easy is to organize data, it's -- people are just like, wow, life is so much easier.

再說一遍，人們預設使用 Postgres，因為他們不知道更好的東西，因為他們所知道的都是關係型的，而每個人都在某種程度上離開了其他關係型平台。這就是我之前所說的重點，一旦我們教育開發人員有關模式的靈活性、如何輕鬆地或水平擴展、可以進行聚合和復雜的地理空間索引的豐富查詢語言、通過使用文檔模型提高生產力以及組織數據是多麼容易，人們就像是，哇，生活輕鬆多了。

Now I want to be clear, this is not a zero-sum game. Postgres does not have to fail for us to be successful. It's a big market, and we're quite excited about the opportunity, but we do see customers moving off Postgres and coming to MongoDB.

現在我想澄清的是，這不是一場零和遊戲。Postgres 不一定要失敗才能讓我們成功。這是一個很大的市場，我們對這個機會感到非常興奮，但我們確實看到客戶從 Postgres 轉向 MongoDB。

Thank you.. That was very helpful. And maybe just a quick follow-up. If we normalize the $15 million in multiyear deal impact you had in Q3, would EA still be down sequentially in Q4? Thank you.

謝謝..這非常有幫助。也許只是快速跟進。如果我們將第三季 1,500 萬美元的多年交易影響正常化，那麼 EA 在第四季的業績還會繼續下滑嗎？謝謝。

We haven't given that level of guidance, but just trying to help you understand in the context of the full year numbers and the headwind that we talked about at the beginning of the year, just given the strength that we saw in Q3.

我們沒有給出這種程度的指導，只是試圖幫助您理解全年數據和我們在年初討論的逆風，以及我們在第三季度看到的強勁勢頭。

Got it. Thanks.

知道了。謝謝。

Raimo Lenschow, Barclays.

雷莫‧倫肖 (Raimo Lenshow)，巴克萊銀行。

Thank you. And if you think about the EA strength this quarter, Michael, you kind of give us a little bit there, like how should we think about renewal the renewal situation and renewal pool coming up like or that you have in Q3 coming up in Q4, et cetera, as well? And then like what does it mean in terms of cross-sell opportunity as people think about starting AI projects self-serve as you kind of mentioned earlier on the call?

謝謝。如果您考慮本季EA 的實力，邁克爾，您可以給我們一些信息，例如我們應該如何考慮續訂、續訂情況和續訂池，或者您在第三季度的續訂情況和第四季度的續訂池，等等，還有？然後，當人們考慮啟動自助式人工智慧專案時，交叉銷售機會意味著什麼，正如您之前在電話會議中提到的那樣？

Yeah. So I think about -- if you think about EA for Q4, it tends to be a large renewal quarter. But what we're talking about in terms of the guide is because we had such strength in multiyear that's where we would expect to see EA be down sequentially, which is not typically our pattern, which is why we called it out.

是的。所以我想——如果你考慮第四季的 EA，它往往是一個大的更新季度。但我們在指南方面所討論的是，因為我們在多年中擁有如此強大的實力，我們預計 EA 會連續下跌，這通常不是我們的模式，這就是我們指出這一點的原因。

In terms of AI workloads and some of those other things, I think it's early to tell. And obviously, we'll continue to evolve and assess our view when we get to the full year guide in March. And then we'll also have an updated view on how the cohorts are behaving and sort of how multiyear played out. But I think in terms of Q4, the comments that I made earlier, hopefully will help.

就人工智慧工作負載和其他一些事情而言，我認為現在下結論還為時過早。顯然，當我們在三月發布全年指南時，我們將繼續發展和評估我們的觀點。然後我們也將對這些群體的行為以及多年來的表現有一個最新的看法。但我認為就第四季而言，我之前發表的評論希望能有所幫助。

Yeah. Okay. Perfect. And then, Dev, can you talk a little bit about, like, obviously, there's a debate of like which database will be the persistent layer if you do AI projects, et cetera. What do you see from the big hyperscalers in terms of working with you guys and partnerships?

是的。好的。完美的。然後，Dev，你能談談，很明顯，如果你做人工智慧項目，哪個資料庫將是持久層等等，這是一個爭論。在與你們的合作和夥伴關係方面，您對大型超大規模企業有何看法？

We obviously just have AWS kind of summer, et cetera. Can you speak to a little bit like how your relationship with those Vegas is evolving around this? And Michael, all the best in case I don't talk to you.

顯然我們只是有 AWS 之類的夏天，等等。您能談談您與維加斯的關係是如何圍繞這件事演變的嗎？邁克爾，祝你一切順利，以防我不跟你說話。

Yeah. So I'll start with the partnership first, like our -- with AWS, as you said, they just had their Reinventure last week. It remains very, very strong. We closed a ton of deals this past quarter, some of them very, very large deals. We're doing integrations to some of the new products like Q and Bedrock and the engagement in the field has been really strong.

是的。因此，我將首先從合作夥伴關係開始，就像我們與 AWS 的合作夥伴關係一樣，正如您所說，他們上週剛剛進行了 Reinventure。它仍然非常非常強大。上個季度我們完成了大量交易，其中一些交易非常非常大。我們正在對 Q 和 Bedrock 等一些新產品進行集成，並且該領域的參與度非常高。

On Azure, I think we -- as I've shared in the past, we start off with a little bit of a slower start. But in the words of the person who runs their partner leadership, the Azure MongoDB relationship has never been stronger. We closed a large number of deals. We're part of what's called the Azure-native IC service program and have a bunch of deep integrations with Azure, including Fabric, Power BI, Visual Studio, Symantec Kernel and Azure OpenAI studio. And we're also one of Azure's largest marketplace partners.

在 Azure 上，我認為我們——正如我過去所分享的那樣，我們一開始的速度有點慢。但用夥伴領導階層負責人的話來說，Azure MongoDB 的關係從未如此牢固。我們完成了大量交易。我們是 Azure 原生 IC 服務計劃的一部分，並與 Azure 進行了大量深度集成，包括 Fabric、Power BI、Visual Studio、Symantec Kernel 和 Azure OpenAI studio。我們也是 Azure 最大的市場合作夥伴之一。

And GCP does -- we've actually seen some uptick in terms of co-sales that we've done this past quarter. GCP made some comp changes where that were favorable to working with MongoDB that we saw some results in the field, and we're focused on closing a handful of large deals with GCP in Q4. So in general, I would say things are going quite well.

GCP 確實如此——我們實際上看到上個季度的聯合銷售有所上升。GCP 進行了一些有利於與 MongoDB 合作的薪酬調整，我們在該領域看到了一些成果，並且我們專注於在第四季度與 GCP 達成一些大型交易。所以總的來說，我想說事情進展順利。

And then in terms of, I guess, implying your question was like the hyperscalers and are they potentially bundling things along with their AI offerings? I mean, candidly, since day one, the hyperscalers have been bundling their database offerings with every offering that they have. And that's been their pretty predominant strategy.

然後，我想，暗示你的問題就像超大規模企業，他們是否有可能將東西與他們的人工智慧產品捆綁在一起？坦白說，從第一天起，超大規模提供者就將他們的資料庫產品與他們擁有的每項產品捆綁在一起。這是他們相當重要的策略。

And we've -- I think we've executed well against strategy because databases are not like a by-the-way decision. It's an important decision. And I think the hyperscalers are seeing our performance and realize it's better to partner with us. And as I said, customers understand the importance of the data layer, especially by our applications. And so the partnership across all three hyperscalers is strong.

我認為我們在戰略上執行得很好，因為資料庫不像一個順便的決定。這是一個重要的決定。我認為超大規模企業正在看到我們的表現，並意識到與我們合作會更好。正如我所說，客戶了解資料層的重要性，尤其是我們的應用程式。因此，所有三個超大規模提供者之間的合作夥伴關係都很牢固。

Okay, perfect. Thank you.

好的，完美。謝謝。

Thanks, Raimo.

謝謝，雷莫。

Brad Sills, Bank of America.

布拉德·希爾斯，美國銀行。

Great. Thank you so much. And congratulations Michael on your next move. I wanted to ask about new workloads here, vector search, stream processing, relational migrator. Is there any one of those three that's ramping faster than maybe you expected? Just a little bit of color on how those new workload types are ramping. Thank you.

偉大的。太感謝了。並祝賀邁克爾的下一步。我想詢問這裡的新工作負載，向量搜索，流處理，關係遷移器。這三者中是否有哪一個的成長速度比您預期的還要快？只是對這些新的工作負載類型如何增長進行一些說明。謝謝。

Yeah. I'll kind of give you just a rundown on some of the -- I mean, essentially, you're asking about the new products, like on search. We introduced a new capability called Atlas Search nodes, which where you can asymmetrically scale your search nodes because if you have a search intensive use case, you don't have to scale all your nodes because that have become quite expensive.

是的。我會向您簡要介紹一些 - 我的意思是，本質上，您正在詢問新產品，例如搜尋產品。我們引入了一項稱為 Atlas 搜尋節點的新功能，您可以在其中不對稱地擴展搜尋節點，因為如果您有搜尋密集型用例，則不必擴展所有節點，因為這已經變得相當昂貴。

And we've seen that this kind of groundbreaking capability really well received. The demand is quite high. And because customers like they can tune the configuration to the unique needs of their search requirements.

我們已經看到這種突破性的能力非常受歡迎。要求相當高。而且因為客戶喜歡他們可以根據其搜尋要求的獨特需求調整配置。

One of the world's largest banks is using Atlas Search to provide like a Google-like search experience on payments data for massive corporate customers. So there's a customer-facing application, and so performance and scalability are critical. A leading provider of AI-powered accounting software uses Atlas Search to Power's invoice analytics future, which allows end users on finance teams to perform ad hoc analysis and easily find past due invoices and voices that contain errors. So that's Search.

全球最大的銀行之一正在使用 Atlas Search 為大量企業客戶提供類似 Google 的支付資料搜尋體驗。因此，存在面向客戶的應用程序，因此效能和可擴展性至關重要。一家領先的人工智慧會計軟體供應商使用 Atlas Search 來推動發票分析的未來，使財務團隊的最終用戶能夠執行臨時分析並輕鬆找到過期發票和包含錯誤的聲音。這就是搜尋。

On Vector Search, again, and it's been our kind of our first full year since going generally available and the product uptake has been actually very, very high. In Q3, we released quantization for Atlas Vector Search, which reduces the memory requirements by up to 96%, allowing us to support larger Vector workloads with vastly improved price performance. For example, a multinational news organization created a GenAI powered tool designed to help producers and journalist sufficiently search, summarize and verify information from vast and very data sources.

再說一次，在向量搜尋方面，這是我們自全面推出以來的第一個完整的一年，產品的使用率實際上非常非常高。在第三季度，我們發布了 Atlas Vector Search 的量化功能，可將記憶體需求降低高達 96%，使我們能夠支援更大的 Vector 工作負載，同時大幅提高性價比。例如，一家跨國新聞機構創建了一款 GenAI 驅動的工具，旨在幫助製片人和記者充分搜尋、總結和驗證來自大量資料來源的資訊。

A leading security firm is using Atlas Vector certified AI fraud and a leading global media company replaced elastic search with hybrid search and vector search use case for a user recommendation engine that's built to suggest -- that's building to suggest articles to end users. And so that's super exciting to see as well.

一家領先的安全公司正在使用經 Atlas Vector 認證的人工智慧欺詐，一家全球領先的媒體公司將彈性搜尋替換為混合搜尋和向量搜尋用例，用於用戶推薦引擎，該引擎旨在向最終用戶推薦文章。所以這也是非常令人興奮的。

We're also seeing a lot of interest in our streaming product. Demand is very high. We just rolled it out to another hyperscaler. And customers are commenting on that the use cases of being able to embed stream processing with MongoDB, it makes their life so much easier.

我們也看到人們對我們的串流媒體產品很感興趣。需求量非常高。我們剛剛將其推廣到另一個超大規模提供者。客戶評論說，能夠在 MongoDB 中嵌入流處理的用例讓他們的生活變得更加輕鬆。

So overall, we're quite pleased with the progress we're making on the new products. And as I said before, natively bundling all these capabilities really reduces or eliminates the need for customers to have to bolt on a bunch of different technologies to solve the same problem, saving them a lot of time, money, and cost, and risk.

總的來說，我們對新產品的進展感到非常滿意。正如我之前所說，本地捆綁所有這些功能確實減少或消除了客戶必須使用一堆不同技術來解決同一問題的需要，從而為他們節省了大量的時間、金錢、成本和風險。

That's really exciting. Thanks, Dave. And then I wanted to ask a question around Cedric's appointment, any focus that may be different here under his leadership that we should be thinking about going forward? Thank you.

這真的很令人興奮。謝謝，戴夫。然後我想問一個關於塞德里克任命的問題，在他的領導下，我們應該考慮向前推進的焦點可能有所不同？謝謝。

No. Cedric has been our CRO for gosh now, like, I think, like five, six years. And I was the interim CRO for about three quarters until he took over when we last made a change. And this is really an expansion of his responsibilities.

不。天啊，塞德里克現在已經擔任我們的首席研究官，我想，大概有五、六年了。我擔任臨時 CRO 大約有四分之三時間，直到我們上次做出改變時他接任。這確實是他職責的擴大。

I've known Cedric for a long time. He and I have worked with at multiple different companies. I think I have a good barometer for understanding sales leadership. There's a number of sales leaders who worked at other top-tier software companies who used to work for me or with me. And so I'm super excited about the role Cedric is going to take.

我認識塞德里克很久了。他和我曾在多家不同的公司工作。我認為我有一個很好的衡量銷售領導力的晴雨表。有許多在其他頂尖軟體公司工作過的銷售主管曾經為我工作或與我一起工作。所以我對塞德里克將扮演的角色感到非常興奮。

And then we're also making some changes under Cedric to better align the different organizations so that we can more tightly work together on going up markets, on app monetization and positioning ourselves well to be the ideal database for GenAI apps.

然後，我們也在Cedric 的領導下做出了一些改變，以更好地協調不同的組織，以便我們能夠在新興市場、應用程式貨幣化方面更緊密地合作，並將自己定位為GenAI 應用程式的理想資料庫。

Super exciting. Thanks, Dave.

超級刺激。謝謝，戴夫。

Thank you. Thanks Brad.

謝謝。謝謝布拉德。

Mike Cikos of Needham & Company.

Needham & Company 的 Mike Cikos。

Thanks for taking the question here. I just wanted to come back to the consumption growth being slightly better than expectations again for the second quarter in a row now. And apologies if I missed it, but this improvement that we're seeing, is this across all vintages and geographies or is it potentially more concentrated in scope? Just trying to get a better understanding what's taking place out there and what's embedded in the guide?

感謝您在這裡提出問題。我只想回到連續第二季消費成長略好於預期的情況。如果我錯過了，我很抱歉，但我們看到的這種改進是跨越所有年份和地區的，還是可能更集中在範圍上？只是想更了解正在發生的事情以及指南中包含的內容？

Yeah. No, I would describe it as broad-based, Mike. And obviously, we're pleased to see it. And we're continuing monitoring and slicing and dicing it in different ways. And as we have information or insights to you, we'll share it. And without trying to throw a whole bunch of cold water on our mind, it was slightly better, not a step function change better, but good to see.

是的。不，我認為它具有廣泛的基礎，麥克。顯然，我們很高興看到它。我們正在繼續以不同的方式監控和切割它。當我們向您提供資訊或見解時，我們會分享。並沒有試圖向我們的頭腦潑一大堆冷水，它稍微好一點，不是一步函數改變更好，但很高興看到。

Terrific. And maybe for a quick follow-up for Dev, I think it builds off maybe Tyler's question at the top of the Q&A. But you had cited that some customers are thinking about their workloads more holistically and even looking to run AI workloads on-prem.

了不起。也許為了對 Dev 進行快速跟進，我認為它可能是基於泰勒在問答頂部提出的問題。但您提到，一些客戶正在更全面地考慮他們的工作負載，甚至希望在本地運行人工智慧工作負載。

How much of that do you think is just a function of customers are still trying to figure out how to optimize for latency and cost? Or is this more a demonstration of we really are in the early phases, the exploratory phase versus going into production? Is there any way to parse that out or is it to not necessarily connected?

您認為其中有多少只是客戶仍在試圖找出如何優化延遲和成本的函數？或者這更表明我們確實處於早期階段，即探索階段與投入生產階段？有什麼方法可以解析出來或它沒有必然的聯繫嗎？

Thank you. No, I think it's kind of a little bit of both. I think you have some customers who are very committed to running a big part of the estate on-prem. So by definition, then if they're going to build an AI workload, it has to be run on-prem, which means that they also need access to GPUs. And they're doing that.

謝謝。不，我認為兩者都有一點。我認為您有一些客戶非常致力於在本地運營大部分資產。因此，根據定義，如果他們要建立人工智慧工作負載，則必須在本地運行，這意味著他們還需要存取 GPU。他們正在這樣做。

And then other customers are leveraging basically renting GPUs from the cloud providers and building their own AI workloads. I do think we're in the very, very early days. They're still learning experimenting. More and more apps are entering production. And as I said on the prepared remarks, we have thousands of workload, AI workloads running on MongoDB.

然後其他客戶基本上利用從雲端供應商租用 GPU 並建立自己的 AI 工作負載。我確實認為我們還處於非常非常早期的階段。他們仍在學習實驗。越來越多的應用程式正在進入生產階段。正如我在準備好的演講中所說，我們有數千個工作負載、人工智慧工作負載在 MongoDB 上運作。

But a very small percentage of them have demonstrated meaningful product market fit. And so the initial traction is kind of still small. But I think as people get more sophisticated with AI as the AI technology matures and becomes more and more useful, I think applications will -- you'll start seeing these applications take off.

但其中只有極少數已表現出有意義的產品市場契合度。因此，最初的牽引力仍然很小。但我認為，隨著人工智慧技術的成熟和變得越來越有用，人們對人工智慧的了解越來越豐富，我認為應用程式將會——你會開始看到這些應用程式起飛。

I kind of chuckle that today, I see more senior leaders bragging about the chips they are using versus the Appstore building. So it just tells you that we're still in the very, very early days of this big platform shift.

我有點笑，今天，我看到更多的高級領導者吹噓他們正在使用的晶片與應用程式商店建設。所以它只是告訴您，我們仍處於這一重大平台轉變的非常非常早期的階段。

Great point. Thank you.

很棒的一點。謝謝。

Eric Heath, KeyBanc.

艾希斯 (Eric Heath)，KeyBanc。

Hi, thanks for taking the question. Michael, it sounds like the takeaway from the call is a greater focus on EA and on enterprise. So should we structurally rethink the EA business differently and think of this more as a healthy double-digit growth business going forward for the foreseeable future?

您好，感謝您提出問題。Michael，聽起來這次電話會議的要點是更關注 EA 和企業。那麼，我們是否應該從結構上以不同的方式重新思考 EA 業務，並將其視為在可預見的未來健康的兩位數成長業務？

And then if I could just ask a follow-up question separate to that. But Mike, I understand that it's still early to identify the fiscal '25 cohort of workloads. But just curious at a high level if they look and feel of higher quality than the fiscal '24 cohort of workloads?

然後我是否可以問一個單獨的後續問題。但麥克，我知道現在確定 25 財年的工作負載組還為時過早。但只是想知道，它們的外觀和感覺是否比 24 財年的工作負載群體更高品質？

Dev, do you want to tackle the first one in terms of EA?

Dev，你想解決 EA 方面的第一個問題嗎？

Yeah. I mean I would say -- I mean we are very committed to our run-anywhere strategy. And as I said, we are first investing in community where for many customers is the first way they experienced MongoDB, and we want them to have the full experience. So we're integrating search and vector search into our core product. And so they can out of the gate really start building applications.

是的。我想說的是——我的意思是我們非常致力於我們的「隨處運行」策略。正如我所說，我們首先投資社區，對於許多客戶來說，這是他們體驗 MongoDB 的第一個方式，我們希望他們有完整的體驗。因此，我們正在將搜尋和向量搜尋整合到我們的核心產品中。這樣他們就可以真正開始建立應用程式。

That will then transition to building those capabilities into EA. So we are clearly investing in the EA product. But Atlas is still a big, big part of our business and a big, big part of our growth engine, and we typically launch new features on Atlas. And because of the capabilities we already have, the fact that it's multi-cloud makes it a very, very compelling offering for many customers.

然後將過渡到將這些功能建置到 EA 中。所以我們顯然是在投資 EA 產品。但 Atlas 仍然是我們業務的一個很大的組成部分，也是我們成長引擎的一個很大的組成部分，我們通常會在 Atlas 上推出新功能。由於我們已經擁有的功能，它的多雲特性使其成為對許多客戶來說非常非常有吸引力的產品。

Yeah. And I think in terms of the workloads, I do think it's early, just as a reminder for folks, they tend to start small, although grow quickly. I think the only other thing that I can add is we've been pretty consistent in that we've been pleased with the new business that we've done, but we need some time to let the cohorts play out as we attract them. But I think, like I said, we've been happy with the new business that we were winning.

是的。我認為就工作量而言，我確實認為現在還為時過早，只是提醒人們，他們往往從小規模開始，儘管成長很快。我認為我可以補充的唯一一件事是，我們一直非常一致，我們對我們所做的新業務感到滿意，但我們需要一些時間來讓我們吸引的群體發揮作用。但我認為，正如我所說，我們對贏得的新業務感到滿意。

William Power, Baird.

威廉鮑爾，貝爾德。

Thank you. Dev, you had some encouraging comments on relational migrator I wonder if you could just touch on what you think is driving the higher interest here? I mean, it sounds like AI is contributing and helping, but it would be great to get some more color there because that still feels like obviously a meaningful long-term opportunity?

謝謝。Dev，您對關係遷移器有一些令人鼓舞的評論，我想知道您是否可以談談您認為是什麼推動了這裡的更高興趣？我的意思是，聽起來人工智慧正在做出貢獻和提供幫助，但如果在那裡獲得更多色彩那就太好了，因為這仍然感覺顯然是一個有意義的長期機會？

And then maybe the second part of the question for Dev or Michael, just be great to get any other framework around the professional services investments. Any way to kind of think about quantification and timing of that?

然後，對於 Dev 或 Michael 來說，問題的第二部分可能是關於專業服務投資的任何其他框架。有什麼辦法可以考慮量化和時間安排嗎？

Yeah. So the reason we're so excited about the opportunity to go after legacy applications is that, one -- it seems like there's a confluence of events happening. One is that the increasing cost and tax of supporting and managing these legacy apps are just going up enough. Second, for many customers who in regulated industries, the regulators are calling their -- the fact that they're running on these legacy apps a systemic risk so they can no longer take the can down the road.

是的。因此，我們對追尋遺留應用程式的機會如此興奮的原因是，一——似乎正在發生一系列事件。一是支持和管理這些遺留應用程式的成本和稅收不斷增加，已經夠高的了。其次，對於受監管行業的許多客戶來說，監管機構稱他們在這些遺留應用程式上運行的事實是系統性風險，因此他們不能再繼續下去。

Third, also because they no longer keep can around some vendors are going end of life. So they have to make a decision to migrate those applications to a more modern tech stack. Fourth, because GenAI is so predicated on data and to build a competitive advantage, you need to leverage your proprietary data, people want to access that data and be able to do so easily. And so that's another reason for them to want to modernize.

第三，也因為他們不再保留罐頭，一些供應商的生命週期即將結束。因此，他們必須決定將這些應用程式遷移到更現代的技術堆疊。第四，由於 GenAI 非常依賴數據並建立競爭優勢，因此您需要利用您的專有數據，人們希望能夠輕鬆存取該數據。這是他們想要現代化的另一個原因。

And then you also have people who built those applications who are retiring or just no longer the firm, so it just creates more and more risk for the companies. Given all that, customers are incredibly interested in figuring out a way to easily and safely and securely migrate of those applications.

然後，還有一些建立這些應用程式的人即將退休或不再是公司，因此這只會給公司帶來越來越多的風險。有鑑於此，客戶對找到一種輕鬆、安全地遷移這些應用程式的方法非常感興趣。

And we always could help them very easily move the data and map the schema from a relational schema to a document schema. The hardest part was essentially rewriting the application. Now with the advent of GenAI, you can now significantly reduce the time.

我們總是可以幫助他們非常輕鬆地移動資料並將模式從關係模式映射到文件模式。最困難的部分本質上是重寫應用程式。現在，隨著 GenAI 的出現，您現在可以顯著縮短時間。

One, you can use GenAI to analyze the existing code. Two, you can use GenAI to reverse engineer tests to test what the code does. And then three, you can use GenAI to build new code and then use this test to ensure that the new code produce the same results as the old code. And so all that time and effort is suddenly cut in a meaningful way, and that's only creating a lot of interest from customers saying, oh my goodness.

第一，你可以用GenAI來分析現有的程式碼。第二，您可以使用 GenAI 進行逆向工程測試來測試程式碼的功能。第三，您可以使用 GenAI 建立新程式碼，然後使用此測試來確保新程式碼產生與舊程式碼相同的結果。因此，所有的時間和精力突然以有意義的方式被削減，這只會讓客戶產生很大的興趣，說，哦，天哪。

And if you're already on a relational app, moving to another relation lab doesn't feel like modernization. So the other advantage is that moving to MongoDB gives them a much more modern platform, a much more agile, flexible performance and scalable platform for their future needs. And that's why we're so excited.

如果您已經在使用關係應用程序，那麼轉移到另一個關係實驗室並不感覺像是現代化。因此，另一個優勢是，遷移到 MongoDB 為他們提供了一個更現代化的平台，一個更敏捷、更靈活的效能和可擴展的平台，可以滿足他們未來的需求。這就是我們如此興奮的原因。

Again, it's early days. We've run a number of pilots that have gone well. We're in the process of working with some customers now in the migration process. This will take time because these are very, very complex applications.

再說一次，現在還為時過早。我們已經進行了一些進展順利的試點。我們正在與一些客戶合作進行遷移。這需要時間，因為這些是非常非常複雜的應用程式。

And actually, one thing I also mentioned was that they're not just going after -- saying go after some tertiary Tier 2 or Tier 3 application. They're saying, we want you to look at some of our crown jewels because these are the apps that are most painful for us. So that's also very exciting. But again, this will take time, but we're very committed to this, and we think this is going to drive -- help us drive long-term -- meaningful long-term growth.

事實上，我還提到的一件事是，他們不僅僅追求——說追求一些第三級或第三級申請。他們說，我們希望您看看我們的一些皇冠上的寶石，因為這些應用程式對我們來說是最痛苦的。所以這也非常令人興奮。但這需要時間，但我們非常致力於這一點，我們認為這將推動——幫助我們推動長期——有意義的長期成長。

Yes, Will. And to the last part of your question on the professional services investment, we're really building out that capacity in order to meet the demand that we're seeing relative to the opportunity. We're calling it in particular because it has a gross margin impact because that's where that will typically show up.

是的，威爾。對於您關於專業服務投資的問題的最後一部分，我們確實正在建立這種能力，以滿足我們所看到的相對於機會的需求。我們之所以特別稱呼它，是因為它會對毛利率產生影響，因為這通常會出現在毛利率上。

And maybe the last thing, and this is probably obvious, but just to sort of underscore it, is the reason we're doing this, though, is for the ARR, right, to drive the new workloads, the additional workloads over to MongoDB as part of that migration. And over time, as we've talked about before, we hope and expect to be able to leverage technology more and more, but at least initially and into the medium term, to be a healthy human/services component to that. I just wanted to sort of effectively telegraph that out to folks.

也許最後一件事，這可能是顯而易見的，但只是為了強調一下，我們這樣做的原因是為了 ARR，對吧，驅動新的工作負載，將額外的工作負載轉移到 MongoDB作為該遷移的一部分。隨著時間的推移，正如我們之前談到的，我們希望並期望能夠越來越多地利用技術，但至少在最初和中期，成為健康的人類/服務組成部分。我只是想有效地向人們傳達這一點。

That's helpful. Thank you.

這很有幫助。謝謝。

Rudy Kessinger, DA Davidson.

魯迪·凱辛格，地方檢察官戴維森。

Thanks for taking me in here. I believe last quarter, you said consumption growth slightly ahead of expectations and while down slower year-over-year growth versus Q2 last year, the year-over-year growth did improve from Q1. And so I guess curious for Q3, could you make a comment in that same regard, obviously, slower on a year-over-year basis than Q3 last year. But was it stable with year-over-year consumption growth in Q2 or better or worse?

謝謝你帶我來到這裡。我相信上個季度，您說消費成長略超預期，雖然年成長較去年第二季放緩，但年成長確實比第一季有所改善。因此，我想對第三季度感到好奇，您能否在同一方面發表評論，顯然，同比第三季度比去年第三季度要慢。但第二季消費年增是穩定還是更好還是更差？

Yes. Rudy, thanks for the question. We haven't specifically called that out relative to Q2. We did see lower year-over-year growth, as we called out, we did see a seasonal rebound. Usually, Q3 is stronger than Q2, and we talked about how that was smaller than in the prior year. So hopefully, that will help you all triangulate.

是的。魯迪，謝謝你的提問。我們還沒有針對第二季具體指出這一點。正如我們所說，我們確實看到了同比增長較低，但我們確實看到了季節性反彈。通常，第三季度強於第二季度，我們討論了第三季度的增幅如何小於前一年。希望這能幫助大家進行三角測量。

Okay. And then just a quick follow-up. I believe it was on your Q4 call back in March. At that point, Dev, you said it would be at least another year until AI applications are being deployed at scale. It sounds like the commentary some early large workloads, but out of the thousands just not many that are at large scale. I guess is your expectation now that maybe it's still at least another year until we're seeing broad AI application rollout to scale?

好的。然後進行快速跟進。我相信這是您在三月第四季的電話會議上提到的。那時，Dev，你說至少還需要一年的時間才能大規模部署人工智慧應用程式。這聽起來像是一些早期大型工作負載的評論，但在數千個中，大規模的並不多。我想您現在的期望是，也許至少還需要一年時間，我們才能看到廣泛的人工智慧應用程式大規模推廣？

Yeah. I think a lot of it is a function of what's happening in the R&D side of AI, right? So for example, today, we don't have a very compelling model designed for our phones, right? Because today, the phones don't have the computing horsepower to run complex models. So you don't see a ton of very, very successful consumer apps besides, say, ChatGPT or Claude. So we don't -- we also don't see like hundreds of apps taking off like you saw kind of the first generation of like the Internet or the cloud era, right, or the mobile era.

是的。我認為這很大程度上是人工智慧研發方面發生的事情的結果，對嗎？例如，今天，我們沒有為我們的手機設計一個非常引人注目的模型，對吧？因為今天的手機不具備運行複雜模型的運算能力。因此，除了 ChatGPT 或 Claude 之外，你看不到大量非常非常成功的消費者應用程式。所以我們沒有——我們也沒有看到數百個應用程式像你看到的第一代那樣起飛，例如網路或雲端時代，或是行動時代。

So like I think we're still in the early days of AI. And so while we see a lot of people building AI apps, a lot of them have kind of fairly rudimentary functionality. But I think that over time, that's going to change. And in fact, I know it will change.

所以我認為我們仍處於人工智慧的早期階段。因此，雖然我們看到很多人建立人工智慧應用程序，但其中許多都具有相當基本的功能。但我認為隨著時間的推移，這種情況將會改變。事實上，我知道它會改變。

I just can't predict when that will happen. But where we do see apps having production, having traction, we're seeing them grow very, very quickly. And we have a lot of them on our platform, it's just very few of them really have meaningful.

我只是無法預測什麼時候會發生。但我們確實看到應用程式已經投入生產、具有吸引力，我們看到它們成長得非常非常快。我們的平台上有很多這樣的東西，但真正有意義的卻很少。

Thank you. And that concludes today's Q&A session. I would like to go ahead and turn the call back over to Dev for closing remarks. Please go ahead.

謝謝。今天的問答環節到此結束。我想繼續將電話轉回給 Dev 進行結束語。請繼續。

Thank you, everyone. I just wanted to say we're really pleased with our Q3 results with strong new business performance and revenue exceeding expectations across both Atlas and EA. We're making the necessary investments to expand our enterprise channel where we see the largest opportunity to establish MongoDB as a standard and the strongest returns on our go-to-market investments.

謝謝大家。我只是想說，我們對第三季的業績感到非常滿意，Atlas 和 EA 強勁的新業務表現和收入都超出了預期。我們正在進行必要的投資來擴展我們的企業管道，我們看到了將 MongoDB 建立為標準的最大機會，以及我們的市場投資的最強回報。

Looking ahead, we are encouraged by the progress we're making on both accelerating legacy app monetization with AI as well as establishing ourselves as a standard of the emerging AI tech stack for greenfield AI applications. And last but not least, I would like to thank Michael again for his contributions over the past 10 years and wish him well. Thank you, everyone, and we'll talk to you soon.

展望未來，我們在利用人工智慧加速傳統應用程式貨幣化以及將自己確立為新興人工智慧應用程式的新興人工智慧技術堆疊標準方面所取得的進展感到鼓舞。最後但並非最不重要的一點是，我要再次感謝邁克爾在過去十年中所做的貢獻並祝他一切順利。謝謝大家，我們很快就會和你們談談。

Thank you for participating in today's conference call. You may all disconnect now.

感謝您參加今天的電話會議。你們現在可以斷開連結了。