MongoDB Inc (MDB) 2026 Q2 法說會逐字稿

Good day everyone and welcome to MongoDB's second sixth quarter fiscal year 2026 earnings call. (Operator Instructions) Please note this conference is being recorded. Now it's my pleasure to turn the call over to Brian Denyeau from ICR. Please go ahead.

大家好，歡迎參加 MongoDB 2026 財年第六季第二季財報電話會議。（操作員指示）請注意，本次會議正在錄音。現在我很高興將電話轉給 ICR 的 Brian Denyeau。請繼續。

Thank you Carmen. Good afternoon, and thank you for joining us today to review MongoDB's second quarter fiscal 2026 financial results, which we announced in our press release issued after the close of the market today. Joining the call today are Dev Ittycheria, President and CEO of MongoDB; Mike Berry, CFO of MongoDB; and Jess Lubert, MongoDB's new Vice President of Investor Relations.

謝謝你，卡門。下午好，感謝您今天加入我們，共同回顧 MongoDB 2026 財年第二季的財務業績，我們在今天收盤後發布的新聞稿中公佈了這一業績。今天參加電話會議的有 MongoDB 總裁兼執行長 Dev Ittycheria、MongoDB 財務長 Mike Berry 以及 MongoDB 新任投資者關係副總裁 Jess Lubert。

During this call, we will make forward-looking statements, including statements related to our market and future growth opportunities. Our opportunity to win new business, our expectations regarding Atlas consumption growth, the impact of non-Atlas business and multiyear license revenue, the long-term opportunity of AI, our financial guidance and underlying assumptions, and our investments in growth opportunities in AI.

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。我們贏得新業務的機會、我們對 Atlas 消費成長的預期、非 Atlas 業務和多年許可收入的影響、人工智慧的長期機會、我們的財務指導和基本假設以及我們對人工智慧成長機會的投資。

These statements are subject to a variety of risks and uncertainties, including the results of operations and financial conditions that could cause actual results to differ materially from our expectations. 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 April 30, 2025, filed with the SEC on June 4, 2025.

這些聲明受到各種風險和不確定性的影響，包括可能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。有關可能影響我們實際結果的重大風險和不確定性的討論，請參閱我們於 2025 年 6 月 4 日向美國證券交易委員會提交的截至 2025 年 4 月 30 日的季度 10-Q 表季度報告中所述的風險。

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. Additionally, we will discuss non-GAAP financial measures on this conference call.

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，除非法律要求，否則我們不承擔更新這些陳述的義務。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。

Please refer to the tables in our earnings release on the Investor Relations portion of our website for a reconciliation of these measures to the most directly comparable GAAP financial measure. With that, I'd like to turn the call over to Dev.

請參閱我們網站投資者關係部分的收益報告表格，以了解這些指標與最直接可比較的 GAAP 財務指標的對照情況。說完這些，我想把電話轉給 Dev。

Thank you, Brian, and thank you to everyone for joining us today. Before discussing our strong quarter, I want to remind everyone about our upcoming Investor Day, which will take place on September 17 at the Javits Center in New York City during our .local conference. We'll spend a day discussing the investments we're making to drive durable growth and margin expansion and our view of the future. I look forward to seeing you then.

謝謝你，布萊恩，也謝謝今天參加我們活動的所有人。在討論我們強勁的季度表現之前，我想提醒大家我們即將舉行的投資者日，該活動將於 9 月 17 日在紐約市賈維茨中心的 .local 會議期間舉行。我們將花一天時間討論為推動持久成長和利潤擴張而進行的投資以及我們對未來的看法。我期待到時見到你。

Now on to Q2. I'm pleased to report another strong quarter as we continue to execute against a large market opportunity. Let me start with our results before giving you a broader company update. We generated revenue of $591 million, up 24% year-over-year and above the high end of our guidance.

現在進入第二季。我很高興地報告，我們又迎來了一個強勁的季度，因為我們繼續抓住巨大的市場機會。在向您介紹更廣泛的公司最新情況之前，讓我先介紹一下我們的業績。我們實現了 5.91 億美元的收入，年增 24%，高於我們預期的最高值。

Atlas revenue grew 29% year-over-year, representing 64% of total revenue. We delivered non-GAAP operating income of $87 million or a 15% non-GAAP operating margin, and we ended the quarter with over 59,900 customers.

Atlas 營收年增 29%，佔總營收的 64%。我們實現了 8,700 萬美元的非 GAAP 營業收入或 15% 的非 GAAP 營業利潤率，本季末我們擁有超過 59,900 名客戶。

Atlas performance was strong, accelerating to 29% year-over-year growth, up from 26% in Q1. Our customer additions were also robust. We have added over 5,000 customers over the last two quarters. These results reflect the strength of MongoDB's platform, our flexible document model, expanded capabilities like search and Vector Search, enterprise readiness and the ability to run anywhere.

Atlas 表現強勁，年增 29%，高於第一季的 26%。我們的客戶數量也大幅增加。過去兩個季度，我們增加了 5,000 多名客戶。這些結果反映了 MongoDB 平台的實力、我們靈活的文件模型、搜尋和向量搜尋等擴展功能、企業就緒性以及在任何地方運行的能力。

Many of our recently added customers are building AI applications, underscoring how our value proposition is resonating for AI, and why MongoDB is emerging as a key component of the AI infrastructure stat. At the same time, we significantly outperformed on operating margin, demonstrated that we can drive durable revenue growth while expanding profitably.

我們最近增加的許多客戶都在建立人工智慧應用程序，這強調了我們的價值主張如何引起人工智慧的共鳴，以及為什麼 MongoDB 正在成為人工智慧基礎設施統計的關鍵組成部分。同時，我們的營業利潤率顯著提高，證明我們可以在擴大盈利的同時推動持久的收入成長。

In short, our results show that customers are choosing MongoDB. Let me tell you why. First, MongoDB is an enterprise-ready database capable of meeting the most stringent enterprise requirements. Over 70% of the Fortune 500 as well as 7 of the 10 largest banks, 14 of the largest 15 healthcare companies, 9 of the 10 largest manufacturers globally are MongoDB customers.

簡而言之，我們的結果表明客戶正在選擇 MongoDB。讓我來告訴你為什麼。首先，MongoDB 是一個企業級資料庫，能夠滿足最嚴格的企業要求。全球財富 500 強企業中超過 70% 的企業、十大銀行中的 7 家、15 家最大醫療保健公司中的 14 家、十大製造商中的 9 家都是 MongoDB 的客戶。

MongoDB is a battle-tested enterprise platform relied on by some of the most sophisticated and demanding organizations of the world in part because of our strong enterprise posture across security, durability, availability and performance.

MongoDB 是一個久經考驗的企業平台，受到世界上一些最成熟、要求最高的組織的信賴，部分原因是我們在安全性、耐用性、可用性和效能方面擁有強大的企業地位。

Atlas enable one of the world's largest automakers to overcome Postgres scalability and flexibility limits while reducing complexity. The company's management console attracts over 8.5 million vehicles, requiring a modern schema to handle both structured and unstructured data, something Postgres could not had.

Atlas 幫助世界上最大的汽車製造商之一克服了 Postgres 可擴展性和靈活性的限制，同時降低了複雜性。該公司的管理控制台吸引了超過 850 萬輛汽車，需要一種現代模式來處理結構化和非結構化數據，這是 Postgres 所無法做到的。

Ultimately, Atlas consolidated infrastructure, accelerated innovation and support the scale of millions of connected vehicles. Second, MongoDB suitable for a broad range of use cases, including the most mission-critical and transaction-intensive applications.

最終，Atlas 整合了基礎設施、加速了創新並支援數百萬輛連網汽車的規模。其次，MongoDB 適用於廣泛的用例，包括最關鍵的任務和交易密集型應用程式。

MongoDB has also supported full asset transactions for more than six years, ensuring strong consistency and data integrity at scale. This is why some of the world's most demanding transactional workloads run on MongoDB today.

MongoDB 也支援全資產交易超過六年，確保了大規模的強一致性和資料完整性。這就是為什麼當今世界上一些要求最苛刻的事務工作負載在 MongoDB 上運行的原因。

For example, Deutsche Telekom selected MongoDB Atlas as the foundation for its internal development platform, which includes mission-critical workloads like contract management, device purchases and billing for 30 million customers.

例如，德國電信選擇 MongoDB Atlas 作為其內部開發平台的基礎，該平台包括合約管理、設備採購和 3,000 萬客戶的計費等關鍵任務工作負載。

With 90 Atlas clusters managing over 60 million customer records, Deutsche Telekom's customer data platform now handles 15 times the concurrent log into legacy systems. By consolidating these high-volume transaction-intensive applications on MongoDB, Deutsche Telekom has improved resiliency, accelerate innovation and deliver a step change in customer engagement.

德國電信的客戶資料平台擁有 90 個 Atlas 集群，管理超過 6,000 萬筆客戶記錄，目前可處理 15 倍於原有系統的並發登入資料。透過在 MongoDB 上整合這些大容量交易密集型應用程序，德國電信提高了彈性，加速了創新，並在客戶參與度方面實現了顯著的改變。

Third, MongoDB has redefined what's core for the database by natively including capabilities like search, Vector Search, embeddings and stream processing. Comparing MongoDB to another database like Postgres is not an apples-to-apples comparison. Take a global e-commerce application that manages inventory and order data while enabling product discovery through sophisticated search across millions of SKUs.

第三，MongoDB 透過原生包含搜尋、向量搜尋、嵌入和流處理等功能重新定義了資料庫的核心。將 MongoDB 與 Postgres 等其他資料庫進行比較並不是同類的比較。採用全球電子商務應用程式來管理庫存和訂單數據，同時透過對數百萬個 SKU 進行複雜的搜尋來實現產品發現。

The choice for this application opportunity not going to be a Postgres is between MongoDB or Postgres plus other offerings like Pinecone, Elastic and Cohere for embeddings. MongoDB's complete solution allows developers to spend less time sitting together and maintaining a patchwork of the spare systems and more time building differentiated functionality that drives the business forward.

這個應用機會的選擇不會是 Postgres，而是在 MongoDB 或 Postgres 加上其他產品（如 Pinecone、Elastic 和 Cohere）之間進行嵌入。MongoDB 的完整解決方案使開發人員可以減少坐在一起維護備用系統的時間，而將更多的時間用於建立推動業務發展的差異化功能。

For example, Agibank, Brazilian neobank with 2.7 million active customers migrated their content management systems storing customer records in Postgres to Atlas. As data volumes grew, Postgres' inflexibility and task execution latency drove performance issues and the database like sophisticated secondary indexes and full text search, hurting sales of core offerings such as loans, insurance and card approvals.

例如，擁有 270 萬活躍客戶的巴西新銀行 Agibank 將其儲存在 Postgres 中的客戶記錄內容管理系統遷移到 Atlas。隨著資料量的增長，Postgres 的不靈活性和任務執行延遲導致了性能問題，並且資料庫類似於複雜的二級索引和全文搜索，從而損害了貸款、保險和信用卡審批等核心產品的銷售。

Agibank was constantly updating the database and manually scaling infrastructure. which is both time-consuming and error prone. With Atlas, Agibank gained a resilient flexible system that handle rising demand and support new services, delivering nearly 5 times better performance and 90% lower cost, all with no outages.

Agibank 不斷更新資料庫並手動擴展基礎設施，這既耗時又容易出錯。借助 Atlas，Agibank 獲得了一個具有彈性的靈活系統，可以處理不斷增長的需求並支援新服務，效能提高了近 5 倍，成本降低了 90%，而且不會中斷。

Fourth, MongoDB is emerging as a standard for AI applications. Over the last few quarters, we've seen a strength in our self-serve channel, driven in part by AI native startups choosing Atlas as the foundation for their applications. In the enterprise segment, adoption is real but early. Much of the activity today centers on employee productivity tools and packaged ISV solutions.

第四，MongoDB正在成為AI應用的標準。在過去的幾個季度中，我們看到了自助服務管道的優勢，部分原因是人工智慧原生新創公司選擇 Atlas 作為其應用程式的基礎。在企業領域，採用是現實，但還為時過早。當今的大部分活動都集中在員工生產力工具和打包的 ISV 解決方案上。

Enterprises are still in the very early stages of building their own custom AI applications that will transform their business. We consistently hear from customers that when teams try to scale from Vibe-coded prototypes built on relational back ends to enterprise-grade deployments. These platform quickly hit limits in flexibility, scalability and performance. Across startups and increasingly enterprises, our unified platform is resonating strongly.

企業仍處於建立自己的客製化 AI 應用程式的早期階段，這些應用程式將改變他們的業務。我們經常聽到客戶說，當團隊嘗試從建立在關係後端的 Vibe 編碼原型擴展到企業級部署。這些平台的靈活性、可擴展性和效能很快就達到了極限。在新創公司和越來越多的企業中，我們的統一平台引起了強烈共鳴。

In the enterprise segment, a leading electric vehicle company chose Atlas and Vector Search to power autonomous driving platform. After testing Vector Search against Postgres PG vector for their in-vehicle voice assistant, they selected MongoDB for superior performance at scale and stronger ROI. They now rely on Atlas to handle over 1 billion vectors and expect 10 times growth in data usage by next year.

在企業領域，一家領先的電動車公司選擇 Atlas 和 Vector Search 來支援自動駕駛平台。在針對車載語音助理測試了 Vector Search 與 Postgres PG 向量之後，他們選擇了 MongoDB，因為它具有卓越的規模性能和更高的投資回報率。他們現在依靠 Atlas 來處理超過 10 億個向量，並預計到明年數據使用量將增加 10 倍。

Dev Red -- DevRev, a well-funded AI-native platform with proven founders disrupting the help desk market build agent OS, its complete agentic platform that autonomously handles billions of monthly requests on Atlas.

Dev Red—DevRev 是一個資金充足的 AI 原生平台，擁有經驗豐富的創辦人，正在顛覆幫助台市場，建立代理作業系統，其完整的代理平台可自主處理 Atlas 上每月數十億個請求。

DevRev accelerated development, velocity, lower cost and scale globally with low latency by using Atlas. Agent OS also leverages Atlas Vector Search for Semantic Search enriching its notch graph and LLMs with domain-specific content.

DevRev 透過使用 Atlas 加速了開發速度、降低了成本並在全球範圍內以低延遲擴大了規模。Agent OS 也利用 Atlas Vector Search 進行語義搜索，豐富其 Notch 圖和 LLM 的領域特定內容。

Companies in nearly every industry and across every geography are choosing MongoDB because we deliver the features, performance, cost effectiveness and AI readiness they need, all in one platform. As we look ahead, we remain confident in MongoDB's position to lead both the current wave of digital transformation and the next wave powered by AI.

幾乎每個產業、每個地區的公司都選擇 MongoDB，因為我們在一個平台上提供他們所需的功能、效能、成本效益和 AI 就緒性。展望未來，我們仍對 MongoDB 引領當前數位轉型浪潮和下一波人工智慧浪潮的地位充滿信心。

With that, here's Mike.

以下是麥克的發言。

Thanks, Dev. I'll begin with a detailed review of our second quarter results, and then finish with our outlook for the third quarter and fiscal year '26. I will be discussing our results on a non-GAAP basis, unless otherwise noted. As Dev mentioned, we had a great quarter as we exceeded all of our guidance ranges and are increasing our full year guidance across the board.

謝謝，Dev。我將首先詳細回顧我們的第二季業績，然後總結我們對第三季和26財年的展望。除非另有說明，我將以非 GAAP 為基礎討論我們的結果。正如 Dev 所提到的，我們本季表現非常出色，超出了所有預期範圍，並且全面提高了全年預期。

Now on to the results. In the second quarter, total revenue was $591 million, up 24% year-over-year and above the high end of our guidance. Shifting to our product mix, Atlas revenue outperformed our expectations and year-over-year growth accelerated to 29% in the quarter and now represents 74% of total revenue.

現在來看看結果。第二季總營收為 5.91 億美元，年增 24%，高於我們預期的最高值。轉向我們的產品組合，Atlas 收入超出了我們的預期，本季同比增長加速至 29%，目前佔總收入的 74%。

This compares to 71% in the second quarter of fiscal '25 and 72% last quarter. We had an impressive Atlas growth quarter, which benefited in part from the strong start to consumption in May that we referenced on our last call as well as broad-based strength, especially in larger customers in the US.

相比之下，25 財年第二季這一比例為 71%，上一季為 72%。我們本季的 Atlas 成長令人印象深刻，這部分得益於我們在上次電話會議上提到的 5 月份消費的強勁開局以及廣泛的強勁表現，尤其是美國較大客戶的強勁表現。

Let me provide some context on Atlas consumption in the quarter. In Q2, Atlas consumption growth was strong and relatively consistent with last year's growth rates. This drove the acceleration in revenue as well as the growth in absolute revenue dollars year-to-date for the first half of fiscal '26.

讓我提供一些有關本季度 Atlas 消費的背景資訊。第二季度，Atlas消費成長強勁，與去年的成長率相對一致。這推動了 26 財年上半年收入的成長以及年初至今絕對收入的成長。

Turning to non-Atlas. Revenue came in ahead of our expectations in the quarter as we continue to have success selling incremental workloads into our existing EA customer base. Non-Atlas ARR which reflects the underlying revenue growth of this product line without the impact of changes in duration grew 7% year-over-year.

轉向非 Atlas。由於我們繼續成功地向現有的 EA 客戶群銷售增量工作負載，本季的收入超出了我們的預期。非 Atlas ARR 反映了該產品線的基本收入成長，不受期限變化的影響，比去年同期成長 7%。

In addition to the good underlying trends at non-Atlas, in Q2, we also benefited from more multiyear deals than expected, reflecting our customers' desire to commit the building with MongoDB long term. Approximately half of the non-Atlas revenue outperformance versus guidance was attributable to multiyear outperformance.

除了非 Atlas 領域的良好基本趨勢外，在第二季度，我們還受益於比預期更多的多年期交易，這反映了我們的客戶希望長期與 MongoDB 合作。非 Atlas 類收入超出預期的約一半可歸因於多年的優異表現。

We had another strong quarter for customer adds in the second quarter as we grew our customer base by approximately 2,800 sequentially, bringing the total customer count to 59,900, which is up from over 50,700 in the year ago period.

我們在第二季度再次實現了強勁的客戶成長，客戶群環比增長了約 2,800 人，總客戶數量達到 59,900 人，高於去年同期的 50,700 人。

This quarter, we incorporated new customers added from the Voyage AI acquisition to our customer count, representing 300 of the 2,800 added. The growth in our total customer count is being driven primarily by Atlas, which had over 58,300 customers at the end of the quarter compared to over 49,200 in the year ago period. It is important to keep in mind the growth in our Atlas customer count reflects new customers to MongoDB in addition to existing EA customers deploying workloads on Atlas for the first time.

本季度，我們將收購 Voyage AI 所增加的新客戶納入我們的客戶數量，佔新增客戶總數 2,800 名中的 300 名。我們客戶總數的成長主要得益於 Atlas，本季末有超過 58,300 名客戶，而去年同期的客戶數量超過 49,200 名。重要的是要記住，Atlas 客戶數量的成長反映了 MongoDB 的新客戶，以及首次在 Atlas 上部署工作負載的現有 EA 客戶。

Of our total customer count, over 7,300 are direct sales customers, a decline of 200 customers sequentially and flat year-over-year. These metrics are largely due to our decision to reallocate a portion of our go-to-market resources from the mid-market to the enterprise channel, starting in the second half of last year.

在我們的總客戶數中，超過 7,300 名是直銷客戶，比上一季減少了 200 名，與去年同期持平。這些指標很大程度是由於我們決定從去年下半年開始將部分市場資源從中端市場重新分配到企業通路。

This does not impact our total customer count, but as an output of fewer self-serve originated customers being elevated to our direct sales team as we move upmarket. In Q2, our total company net ARR expansion rate was approximately 119%, which is consistent with recent quarters. We ended the quarter with 2,564 customers with at least $100,000 in ARR, representing 17% growth versus the year ago period.

這不會影響我們的總客戶數量，但隨著我們向高端市場邁進，越來越少的自助服務客戶被提升到我們的直銷團隊。第二季度，我們公司整體淨 ARR 擴張率約為 119%，與最近幾季一致。本季結束時，我們擁有 2,564 名 ARR 至少為 10 萬美元的客戶，比去年同期成長了 17%。

Moving down the income statement, gross profit in the second quarter was $436 million, representing a gross margin of 74%, which is down from 75% in the year ago period. Our year-over-year gross margin decline is primarily driven by Atlas growing as a percent of the overall business.

損益表中，第二季毛利為 4.36 億美元，毛利率為 74%，低於去年同期的 75%。我們的毛利率年減主要是因為 Atlas 在整體業務中所佔的百分比成長所致。

Our income from operations was $87 million for a 15% operating margin compared to 11% in the year ago period. We are very pleased with our stronger-than-expected margin results, operating margin results which benefited mainly from our revenue outperformance.

我們的營業收入為 8,700 萬美元，營業利潤率為 15%，而去年同期為 11%。我們對高於預期的利潤率結果感到非常滿意，營業利潤率結果主要受益於我們的收入優異表現。

Additionally, I'd like to provide a little context on the modest restructuring we undertook in the quarter. It impacted less than 2% of employees, and resulted in approximately $5 million of one-time charges, which we have excluded from our non-GAAP financials.

此外，我想提供一些有關我們在本季度進行的適度重組的背景資訊。它影響了不到 2% 的員工，並導致了約 500 萬美元的一次性費用，我們已將其排除在非 GAAP 財務報表之外。

This action is consistent with the key priorities I outlined for you last quarter, to identify ways to both reallocate existing spend to higher ROI opportunities and be more disciplined about incremental spending. We are focused on running an efficient scalable business that supports growth in revenue and profitability to drive long-term shareholder value.

這項行動與我上個季度為您概述的關鍵優先事項一致，即找到將現有支出重新分配給更高投資回報率機會的方法，並對增量支出進行更嚴格的約束。我們專注於經營高效可擴展的業務，支持收入和盈利的成長，從而推動長期股東價值。

Net income in the second quarter was $87 million or $1 per share based on 87 million diluted shares outstanding. This compares to a net income of $59 million or $0.70 per share on 84 million diluted shares outstanding in the year ago period.

第二季淨收入為 8,700 萬美元，即每股 1 美元（基於 8,700 萬股稀釋流通股）。相比之下，去年同期的淨利潤為 5,900 萬美元，即每股 0.70 美元，流通股數為 8,400 萬股。

Turning to the balance sheet and cash flow. We ended the second quarter with $2.3 billion in cash, cash equivalents, short-term investments and restricted cash. During the quarter, we spent $200 million to repurchase approximately 930,000 shares, which was under our previously announced $1 billion total share repurchase authorization.

轉向資產負債表和現金流。截至第二季末，我們擁有 23 億美元現金、現金等價物、短期投資和受限現金。本季度，我們花費 2 億美元回購了約 93 萬股股票，這低於我們先前宣布的 10 億美元總股票回購授權。

Operating cash flow was well above our expectations at $72 million, and free cash flow was $70 million, which compares to negative $1 million and negative $4 million respectively, in the year ago period. Our strong cash flow results were driven primarily by strong operating profit and higher cash collections.

經營現金流遠高於我們的預期，達到 7,200 萬美元，自由現金流為 7,000 萬美元，而去年同期的營運現金流和自由現金流分別為負 100 萬美元和負 400 萬美元。我們強勁的現金流結果主要得益於強勁的營業利潤和更高的現金收款。

Before turning to our outlook in greater detail, I'd like to share the key points driving how we are looking at the rest of fiscal year '26. Number one, we are raising our expectations for revenue based on our confidence in Atlas as well as a strong performance in the first half of the year, providing a higher starting point for Atlas heading into the second half.

在更詳細地介紹我們的展望之前，我想分享一下我們對 26 財年剩餘時間的看法的一些關鍵點。第一，基於對Atlas的信心以及上半年的強勁表現，我們提高了營收預期，為Atlas下半年的發展提供了一個更高的起點。

Number two, we are increasing our operating margin guidance by 150 basis points at the high end, reflecting our strong Q2 performance and continued focus on margin improvement. And number three, we are raising our operating margin guidance while still continuing to make incremental investments for growth with a focus on R&D and developer awareness.

第二，我們將營業利潤率預期最高上調了 150 個基點，這反映了我們第二季度的強勁表現以及對利潤率提高的持續關注。第三，我們正在提高營業利潤率預期，同時仍持續增加成長投資，重點是研發和開發人員意識。

Now moving on to our full year guidance. I'd like to provide some incremental comments on our expectations. First, as we discussed, we had a strong start to the year and are confident in our ability to drive continued revenue and profitability growth.

現在開始我們的全年指導。我想對我們的期望提出一些補充性的評論。首先，正如我們所討論的，我們今年開局強勁，並且有信心我們有能力推動持續的收入和獲利成長。

We are raising our full year revenue guidance by $70 million, including the $38 million outperformance in Q2. This reflects -- excuse me, this reflects the strong Q2 consumption benefiting revenue in the second half and our continued confidence in Atlas growth. All in, this implies mid-20s percentage growth for Atlas in the second half of the year.

我們將全年營收預期上調 7,000 萬美元，其中包括第二季超出預期的 3,800 萬美元。這反映出——對不起，這反映出第二季度強勁的消費有利於下半年的收入，以及我們對 Atlas 成長的持續信心。總體而言，這意味著 Atlas 下半年的成長率將達到 25% 左右。

Second, incorporating our strong performance in the first half, we expect non-Atlas subscription revenue will now be down in the mid-single digits for the year compared to our prior expectation of high single-digit decline.

其次，結合我們上半年的強勁表現，我們預計今年非 Atlas 訂閱收入將下降中個位數，而我們先前預期的降幅為高個位數。

We also expect a headwind from multiyear license revenue for fiscal '26 to now be $40 million due to the Q2 outperformance compared to our prior expectation of approximately $50 million. Please note, we expect non-Atlas ARR will continue to grow year-over-year.

我們也預計，由於第二季的表現優於我們先前預期的約 5,000 萬美元，26 財年的多年授權收入將面臨阻力，目前為 4,000 萬美元。請注意，我們預計非 Atlas ARR 將繼續逐年成長。

Finally, we are raising our expectations for operating margin to 14% at the high end, up from 12.5% in our prior quarter guidance. This reflects the better-than-expected revenue performance, the impact of our more disciplined approach to investing for growth and our increased focus on efficiency.

最後，我們將營業利潤率預期從上一季的 12.5% 上調至最高 14%。這反映了好於預期的收入表現、我們更嚴謹的成長投資方式的影響以及我們對效率的更多關注。

For fiscal year '26, we now expect revenue to be in the range of $2.34 billion to $2.36 billion, an increase of $70 million from our prior guide. We are raising our non-GAAP income from operations expectations by $44 million, and are now targeting a range of $321 million to $331 million.

對於 26 財年，我們目前預計營收將在 23.4 億美元至 23.6 億美元之間，比我們先前的預測增加 7,000 萬美元。我們將非公認會計準則營業收入預期提高了 4,400 萬美元，目前的目標範圍是 3.21 億美元至 3.31 億美元。

And non-GAAP net income per share to be in the range of $3.64 to $3.73, based on 87.4 million diluted shares outstanding. Note that the non-GAAP net income per share guidance for the third quarter and fiscal year '26 assumes a non-GAAP tax provision of 20%.

基於 8,740 萬股稀釋流通股，非 GAAP 每股淨收益將在 3.64 美元至 3.73 美元之間。請注意，26 財年第三季和每股非公認會計準則淨收入指引假設非公認會計準則稅務準備金為 20%。

Moving on to our Q3 guidance, a few things to keep in mind. First, we expect to see a low 20% year-over-year decline in the non-Atlas business after the strong multiyear outperformance we experienced in Q3 of fiscal year '25. As a reminder, Q3 of last year was our strongest multiyear revenue quarter and is just a portion of the multiyear headwind.

繼續我們的第三季指導，需要記住一些事情。首先，在經歷了 2025 財年第三季的多年強勁表現之後，我們預計非 Atlas 業務的同比下降幅度將達到 20%。提醒一下，去年第三季度是我們多年來收入最高的季度，但這只是多年逆風的一部分。

Second, we expect operating margin will be lower than in Q2, primarily due to the expected sequential decline in non-Atlas revenue, which is very high-margin revenue. In addition, it is also impacted by the timing of operating expenses, specifically R&D hiring and seasonality of our marketing investments.

其次，我們預期營業利潤率將低於第二季度，主要原因是非 Atlas 業務收入（利潤率非常高的收入）預計將季減。此外，它還受到營運費用時間的影響，特別是研發招募和行銷投資的季節性。

With that context, I will now turn to our outlook for the third quarter. For the third quarter, we expect revenue to be in the range of $587 million to $592 million. We expect non-GAAP income from operations to be in the range of $66 million to $70 million, and non-GAAP net income per share to be in the range of $0.76 to $0.79 based on 87.7 million diluted shares outstanding.

基於此背景，我現在將談談我們對第三季的展望。我們預計第三季的營收將在 5.87 億美元至 5.92 億美元之間。我們預計非公認會計準則下的營業收入將在 6,600 萬美元至 7,000 萬美元之間，基於 8,770 萬股稀釋流通股，非公認會計準則下的每股淨收入將在 0.76 美元至 0.79 美元之間。

To summarize, we had a very strong quarter. We are pleased with our ability to drive revenue growth across the business and increase our operating profit expectations. We remain incredibly excited about the opportunity ahead, and we'll continue to invest responsibly to drive long-term shareholder value.

總而言之，我們本季表現非常強勁。我們很高興能夠推動整個業務的收入成長並提高我們的營業利潤預期。我們對未來的機會仍然感到無比興奮，我們將繼續負責任地投資，以推動長期股東價值。

I would also like to take a moment to extend a warm welcome to Jess Lubert, our new Vice President of Investor Relations, who started with us yesterday. Jeff joins us from Juniper Networks, where he led their Investor Relations effort, including, most recently, helping the company navigate the acquisition by Hewlett Packard Enterprise. We're excited to have him on board and eager to see the impact of this work.

我還想藉此機會向昨天加入我們的新投資者關係副總裁 Jess Lubert 表示熱烈的歡迎。Jeff 在加入我們之前曾任職於瞻博網絡，負責該公司的投資者關係工作，包括最近幫助該公司完成被惠普企業收購的任務。我們很高興他能加入我們，並渴望看到這項工作的影響。

Last but not least, we look forward to seeing many of you in a few weeks at our Investor Day. Please reach out to our Investor Relations team at ir@mongodb.com with any questions. With that, we'd like to open it up for questions. Carmen, take it away.

最後但同樣重要的一點是，我們期待幾週後在投資者日上見到你們。如有任何疑問，請聯絡我們的投資者關係團隊 ir@mongodb.com。好了，我們現在可以開始回答問題了。卡門，把它拿走。

(Operator Instructions) Sanjit Singh, Morgan Stanley.

（操作員指示） 摩根士丹利的 Sanjit Singh。

Hi, thank you for taking the question and congrats on a heck of a quarter in Q2. I wanted to dive into some of the drivers into Q2. When I look at the acceleration of Atlas, which has now accelerated for two quarters in a row, and I kind of just look at the sequential dollar adds, I had the up more than $40 million in Q2, which is kind of the strongest sequential dollar adds we've seen in quite some time in what's been a pretty sober sort of cloud spending environment.

您好，感謝您回答這個問題，並祝賀您第二季度取得了出色的成績。我想深入了解 Q2 的一些驅動因素。當我看到 Atlas 的加速成長時（它已經連續兩個季度加速），我只是看一下連續的美元增長，我發現第二季度的美元增長超過 4000 萬美元，這是我們在相當冷靜的雲支出環境下相當長一段時間以來看到的最強勁的連續美元增長。

So I was wondering if you could give us some sense of the drivers of the strong sequential adds this quarter, I pointed to May. But if anything you can give us from like a workload perspective or any other new factors, maybe the workloads from last year starting to ramp? I just like to understand that trajectory a little bit better.

所以我想知道您是否可以讓我們了解本季強勁連續成長的驅動因素，我指的是五月。但是，如果您能從工作量角度或任何其他新因素給我們任何信息，也許是去年的工作量開始增加？我只是想更好地理解那條軌跡。

Yeah, Sanjit, thank you, thanks for the question. So clearly, we're really pleased by the quarter and really pleased by the accelerating growth in Atlas. I would say a lot of it was due to the workloads that we acquired over the past year, especially with our move up market that are growing faster and becoming bigger than previous workloads we've seen. So I think the move-up market is really paying off.

是的，Sanjit，謝謝你，謝謝你的提問。顯然，我們對本季的表現感到非常滿意，對 Atlas 的加速成長也感到非常高興。我想說，這在很大程度上是由於我們在過去一年中獲得的工作量，特別是我們的向上移動市場，其成長速度比我們以前見過的工作量更快、更大。所以我認為升級市場確實正在獲得回報。

And what we're also seeing is that there's a great uptick of some of the other capabilities we offer, like search and Vector Search that are also adding to that growth of those workloads. And then as we mentioned, we also acquired a ton of new customers obviously, the self-serve customers tend to spend less on a per customer basis, but we obviously have added lots of customers over the last six months. And I think that's also helping drive some of the growth.

我們也看到，我們提供的一些其他功能也有了很大的成長，例如搜尋和向量搜索，這些功能也增加了這些工作負載的成長。正如我們所提到的，我們也顯然獲得了大量新客戶，自助服務客戶的平均每位客戶花費較少，但在過去六個月中我們顯然增加了很多客戶。我認為這也有助於推動部分成長。

Yeah, that's great color. I wanted to follow up on the go-to-market side. Over the last couple of years, you've been sort of tinkering and optimizing the go-to-market organization across sort of territory investment, but also sort of quotas and moving to incremental consumption.

是的，顏色很棒。我想跟進行銷方面的情況。在過去的幾年裡，你們一直在調整和優化市場進入組織，包括區域投資、配額和轉向增量消費。

Could you give us an update on the state of operations for the sales force today? And in some sense, if I look at the customer adds, it seems like things are humming quite well. But just to understand how -- like what's the state of the organization today that would be really helpful.

您能否向我們介紹一下今天銷售團隊的營運狀況？從某種意義上來說，如果我看一下客戶添加的內容，似乎事情進展得相當順利。但只要了解——例如現在組織的狀況如何，這就會非常有幫助。

Yeah, sure. So nothing really has changed. We're just doubling down on what we said previously. We are moving up markets. We're focusing our high-end sales force focus on the most sophisticated and demanding customers.

是的，當然。所以其實什麼都沒有改變。我們只是加倍強調我們之前說過的話。我們正在向高端市場邁進。我們的高端銷售團隊專注於最成熟、要求最高的客戶。

These are typically enterprise customers all around the world. And then we're using our self-serve channel to better serve the SMB market. I know there are a lot of questions about where we're kind of abandoning the self-serve -- the early-stage market by this move. And I think the results over the last couple of quarters have shown that we are not.

這些通常是遍布世界各地的企業客戶。然後，我們使用自助服務管道來更好地服務中小企業市場。我知道有很多人質疑我們這個舉動是否意味著放棄自助服務——早期市場。我認為過去幾個季度的結果表明我們並非如此。

I think we're just becoming much more effective in serving that market while also being very effective in growing our wallet share in these larger accounts. So we're really just continuing with the strategy that we articulated before. And obviously, we're pleased with the results.

我認為我們在服務該市場方面變得更加有效，同時也非常有效地增加我們在這些大帳戶中的錢包份額。所以我們其實只是繼續執行我們之前闡述的策略。顯然，我們對結果很滿意。

Appreciate the thought today. Thank you.

感謝今天的想法。謝謝。

Thank you, Sanjit.

謝謝你，桑吉特。

Raimo Lenschow, Barclays.

巴克萊銀行的 Raimo Lenschow。

Perfect. Thank you. First of all, congrats to Jess. All the best. Two quick questions from me. Staying on that theme of self-service, that acceleration, and Dev, obviously, you changed things around, but it kind of -- it's accelerated despite kind of you actually moving up market. Like can you help us understand that and what's driving that a little bit? And then I had one follow-up for Mike.

完美的。謝謝。首先，祝賀傑西。一切順利。我想問兩個簡單問題。繼續圍繞自助服務、加速和開發這個主題，顯然，你改變了一些事情，但它有點 - 儘管你實際上在向高端市場發展，但它還是加速了。您能幫助我們理解這一點以及是什麼推動了這一點嗎？然後我對麥克進行了一次跟進。

Yeah, I mean, clearly, the output metrics look really good. But I would say the work around self-serve has been going on for a while. The team is really good at running experiments using a data-driven approach to figure out what's working to figure out what's not working.

是的，我的意思是，顯然，輸出指標看起來非常好。但我想說，圍繞自助服務的工作已經進行了一段時間了。該團隊非常擅長使用數據驅動的方法進行實驗，以找出有效方法和無效方法。

A new motion that we're also doing at showing good results as going after SQL developers who don't really know MongoDB and attracting them to our platform, really helping them understand the value proposes of MongoDB, even running like things like office hours where we spend time with SQL developers to explain the benefits of modeling data on a document database.

我們正在進行的一項新舉措也取得了良好的效果，即吸引那些不太了解 MongoDB 的 SQL 開發人員加入我們的平台，真正幫助他們理解 MongoDB 的價值主張，甚至開展辦公時間等活動，我們花時間與 SQL 開發人員一起解釋在文件資料庫上建模資料的好處。

And all these experiments and tactics that we're doing, which are very data-driven, are really paying off. And May Petry used to run that group is now our CMO and she had a strong team under her, and we feel really good about what that sales team has been doing. But again, we don't want to declare victory too early, but obviously, we're very pleased with the results.

我們正在進行的所有這些實驗和策略都是以數據為導向的，並且確實取得了成效。梅·佩特里 (May Petry) 曾經負責管理該團隊，現在是我們的首席行銷官，她手下有一支強大的團隊，我們對該銷售團隊的表現感到非常滿意。但同樣，我們不想過早宣布勝利，但顯然，我們對結果非常滿意。

Yeah, no, that's really nice to see. And then Mike, thanks, first of all, for all the accidents disclosure, the ARR for the non-Atlas or EA part is kind of really helpful. If you think about the -- I get the logic around the renewal cohorts, especially Q3. But am I doing the math correctly, that actually next year, that part of the business looks more interesting because the cohort looks better. Like just trying to get your idea and maybe you might not even give it to us because you just do ARR. Thank you.

是的，不，看到這個真的很高興。然後 Mike，首先感謝你披露的所有事故，非 Atlas 或 EA 部分的 ARR 確實很有幫助。如果你考慮一下──我就會了解續約群體的邏輯，尤其是第三季。但我的計算是否正確？實際上，明年，這部分業務看起來會更有趣，因為群體看起來更好。就像只是想了解你的想法，也許你甚至不會把它告訴我們，因為你只做 ARR。謝謝。

Sure, so thanks for the question. So I'm going to hold that answer until we get to Q3 of next year because it kind of depends on what happens in Q3 of this year. So the one thing is, as we talked about, the big impact in Q3 of this year is the multiyear. We'll see how it comes back next year, but it really depends Raimo on how we do in Q3 this year.

當然，謝謝你的提問。因此我將保留這個答案直到明年第三季度，因為這取決於今年第三季度發生的情況。所以，正如我們所討論的，今年第三季的重大影響是多年期的。我們將看看明年情況如何，但這實際上取決於我們今年第三季的表現。

Yeah, okay, perfect. Thank you, but thanks for the disclosure, really helpful.

是的，好的，完美。謝謝，但感謝您的披露，真的很有幫助。

You're welcome.

不客氣。

Thanks Ramo.

謝謝拉莫。

Tyler Radke, Citi.

花旗銀行的泰勒拉德克（Tyler Radke）。

Hey, thanks for taking the question. And nice job on the Atlas growth. I wanted to dig into the AI commentary that you had, Dev. Obviously, last quarter, you talked about cursor, which obviously is ramping up significantly in terms of their ARR.

嘿，謝謝你回答這個問題。Atlas 的發展做得很好。我想深入了解你的 AI 評論，Dev。顯然，上個季度，您談到了 Cursor，其 ARR 顯然正在大幅成長。

And I think you called out many examples this quarter, including an autonomous vehicle company. It sounds like expecting pretty significant growth there. But how much of that is playing into the Atlas strength that you're seeing here in the quarter?

我認為您在本季度舉了很多例子，包括一家自動駕駛汽車公司。聽起來那裡預計會有相當顯著的成長。但是，其中有多少對您在本季度看到的 Atlas 實力起到了作用？

Any way to quantify that cohort or use cases, whether it's Vector Search or maybe even if you throw in Voyage, just help us understand if that's starting to move the needle because it sounds like there's some pretty high profile wins in there?

有沒有辦法量化該群體或用例，無論是 Vector Search 還是 Voyage，都可以幫助我們了解這是否開始產生影響，因為這聽起來像是其中有一些相當引人注目的勝利？

Yeah, so thanks for the question, Tyler. While we're adding thousands of AI native customers, I will tell you that the growth that we delivered this quarter was not material to that growth. Growth is really driven by our core business and our core customer base. And so -- and while we're very happy with the AI customers increasingly choosing MongoDB, it was not a material mover of the needle for our growth.

是的，謝謝你的提問，泰勒。雖然我們增加了數千名 AI 原生客戶，但我要告訴您，本季我們實現的成長對於該成長並不重要。成長的真正動力是我們的核心業務和核心客戶群。因此——雖然我們很高興看到越來越多的 AI 客戶選擇 MongoDB，但這並沒有為我們的成長帶來實質的推動作用。

Great. And then a follow-up on the migration opportunity. I know you've been investing in relational migrator. You're working with companies like Cognition to accelerate the code migration opportunity. And you've seen professional services ramp up a little bit.

偉大的。然後跟進遷移機會。我知道您一直在投資關係遷移器。您正在與 Cognition 等公司合作，以加速程式碼遷移機會。你已經看到專業服務逐漸增加。

But where have you started to see sort of the time to migration or replatform improve a bit? Just anything you could share in terms of that migration opportunity if that's started to improve in terms of velocity or size of workload ratio would be helpful. Thank you.

但是您從哪裡開始看到遷移或重新平台的時間有所改善呢？如果遷移機會在速度或工作負載比例方面開始改善，那麼您分享的任何資訊都將很有幫助。謝謝。

Yeah, sure. So yes, we're super excited about what we call app modernization or legacy app modernization. You'll hear a lot more about this at Investor Day in September, Tyler. But what I will say is that the value proposition is very clear. Customers are very, very motivated to try and modernize these legacy systems for a wide variety of reasons.

是的，當然。是的，我們對所謂的應用程式現代化或遺留應用程式現代化感到非常興奮。泰勒，您將在九月份的投資者日聽到更多有關此內容的消息。但我要說的是，價值主張非常明確。出於各種各樣的原因，客戶非常積極地嘗試對這些遺留系統進行現代化改造。

We are seeing a lot of progress. We've actually brought in a new leader, new product leader, who brings a lot of depth and scale, especially around AI to help us build the tooling to leverage AI to really drive more automation in terms of how we analyze and refactor the code.

我們看到了很多進步。我們實際上引進了一位新的領導者、新的產品領導者，他帶來了許多深度和規模，特別是在人工智慧方面，他幫助我們建立工具來利用人工智慧真正推動我們在分析和重構程式碼方面實現更多的自動化。

We brought in a new leader last quarter to really help drive the delivery and the go-to-market efforts around app mod. So we're definitely beating up resources. And I would say that we're investing a lot in product and there's a lot more to do.

上個季度，我們引入了一位新領導，真正幫助推動應用程式修改的交付和上市工作。所以我們肯定會浪費資源。我想說我們在產品上投入了大量資金，還有很多工作要做。

And I would say, this is something that we're very excited about, but it will drive more of our longer-term growth less -- it won't be as pronounced in terms of this year, but we're very, very excited about the opportunity, and we're definitely -- we'll spend more time discussing this and what we're actually doing on the product side in September.

我想說，這是我們非常興奮的事情，但它將推動我們更多的長期成長——就今年而言不會那麼明顯，但我們對這個機會感到非常非常興奮，我們肯定會——我們將在 9 月份花更多時間討論這個問題以及我們在產品方面實際做的事情。

Thank you.

謝謝。

Jason Ader, William Blair.

傑森·阿德、威廉·布萊爾。

Yeah, thank you. Dev, I was hoping you could talk about some of the kind of latest industry developments just on the technology side, in particular, I'm thinking about Lake base from Databricks and DocumentDB in the Linux Foundation. Can you just comment on both those things? And how they might impact MongoDB and how you differentiate?

是的，謝謝。Dev，我希望您能談談技術方面的一些最新行業發展，特別是我正在考慮 Databricks 的 Lake 基礎和 Linux 基金會的 DocumentDB。您能對這兩件事發表評論嗎？它們會對 MongoDB 產生什麼影響以及您如何區分？

Yeah, so let me tackle them one by one. Clearly, what we are seeing is that the strategic high ground for AI, especially when it comes to inferences OLTP. So we talked about this on the last call where some companies that acquired early-stage OLTP start-ups. And what I really spoke to when those companies had spoken about their organic efforts to build an OLTP platform.

是的，讓我一一解決它們。顯然，我們看到的是人工智慧的戰略制高點，特別是在推理 OLTP 方面。我們在上次電話會議上討論過這個問題，當時一些公司收購了早期的 OLTP 新創公司。當這些公司談到建立 OLTP 平台的有機努力時，我真正談論的是。

And I think what I spoke to was the fact that they building an OLTP platform that's ready and mission-critical and enterprise can serve the most demanding requirements of enterprises is not trivial. And I think they basically throw in the towel and decided to do these acquisitions.

我認為我所說的事實是，他們建立一個隨時可用、任務關鍵型且能夠滿足企業最苛刻要求的 OLTP 平台並非易事。我認為他們基本上是放棄了並決定進行這些收購。

And what it just reinforces that OLTP is the strategic high ground for AI, and we believe that if now customers are going to be using what OLTP platform that they want for AI, just given our architecture, just given the fact that we have a durable architectural advantage in terms of JSON support, which addresses messy complicated and highly interdependent and constantly changing data structures. The fact that we integrated search and Vector Search, I think, really helps us position going after AI.

這進一步證明 OLTP 是 AI 的戰略制高點，我們相信，如果現在客戶要使用他們想要的 OLTP 平台用於 AI，那麼只要考慮到我們的架構，只要考慮到我們在 JSON 支援方面擁有持久的架構優勢，就可以解決混亂、複雜、高度相互依賴且不斷變化的資料結構。我認為，我們將搜尋和向量搜尋結合起來，確實有助於我們在人工智慧領域的定位。

With regards to your second question around the Linux Foundation, I think what this really also shows is that real JSON is much more important now with AI than ever before. and the clones and bolt-ons that have traded off features and performance and developer experience have just not met customer expectations.

關於您關於 Linux 基金會的第二個問題，我認為這也表明，真正的 JSON 對於人工智慧來說比以往任何時候都更加重要。而那些以功能、效能和開發人員體驗為代價的複製和附加元件根本無法滿足客戶的期望。

And candidly, what I see this is that the hyperscalers are investing less and really handing off to the open source community to kind of really take on the bulk of the work in terms of product development. Our hyperscaler partnerships remain strong. And I think we have the right open source model where we can balance the access to free software while preserving the ability to both generate and capture value.

坦白說，我看到的是，超大規模企業的投資越來越少，實際上將產品開發的大部分工作交給了開源社群。我們與超大規模廠商的合作關係依然強勁。我認為我們擁有正確的開源模型，我們可以平衡對免費軟體的訪問，同時保留創造和獲取價值的能力。

Great. Thank you. And then just one quick follow-up. Why don't we hear so much about Postgres adoption for AI start-ups. You talked about the success you guys are having. But if Postgres has the disadvantages that you've talked about multiple times, scalability, JSON support, how come we hear so much about that, kind of at least from the early stages of AI?

偉大的。謝謝。然後只需快速跟進一次。為什麼我們沒有聽到太多關於人工智慧新創公司採用 Postgres 的消息？您談到了你們所取得的成功。但是，如果 Postgres 具有您多次提到的缺點，即可擴展性、JSON 支持，那麼我們怎麼會聽到這麼多關於這些方面的信息，至少在 AI 的早期階段是這樣？

Yeah, that's a really good question. And I think it's important to understand, and we spend a lot of time -- we have now invested in the team in the Bay Area that spends a lot of time with the startup community. What's become clear, there's a lot of these startup founders don't think that hard about their database choice. They kind of go with what they know.

是的，這是一個非常好的問題。我認為理解這一點很重要，我們花了很多時間——我們現在已經投資了灣區的團隊，他們花了很多時間與新創公司社群打交道。顯而易見的是，許多新創公司的創辦人並沒有認真考慮資料庫的選擇。他們按照自己所知的方式去做。

And what we are seeing is that as some of these startups are scaling, they're running to real scaling challenges with Postgres. And what -- and we've talked about this in the past, like when you add -- when you use JSON B on Postgres, a 2 kilobyte document or bigger starts really creating performance problems because Postgres has to do something called off-road storage, which creates enormous performance overheads.

我們看到的是，隨著一些新創公司的擴張，他們面臨 Postgres 真正的擴張挑戰。而且 — — 我們過去曾討論過這個問題，例如當您添加 — — 當您在 Postgres 上使用 JSON B 時，2 KB 或更大的文檔開始真正產生性能問題，因為 Postgres 必須執行稱為越野存儲的操作，這會產生巨大的性能開銷。

And so the developers need a platform that can handle structured, semi-structured and unstructured data, they need obviously a platform that performs well, and they need a platform that can scale as they grow. And what we're hearing clearly from the startup communities that Postgres, in many cases, is not scaling for them, and they're now coming to us.

因此，開發人員需要一個能夠處理結構化、半結構化和非結構化資料的平台，他們顯然需要一個效能良好的平台，並且他們需要一個能夠隨著他們的成長而擴展的平台。我們從新創企業社群清楚地聽到，在很多情況下，Postgres 無法為他們擴展，所以他們現在轉向我們。

And so we feel really good about our position. But the reality is that a lot of these AI founders kind of start what they know or what they've used in the past and only when the business startups scaling to this start recognizing the challenges. And we realize we need to do more developer education and do more work.

因此，我們對自己的地位感到非常滿意。但現實情況是，許多人工智慧創辦人只是從他們所了解的或過去使用過的東西開始，只有當新創公司擴展到這個領域時，他們才開始意識到挑戰。我們意識到我們需要對開發人員進行更多的教育並做更多的工作。

And so we're investing a lot in the startup community. We're running a big event in October in San Francisco with a big Hackathon and we're inviting a lot of customers to participate. But that's just the start of a meaningful investment we're making in the Bay Area and the AI startup community to rethink their decisions. I'm just going with what they know.

因此，我們在創業社群投入了大量資金。我們將於十月在舊金山舉辦一場大型活動，其中包括一場大型黑客馬拉松，我們邀請了許多客戶參加。但這只是我們在灣區和人工智慧新創企業社區進行的一項有意義的投資的開始，以重新考慮他們的決策。我只是按照他們所知道的方式去做。

Thank you.

謝謝。

Mike Cikos, Needham.

麥克·西科斯，尼德姆。

Hey, thanks for taking the questions, guys. I just wanted to come back to Atlas specifically. And Mike, I appreciate last quarter, you gave us some very granular color around Atlas trends. Was hoping we could get an update on how that was trends played out this quarter? Or just at the very least why we did see such broad-based strength from large customers this quarter? Thank you.

嘿，謝謝大家回答問題。我只是想特別回到 Atlas。麥克，我很欣賞上個季度你為我們提供有關 Atlas 趨勢的一些非常詳細的資訊。我們是否希望能夠了解本季趨勢的最新情況？或者至少為什麼我們本季看到大客戶表現如此廣泛強勁？謝謝。

Sure. Thanks for the question, Mike. So when we talk about consumption in the second quarter for Atlas, as we talked about, it perform well grew 29% year-over-year. As we talked about, Mike, the consumption growth were relatively consistent with last year.

當然。謝謝你的提問，麥克。因此，當我們談論 Atlas 第二季度的消費時，正如我們所討論的，它表現良好，比去年同期增長了 29%。正如我們所討論的，麥克，消費成長與去年相對一致。

And as we talked about on the last call, we started out with a strong May, and we saw a broad-based strength across most of the geos and segments, so nothing to call out there. But we did see notable strength in the larger customers in the US.

正如我們在上次電話會議上所討論的那樣，5 月份我們的業績表現強勁，而且我們看到大多數地區和細分市場都呈現普遍強勁勢頭，因此沒有什麼可說的。但我們確實看到美國大客戶展現出顯著的實力。

And if we dive deeper on that one, as Dev talked about, we are seeing some workloads from our larger customers grow for longer and expand more than we have seen in the past, so that's good. While there's many moving parts in the consumption business, we also expect that there is benefit from our go-to-market changes and given the preponderance of our strategic accounts being in the US.

如果我們深入研究這一點，正如 Dev 所說的那樣，我們會發現來自一些較大客戶的工作負載增長的時間更長，擴展的幅度也比過去更大，所以這是件好事。雖然消費業務中有很多活動部件，但考慮到我們的策略客戶主要在美國，我們也預期我們的市場進入變化將帶來好處。

No surprise that we saw that growth mostly in the US. And then lastly, Mike, there is some benefit from comparing it to a little slower growth in Q1. So that would be the detail on Q2 as it relates to consumption growth.

毫不奇怪，我們看到這種成長主要發生在美國。最後，麥克，與第一季略慢的成長相比，這還是有好處的。這就是第二季與消費成長相關的細節。

Thank you for that. And if I could just squeeze maybe one more in. On the outperformance that we saw this quarter for the multiyear deals. And maybe I'm just misunderstanding here, but -- my assumption was the reason we were facing this outperformance was really tied to the fact that in prior years, we've had some pretty big deals on the multiyear front.

謝謝你。如果我能再擠進一個就好了。我們在本季度看到了多年期交易的出色表現。也許我只是誤解了，但是——我的假設是，我們面臨這種優異表現的原因實際上與前幾年我們在多年期方面進行了一些相當大的交易有關。

And so to see some of these deals come in this year, is that a function of customers renewing earlier, which is helping fill that larger divot that we previously expected. Is that a fair assumption? Or can you help me think through that a little bit more? Thank you.

因此，今年出現的一些交易是客戶提前續約的結果，這有助於填補我們先前預期的更大空白。這是一個合理的假設嗎？或是您能幫我再仔細想想嗎？謝謝。

So thanks for the golf analogy. No, it did not fill the divot. So in Q2, it was really -- it was good underlying strength in ARR growth and then greater-than-expected multiyear. There were really no pull forward, Mike. And this is a hard business to forecast because sometimes even customers don't know whether they're going to opt for an annual renewal or a multiyear.

謝謝你用高爾夫來做比喻。不，它沒有填補草皮凹痕。因此，在第二季度，ARR 成長確實具有良好的潛在實力，且多年成長均超乎預期。真的沒有什麼進步，麥克。這是一個很難預測的業務，因為有時甚至客戶都不知道他們是選擇年度續約還是多年續約。

So it was -- there was no pull forwards and there was nothing out of the ordinary. Very importantly, we left the non-Atlas assumptions consistent with our last guidance. Hence, pulling down the multiyear headwind from [$50 million] to [$40 million]. And again, nothing to call out on Q2, no pull forwards and there were really no large multiyears in there. It was just across a good subset of customers.

事實確實如此——沒有向前拉動，也沒有任何異常。非常重要的是，我們保留了與上一次指導一致的非 Atlas 假設。因此，將多年的逆風從 [5000 萬美元] 降至[4000萬美元]。再說一次，第二季沒有什麼值得關注的，沒有向前推進，而且實際上也沒有什麼大的多年期業績。它只是針對了一小部分客戶。

Thank you again.

再次感謝您。

Yeah.

是的。

Alex Zukin, Wolf Research.

沃爾夫研究公司的亞歷克斯祖金 (Alex Zukin)

Yes, thanks for squeezing me in, and I'll echo the congrats on truly amazing quarter. I guess, Dev, when you think about the AI comments that you've talked about both in the press release and in the call, maybe just a little bit more nuance on the use cases, not necessarily that you're seeing kind of contribute materially today, but the differentiation of the platform that you're able to incrementally take market share as it becomes available, both in net new kind of AI native companies, but also in some of your larger existing companies or customers that are starting to modernize for this kind of conversational or AI-native era.

是的，感謝您抽出時間給我，我會再次祝賀您度過了一個真正令人驚嘆的季度。我想，Dev，當您思考在新聞稿和電話會議中談到的人工智能評論時，也許對用例有一點點細微的差別，不一定是您今天看到的實質性貢獻，而是平台的差異化，隨著平台的推出，您可以逐步佔領市場份額，無論是在全新的人工智能原生公司中，還是在一些較大的現有公司或客戶中，它們都開始為這種現代化或人工智能時代進行這種現代化改造。

Where are you seeing the most momentum in terms of workload construction and scale? And when do you think we should expect to kind of actually start seeing that contribute more materially to the growth in consumption?

在工作負載建置和規模方面，您認為哪個方面發展動能最強？您認為我們什麼時候才能真正開始看到它對消費成長做出更實質的貢獻？

Yeah, so thanks for the question, Alex. A couple of points. Again, we're very pleased with the results of this quarter, but I would say the AI cohort was not a material driver of the growth. That being said, what we are seeing is a lot of customers very, very interested in our architecture.

是的，謝謝你的提問，亞歷克斯。有幾點。再次，我們對本季的業績非常滿意，但我想說人工智慧群體並不是成長的實質驅動力。話雖如此，我們看到很多客戶對我們的架構非常感興趣。

And let me again walk through why. One, we're JSON database. JSON is the best way to express and model the complicated and messy and highly independent and constantly evolving data structures that you have to deal with in the real world. So that's point number one. So it's much easier to do that in MongoDB than to do that on some clue kind of set up on top of a relational database.

讓我再解釋一下原因。首先，我們是 JSON 資料庫。JSON 是表達和建模現實世界中必須處理的複雜、混亂、高度獨立且不斷發展的資料結構的最佳方式。這是第一點。因此，在 MongoDB 中執行此操作比在關聯式資料庫之上設定的某種線索上執行此操作要容易得多。

Second is that we integrate search and Vector Search. So you can do very sophisticated things to what people call hybrid search and retrieval, you can do very sophisticated things and finding information quickly, which is a very unique differentiator for us. So what this means that rather than stitching together multiple systems, you can do this all on MongoDB, so it becomes less complexity and lower cost.

第二，我們把搜尋和向量搜尋結合起來。因此，您可以對人們所說的混合搜尋和檢索做非常複雜的事情，您可以做非常複雜的事情并快速找到信息，這對我們來說是一個非常獨特的區別。這意味著您無需將多個系統拼接在一起，而是可以在 MongoDB 上完成所有操作，從而降低複雜性和成本。

The third thing is that we've now embedded voyage models on our platform, right? So the -- if you control the embedding layer, you sit at the gateway of meeting of AI, right? What the embedding models do is really our bridge between a company's private data and the LLM.

第三件事是，我們現在已經在平台上嵌入了航行模型，對嗎？所以——如果你控制了嵌入層，你就處於 AI 會議的門戶，對嗎？嵌入模型其實就是在公司私​​人資料和 LLM 之間架起一座橋樑。

So that becomes really important because the better the quality of the embedding model, the better the quality of the signal of your own data. So that reduces things like hallucinations or just bad outputs. And so customers are now as people start caring more and more about like higher state use cases, they really want to ensure those outputs are high.

這變得非常重要，因為嵌入模型的品質越好，您自己資料的訊號品質就越好。這樣就可以減少幻覺或不良輸出等現象。因此，隨著人們開始越來越關注更高狀態的用例，客戶確實希望確保這些產出很高。

And the fact that it's part of our platform, we can enable you to do auto embeddings. It becomes an incredibly compelling feature. In terms of the market, what I would say is that the enterprise uptake of AI is still early.

事實上，它是我們平台的一部分，我們可以讓您進行自動嵌入。它成為一個令人難以置信的引人注目的功能。就市場而言，我想說的是企業對人工智慧的採用仍處於早期階段。

I've said this for a couple of years now, and I think a lot of people were a little skeptical of what I said, but it's proving to be true. As you predicted, like the lack of skills and the lack of trust with AI systems is kind of slowing -- people have been very cautious about deploying AI.

我已經說了幾年了，我想很多人對我所說的話有點懷疑，但事實證明這是真的。正如您所預測的那樣，技能的缺乏和對人工智慧系統的信任正在逐漸減弱——人們對部署人工智慧一直非常謹慎。

Where it is being deployed is really on end user productivity, whether it's developers with cogen tools or business users using tools to summarize documents extract data or things like deflecting tickets from people to systems with like conversational AI.

它的部署實際上是為了提高最終用戶的生產力，無論是使用 cogen 工具的開發人員，還是使用工具來總結文件、提取資料的業務用戶，或者將票據從人員轉移到具有對話式 AI 的系統等。

I think you are starting to see the first steps in people deploying agent-based systems, and I can talk a little bit about that, but that's still very, very early. We're seeing small ISVs, some of them are taking off, we are really driving most of the impact.

我認為您已經開始看到人們部署基於代理的系統的第一步，我可以稍微談一下這一點，但這還為時過早。我們看到了小型 ISV，其中一些正在起飛，我們確實在推動大部分影響。

But the real enduring value will come. When you talk to a customer today, most of them when you ask them is really an we're seeing some productivity gains here and there, but it's not really transforming that business.

但真正的持久價值終將到來。今天，當你與客戶交談時，大多數人會問他們，我們確實看到了一些生產力的提高，但這並沒有真正改變業務。

I think the real enduring value will come when they build custom AI solutions that can truly transform the business, whether it's to drive new revenue opportunities or dramatically reduce their existing cost structure. But we're really pleased.

我認為，當他們建立能夠真正改變業務的客製化 AI 解決方案時，真正的持久價值就會顯現出來，無論是為了推動新的收入機會還是大幅降低現有的成本結構。但我們真的很高興。

I mentioned this electric car company that's very tech savvy that's using MongoDB, I should mention one of the fastest-growing startups in the Bay Area has that big on MongoDB. DevRev, the company going after the help desk space has built their own Agentic platform of MongoDB. So we feel really good about what to sell potentially the future. But as I said, it was a small part of our growth this quarter.

我提到了這家非常精通技術的電動車公司正在使用 MongoDB，我應該提到灣區發展最快的新創公司之一在 MongoDB 上投入了大量資金。DevRev 是一家專注於幫助台領域的公司，它已經建立了自己的 MongoDB Agentic 平台。因此，我們對未來可能銷售的產品感到非常滿意。但正如我所說，這只是我們本季成長的一小部分。

Very helpful. And then maybe if I could just sneak one in for Mike. You've been kind of saying from, I think, the first day you started about how the margin profile of this business, it's not it's an words and it's clearly coming through in both the growth acceleration, but also the meaningful margin outperformance.

非常有幫助。然後也許我可以偷偷帶一份給麥克。我想，從您上任第一天起，您就一直在談論這項業務的利潤狀況，這不是空談，而是明顯體現在成長加速和利潤率顯著提升上。

As you think about sustaining this kind of accelerating pace and investing in things like the Bay Area startup community, how are you finding that balance and versus or balance that quite frankly, is elusive to a lot of companies that are doing what you guys are doing?

當您考慮維持這種加速發展的速度並投資於灣區初創企業社區等時，您如何找到這種平衡，或者坦率地說，對於許多從事與您相同業務的公司來說，這種平衡是難以實現的？

Well, I think it's the funnest part of my job, quite frankly. So I would give kudos to not only the management team, but everybody at MongoDB to really jump in this. I think that this has been a company-wide effort. And as we look forward and as we talked about, Alex, the number one driver of margin expansion for Mongo is the revenue growth. So those two are directly connected.

嗯，坦白說，我認為這是我工作中最有趣的部分。因此，我不僅要向管理團隊表示敬意，還要向 MongoDB 的每位員工表示敬意，感謝他們真正參與這項事業。我認為這是全公司上下共同努力的成果。正如我們展望未來以及我們談到的，亞歷克斯，Mongo 利潤率擴張的首要驅動力是收入成長。所以這兩者是直接相關的。

It's a great business model, where when we can grow Atlas in the 20% plus range and then keep that ARR or VA in that single digit. It generates a ton of gross profit that funds a lot. And the team has done a really -- has done a great job of making sure that we are investing in growth, that we go back and look at what we're doing, making sure that it's driving growth, if it's not, then we have an open discussion about whether we should reallocate. So I felt good about it when I started, candidly, I feel better about it 90 days later.

這是一個很棒的商業模式，我們可以讓 Atlas 的成長率達到 20% 以上，同時將 ARR 或 VA 保持在個位數。它產生了大量的毛利，為許多企業提供了資金。團隊確實做得非常出色，確保我們投資於成長，回顧並審視我們正在做的事情，確保它能夠推動成長，如果沒有，那麼我們會公開討論是否應該重新分配。所以當我開始時我感覺很好，坦白說，90 天後我感覺更好。

Excellent. Thank you guys. Congrats again.

出色的。謝謝你們。再次恭喜。

Thanks.

謝謝。

Thank you, Alex.

謝謝你，亞歷克斯。

Kash Rangan, Goldman Sachs.

高盛的卡什·蘭根（Kash Rangan）。

It's always tough to go after, Alex, because you have such a good question, but that's not going to stop me. So Dev and Mike, congratulations on the quarter. It's super interesting, you were talking about how some silicon valley AI startup founders don't have time to think about databases, but a good friend Dheeraj seems to have made a wise choice here.

亞歷克斯，因為你提出了這麼好的問題，所以追問起來總是很困難，但這不會阻止我。所以 Dev 和 Mike，恭喜本季取得的成績。這非常有趣，你談到一些矽谷人工智慧新創公司的創始人沒有時間考慮資料庫，但好朋友 Dheeraj 似乎在這裡做出了明智的選擇。

So as you set encampment up in the Bay Area and start to evangelize the need for an Atlas consumption AI savvy database, how do you reconcile the head to the fact that same time enterprise is where you really saw the bread-and-butter value proposition of Mongo resonates.

因此，當您在灣區紮營並開始宣傳 Atlas 消費 AI 智慧資料庫的必要性時，您如何讓頭腦與這樣一個事實相協調：同一時間，企業才是您真正看到 Mongo 的基本價值主張產生共鳴的地方。

So could -- would is happening with DevRev be a leading indication of what's going to happen in the enterprise because we evolve much to your observation, not seen much of a productivity impact in the enterprise because of AI at the business level? And so what could be that unlocks what are folks like Dheeraj doing correctly that is a -- could be a precursor, if it is for what is to come in the enterprise?

那麼，DevRev 發生的事情是否能預示企業將會發生什麼，因為根據您的觀察，我們已經取得了很大進展，但並沒有看到企業生產力因業務層面的人工智慧而受到太大影響？那麼，什麼可以揭示像 Dheeraj 這樣的人在做什麼是正確的，這可能是一個先兆，如果它是企業未來發展的先兆呢？

Yeah. So Kash, thanks for the question. Obviously, I have so much respect for Dheeraj, he built Nutanix into a real great business, and he's going to do the same at DevRev. I will tell you that the AI cohort, as I said earlier, is -- was not really material to our growth. So I think these are all customers kind of earlier in their journey.

是的。Kash，謝謝你的提問。顯然，我非常尊重 Dheeraj，他將 Nutanix 打造成為一家真正偉大的公司，他也將在 DevRev 做同樣的事情。我會告訴你們，正如我之前所說，人工智慧群體對我們的成長並不重要。所以我認為這些都是處於旅程早期階段的客戶。

So what we are seeing, what's driving the growth right now is these large enterprises with workloads that we acquired both last year and this year that are really driving the growth, especially the Atlas growth that we saw this quarter.

因此，我們看到，目前推動成長的是我們去年和今年收購的這些擁有大量工作負載的大型企業，它們真正推動了成長，尤其是我們本季看到的 Atlas 成長。

And what that really confirms is that our move up market made sense. The quality of those workloads, the durability of their growth, they become -- grow for longer and become bigger than what we've seen in the past is really making us feel good about that decision.

這確實證實了我們的市場向上發展是合理的。這些工作負載的品質、它們成長的持久性、它們成長的時間更長、規模比我們過去所見的更大，確實讓我們對這個決定感到滿意。

And to juxtapose that, we also obviously decided to double down and self-serve to better serve the small- and medium-sized business market, and that's also become obviously becoming more and more effective and gets us given the number of customers that we've added over the last six months.

與此形成對比的是，我們顯然還決定加倍投入和自助服務，以更好地服務於中小型企業市場，而且這顯然也變得越來越有效，並且讓我們在過去六個月中增加了客戶數量。

So we feel like those motions are working well in concert together. And we feel like this allows us to be much more efficient about how we go to market. And there's also going to be continuing more work to continue to drive that efficiency even better, but we also are investing for the long term.

所以我們覺得這些動作協同得很好。我們覺得這讓我們能夠更有效率地進入市場。我們也將繼續進行更多工作來進一步提高效率，但我們也正在進行長期投資。

And so we're just constantly debating those decisions internally, but we feel good about what's working. And we feel good that like someone like Dheeraj is betting early on MongoDB because that's a good signal for other founders who are thinking about doing the same.

因此，我們只是不斷地在內部討論這些決定，但我們對有效的方法感到滿意。我們很高興看到像 Dheeraj 這樣的人在早期就押注 MongoDB，因為這對其他考慮做同樣事情的創始人來說是一個好信號。

Awesome, we'll drill into this more in a couple of weeks when we see you in San Francisco.

太棒了，幾週後我們在舊金山見到您時，我們會更深入地探討這個問題。

Absolutely.

絕對地。

Brad Reback, Stifel.

布拉德·雷巴克（Brad Reback），Stifel。

Great, thanks very much. The 7% EA ARR growth seems fine. I'm assuming you're not satisfied with single-digit growth there. Dev, any sense of where we should think about that longer term? Thanks.

太好了，非常感謝。7% 的 EA ARR 成長看起來不錯。我猜你對個位數的成長不會滿意。Dev，對於這一長期問題我們該如何思考，您有什麼看法嗎？謝謝。

Clearly, EA is a large enterprise motion. And what we've seen is that it's typically less new customers A and it's more of our existing customer base who have a mix of in and sometimes they and then also start deploying Atlas.

顯然，EA 是一項大型企業行動。我們看到的是，通常新客戶較少，而現有客戶群則較多，他們有時也會開始部署 Atlas。

I think one thing that's becoming more and more clear is that customers are becoming much more thoughtful about like how they think about using deployments on-premise versus using the cloud. I think four, five years ago, there's a belief that everything was going to move to the cloud.

我認為越來越清楚的一件事是，客戶開始更認真地考慮如何使用內部部署還是使用雲端。我認為四、五年前，人們相信一切都將轉向雲端。

I think large enterprises become much more sophisticated and nuanced in their thinking, and they believe that some workloads make sense to run on-prem and some workloads make sense to run in the cloud. And I think that's where the MongoDB story becomes really attractive because the same code base can be used.

我認為大型企業的思維變得更加複雜和細緻，他們認為某些工作負載適合在本地運行，而某些工作負載適合在雲端運行。我認為這就是 MongoDB 真正吸引人的地方，因為可以使用相同的程式碼庫。

And so it also gives them optionality for the future where they can move from on-prem to the cloud, and a lot of our EA customers have done that, either with new workloads and some existing workloads, and then they can also move from cloud to cloud. And they can also move back to on-prem if they choose to do so. So that optionality becomes a very powerful value proposition for our customers.

因此，它也為他們提供了未來的選擇，他們可以從本地遷移到雲端，我們的許多 EA 客戶都這樣做了，要么使用新的工作負載，要么使用一些現有的工作負載，然後他們也可以從一個雲端遷移到另一個雲端。如果他們願意的話，他們也可以遷回本地。因此，這種可選性對於我們的客戶來說成為一個非常強大的價值主張。

Great. Thank you very much.

偉大的。非常感謝。

Thank you, Brad.

謝謝你，布拉德。

Ittai Kidron, Oppenheimer.

伊泰·基德倫，奧本海默。

Thanks, great numbers and congrats to Jess and good luck in your new role. Dev, I wanted to dig into the AI opportunity again, but take it from a perspective of a go-to-market motion. Clearly, you can power a lot of AI use kits that are embedded with bigger platforms through a self-serve motion, but it sounds like to really capture the big workload opportunities. It's going to have to be more of an enterprise poor.

謝謝，恭喜傑西取得如此出色的成績，祝你在新崗位上一切順利。Dev，我想再次深入挖掘人工智慧的機會，但從進入市場的角度來考慮。顯然，您可以透過自助服務動作為嵌入更大平台的許多 AI 使用套件提供動力，但這聽起來確實像是在抓住巨大的工作機會。它將不得不更加貧窮。

So I'm kind of wondering how do you think about targeting the AI opportunity from go-to-market motion that doesn't just fall into -- if you're a big enterprise, we're going to send you to an enterprise salesperson and all the risk called or self-serve and do it yourself. Is there something a little bit more, do you think target perhaps that you need to take here in order to capitalize on this opportunity?

所以我想知道您如何看待從進入市場的動作中瞄準人工智慧機會，而不僅僅是 - 如果您是一家大企業，我們會將您發送給企業銷售人員，並將所有風險稱為自助服務並自行完成。還有什麼問題嗎？您認為需要設定哪些目標才能利用這個機會？

Yeah, what I would say, Ittai, is that we've seen this moving before with the cloud, where some early-stage customers are growing very, very quickly, and then we then put dedicated sales focus on those accounts and they grew then even faster.

是的，伊泰，我想說的是，我們之前在雲端運算領域就看到過這種情況，一些早期客戶的成長非常非常快，然後我們將專門的銷售重點放在這些客戶上，他們的成長速度甚至更快。

So we're clearly watching the market. And when self-serve customers are to a point where they really need a higher touch kind of engagement model then we're more than happy to do that. And we have a team that kind of helps transition customers from self-serve to more of a direct sales approach. And that has worked for us.

所以我們顯然在關注市場。當自助服務客戶真正需要更高接觸式的參與模式時，我們非常樂意這樣做。我們有一個團隊，致力於幫助客戶從自助服務轉變為直接銷售方式。這對我們來說是有效的。

I think what we've learned is that line by which we actually engage high-touch model can move higher because we've become so sophisticated with self-serve that we can really serve customers for early-stage customers for a long period of time.

我認為，我們所學到的是，我們實際採用高接觸模式的路線可以更高，因為我們在自助服務方面已經變得非常成熟，我們可以真正為早期客戶提供長期服務。

In terms of the enterprise, what I would say is what I've said earlier is that the enterprise is still quite early in their journey to AI. Most of the investments right now are more on end user productivity like developers using cogen tools, and what I call low stakes use cases.

就企業而言，我想說的就像我之前所說的那樣，企業在人工智慧的道路上還處於相當早期的階段。目前大部分的投資更集中在最終用戶生產力上，例如使用 cogen 工具的開發人員，以及我所說的低風險用例。

In fact, I had two meetings today with two different leaders of two different financial institutions here in New York and they both talked about what they're doing in AI. They both admitted that they've kind of started with low stakes use cases, but their appetite to start doing more is increasing as they get more and more comfortable with the technology and they're quite excited to leverage MongoDB as part of that journey.

事實上，今天我與紐約兩家不同金融機構的兩位領導人舉行了兩次會議，他們都談到了他們在人工智慧領域所做的工作。他們都承認，他們是從低風險用例開始的，但隨著他們對這項技術越來越熟悉，他們開始做更多事情的興趣也越來越大，並且他們非常高興能夠利用 MongoDB 作為這趟旅程的一部分。

But again, I think that's kind of a microcosm into the enterprise market where I think they're still quite early in their AI journey. And if you remember, this is something I've been saying for a while that most customers -- most people overestimate the impact of a new technology like AI in the short term but underestimated in the long term. And I think we're just in that classic journey right now.

但同樣，我認為這是企業市場的縮影，我認為他們在人工智慧之旅中仍處於相當早期的階段。如果你還記得的話，我一直在說的是，大多數客戶——大多數人都高估了人工智慧等新技術在短期內的影響，但低估了其長期影響。我認為我們現在正處於那段經典的旅程中。

I appreciate that. And maybe as a follow-up, Mike, I just want to make sure I dig in a little bit into the non-Atlas business, the EA -- predominantly EA business. Can you tell us roughly what percent of your customers here are multiyear deals versus just annual deals? I'm just kind of curious how -- where we are now? And what was it, say, a year or two ago? And where do you think that mix is going to be a year or two from now?

我很感激。也許作為後續，麥克，我只是想確保我對非 Atlas 業務，即 EA——主要是 EA 業務，有一點了解。您能否告訴我們，你們這裡的客戶中，簽訂多年期合約和簽訂年度合約的大概佔比是多少？我只是有點好奇我們現在在哪裡？那麼，一兩年前的情況又如何呢？您認為一兩年後這種混合會如何發展？

Yeah, thanks for the question. We don't break out the percentage of customers on multiyear versus one year. What I would say is, in fiscal '25, obviously, we saw a lot of larger multiyear deals, and you see that in the numbers. This year, we will always see multiyear deals. They haven't been, I would call it, as large, so it's more widespread.

是的，謝謝你的提問。我們沒有詳細列出多年期客戶和一年期客戶的百分比。我想說的是，在 25 財年，我們顯然看到了很多更大的多年期交易，您可以從數字中看到這一點。今年，我們總是會看到多年期交易。我認為它們的規模還沒有那麼大，因此分佈更為廣泛。

So we -- that's really the change that we've seen. We haven't broken that out. I don't think that it has changed much, especially over the year, as Dev talked about, it's going to be a mix of Atlas and on-prem, and that mix has stayed relatively consistent.

所以——這就是我們真正看到的改變。我們還沒有揭曉這一點。我認為它沒有太大變化，尤其是在過去一年中，正如 Dev 所說的那樣，它將是 Atlas 和本地的混合，而且這種混合保持相對一致。

When you look at the customers that are choosing multiyear deals, has anything changed in the way they think about the reasoning behind doing that versus not?

當您觀察那些選擇多年期交易的客戶時，他們對於選擇或不選擇多年期交易的理由的看法是否發生了變化？

No. Reasons are the same. It's typically their -- if it aligns with their long-term strategy, they want to be able to lock in the pricing. And as everybody knows, hey, data has gravity, moving data around is not fun for everybody so they want to be able to lock in and guarantee their prices for that period of time.

不。原因都是一樣的。通常，如果符合他們的長期策略，他們希望能夠鎖定價格。眾所周知，數據具有引力，行動數據對每個人來說都不是一件有趣的事，所以他們希望能夠在那段時間內鎖定並保證他們的價格。

Appreciate it.

非常感謝。

Ittai, thank you.

伊泰，謝謝你。

Siti Panigrahi, Mizuho.

瑞穗的 Siti Panigrahi。

Thanks for taking my question. And Dev, I think some of the comments you were talking about the AI slowdown, and you heard about recent MIT report about AI implementation not getting any kind of return. How do you see -- what kind of do you think the inflection point when we think we'll start seeing some of the adoption of this AI like you say they are testing, but what can trigger?

感謝您回答我的問題。戴夫，我認為您談到的一些評論是關於人工智慧發展放緩的，而且您也聽說了麻省理工學院最近關於人工智慧實施沒有獲得任何回報的報告。您如何看待——當我們認為我們將開始看到這種人工智慧的採用時，您認為拐點是什麼樣的，就像您說的他們正在測試的那樣，但什麼可以觸發呢？

I know you have been talking about a year ago, probably we are a few years out. But it's good to see some of the traction. So how do you, first of all, what would be your view on that report? And how should we think about in terms of revenue contribution -- material contribution from AI?

我知道您一直在談論一年前的事情，也許我們還要再過幾年。但看到一些進展還是令人欣慰的。那麼首先，您對該報告有何看法？我們該如何看待人工智慧帶來的收入貢獻──物質貢獻？

Yeah. So I think it just comes down to the fundamental principles. I think customers need to feel, one, that the quality of the output of these AI systems is high. Obviously, AI systems are probabilistic in nature, not deterministic in nature. So you can't always guarantee the output.

是的。所以我認為這只是基本原則而已。我認為客戶需要感受到，第一，這些人工智慧系統的輸出品質很高。顯然，人工智慧系統本質上是機率性的，而不是確定性的。所以你不能總是保證輸出。

You can hope that you've trained the models well. You've hoped that you've given it the right information, but you can't always guarantee the output. So as I mentioned, I had meetings with two financial services customers earlier today, and both of them are still hesitant to roll out an end user-facing AI applications for those specific reasons.

您可以希望您已經很好地訓練了模型。您希望您已經向它提供了正確的信息，但您無法始終保證輸出。正如我所提到的，今天早些時候我與兩家金融服務客戶會面，由於這些特定原因，他們都仍不願推出面向最終用戶的人工智慧應用程式。

So it's going to take a little bit of time for people to really get comfortable that they can really deal with the last mile issues and make sure that they don't have any errors that potentially could be impacting their brand or really caused a lot of customer problems. So that's point number one.

因此，人們需要一點時間才能真正適應處理最後一哩路的問題，並確保他們不會出現任何可能影響其品牌或真正導致大量客戶問題的錯誤。這是第一點。

Then there's issues around obviously the security of these systems, the stability and reliability of the systems, the scalability of these systems. As I mentioned, some of these early-stage companies are running into scaling issues with existing architecture, which is why they're coming to us.

那麼顯然存在有關這些系統的安全性、系統的穩定性和可靠性以及系統的可擴展性的問題。正如我所提到的，其中一些早期公司在現有架構的擴展方面遇到了問題，這就是他們來找我們的原因。

So I think we're just in that learning journey. I mean I don't know if there's going to be some massive tipping point. I think what we are seeing with the frontier models is that all these frontier models are kind of clustering around the same ballpark in terms of performance and the efficacy of their models.

所以我認為我們正處於學習的旅程中。我的意思是我不知道是否會出現某個巨大的轉折點。我認為，我們在前沿模型中看到的是，所有這些前沿模型在性能和模型功效方面都聚集在同一個範圍內。

So I think what's going to start happening is how people start leveraging these insights to build what I call scaffolding around these frontier miles to address the needs of their business. Obviously, everyone's talking about agents and people are very, very focused on essentially using agents to drive a lot of work.

所以我認為接下來要發生的事情是人們如何開始利用這些見解來建立我所說的圍繞這些前沿領域的腳手架，以滿足他們的業務需求。顯然，每個人都在談論代理，人們非常非常注重使用代理來推動大量工作。

Agents require -- if you think, agents will use your systems much more intensely than humans will because they can do things much more quickly. So you need platforms that can massively scale up and down, which is, again, a good sign and support indicator for MongoDB.

代理需要－如果你認為的話，代理會比人類更強烈地使用你的系統，因為他們可以更快地完成任務。因此，您需要能夠大規模擴展和縮小的平台，這對 MongoDB 來說又是一個好兆頭和支援指標。

So I think it's going to take a little bit of time. It's going to take time to being comfortable with technology is going to take time where people start with low stakes use cases and start gravitating to higher state use cases. So I don't think there's going to be some seminal inflection point. I think it's just going to take time. But I think that time is coming.

所以我認為這需要一點時間。人們需要時間來適應技術，需要時間從低風險用例開始，然後開始轉向更高狀態的用例。所以我不認為會出現什麼重大的轉捩點。我認為這只不過需要時間。但我認為這個時刻即將到來。

That's a great color, Dev. Thank you.

這顏色真棒，Dev。謝謝。

Thank you.

謝謝。

Brad Sills, Bank of America.

美國銀行的布拉德·西爾斯。

Great, thank you so much. I wanted to ask about some of the investments that you alluded to earlier that you're making in R&D. How are you thinking about that? Is it incremental investments in some of these newer offerings like vector and streaming? Are there other new workloads that you're thinking of addressing here? Would love to get some color on just where you're investing in the stack? Thank you.

太好了，非常感謝。我想詢問一下您之前提到的在研發方面進行的一些投資。您對此有何看法？這是對向量和串流媒體等一些較新產品的增量投資嗎？您是否考慮在這裡解決其他新的工作量？想要了解您在堆疊上投資的具體內容嗎？謝謝。

Yeah, sure. So we talked about the fact that R&D is a big part of our investment focus for this year. One, we came out with 8.0, which is the most performant release ever. So we're already starting to see dividends of our investments in our platform. 8.1 is even better.

是的，當然。因此，我們談到研發是我們今年投資重點的重要組成部分。首先，我們推出了 8.0，這是迄今為止性能最高的版本。因此，我們已經開始看到我們平台投資的紅利。 8.1 甚至更好。

And then we're also making investments in the expansion parts of our platform. What I will say is we're going to go into a lot more detail around this Investor Day. So if you can hold until September 17, we'll go into a lot of things that we're doing on the R&D side as well as what we're doing on application modernization and the tooling that we're building there that will really speak to those investments that we're making, and we'll give you a lot more color.

然後我們也對我們平台的擴展部分進行了投資。我想說的是，我們將在投資者日進行更詳細的討論。因此，如果您能等到 9 月 17 日，我們將詳細介紹我們在研發方面所做的許多工作，以及我們在應用程式現代化方面所做的工作和我們在那裡構建的工具，這些將真正體現我們正在進行的投資，我們將為您提供更多資訊。

Got it. Great, thanks for that, Dev. And one more if I may, please. I know there's been an effort to focus on driving higher quality workloads in that larger account base. I mean, to what extent would you attribute some of this upside to that effort? And maybe just an update on that effort as you may --

知道了。太好了，謝謝你，Dev。如果可以的話，請再說一句。我知道我們一直在努力致力於在更大的客戶群中推動更高品質的工作量。我的意思是，您會在多大程度上將這種好處歸功於這種努力？也許只是對這項努力的更新，正如你可能--

I would assure you be a lot to that effort. I would say a big part of this growth is the fact that we're acquiring higher-quality workloads that are growing faster and for longer than the workloads required, say, in earlier years. And I think that's a big part of why you're seeing this growth happen now.

我向你保證，這項努力將會變得很大成效。我想說，這種成長很大一部分原因是，我們正在獲得更高品質的工作負載，這些工作負載的成長速度比前幾年所需的工作負載更快、持續時間更長。我認為這就是現在看到這種增長的一個重要原因。

Great. Thank you.

偉大的。謝謝。

Carmen, I think we have time for one more question.

卡門，我想我們還有時間再問一個問題。

Rishi Jaluria, RBC.

Rishi Jaluria，RBC。

Wonderful, thanks for squeezing me in at the deadline. I'll keep myself to one question. Dev, really nice to see the early traction with AI native companies. it's always made sense to us, especially given your scalability and your ability to work with unstructured data.

太好了，謝謝你在最後期限前給我時間。我只問一個問題。Dev，很高興看到 AI 原生公司早期的吸引力。這對我們來說總是有意義的，特別是考慮到您的可擴展性和處理非結構化資料的能力。

If we were to fast forward 5, 10 years and we start to see a real paradigm shift where instead of agents built on kind of the traditional mobile interface that we've been in for the past 30 years, we actually entered kind of a multi-agentic world where maybe the interaction vector may move away from what we've been used to in a more natural language.

如果我們快進 5 到 10 年，我們就會開始看到真正的範式轉變，其中不再是過去 30 年來一直使用的傳統移動界面上構建的代理，而是我們實際上進入了一個多代理世界，其中交互向量可能會遠離我們在更自然的語言中習慣的向量。

Can you talk about why MongoDB still has a strong role and some of the investments that you might be making to position yourself well for the world, understanding that's at least several years away? Thanks.

您能否談談為什麼 MongoDB 仍然佔據著強大的地位，以及您可能進行的一些投資，以使自己在世界範圍內佔據有利地位，並且您知道這至少還需要幾年的時間？謝謝。

Yeah, sure. So again, just to make sure we're all talking the same language. We believe that agents essentially do three things. One, they perceive or understand the state of things. So you need essentially a way to understand the state of what's happening in your business, then you need to decide what to do or plan.

是的，當然。所以，再次強調，只是為了確保我們都在說同一種語言。我們認為代理商主要做三件事。一是他們感知或了解事物的狀態。因此，您本質上需要一種方法來了解您的業務狀況，然後您需要決定要做什麼或計劃什麼。

So basically, you have to come up with the plan saying, I want to take this action, these sets of actions. And then you have to act. You actually have to go execute those actions, right? So why is MongoDB good for agents.

所以基本上，你必須制定計劃，說我想採取這個行動，這些行動。然後你就必須採取行動。你實際上必須去執行那些動作，對嗎？那為什麼 MongoDB 對代理商有好處呢？

One, as I said before, the JSON document database is the best of being able to model the real world, the messiness, the complicated nature. The real world does not fit easily in rows and columns. And that's why our document database, I think, is the best way to do that.

第一，正如我之前所說，JSON 文檔資料庫最擅長模擬現實世界的混亂和複雜性。現實世界並不容易用行和列來概括。這就是為什麼我認為我們的文檔資料庫是實現這一目標的最佳方式。

Two, we obviously support search and Vector Search. So you can do very sophisticated hybrid search. So that becomes super important. And then with memory, if agents didn't have memory, they would act like goldfish. They could only react to the last piece of information that they saw.

二，我們顯然支持搜尋和向量搜尋。因此您可以進行非常複雜的混合搜尋。所以這變得非常重要。然後有了記憶，如果代理人沒有記憶，他們就會像金魚一樣表現。他們只能對看到的最後一條訊息做出反應。

So memory lets agents connect the dots across time and situations. So you have different kinds of memory, things like short-term context, past experiences, knowledge, skills, et cetera, they need to build share quickly. You need to be able to orchestrate those agents because you may have multiple agents doing a certain task. You need to register and have govern policies around those agents.

因此，記憶可以讓代理人將不同時間和不同情況的點連結起來。所以你有不同類型的記憶，像是短期背景、過去的經驗、知識、技能等等，它們需要快速建立分享。您需要能夠協調這些代理，因為您可能有多個代理執行某項任務。您需要註冊並制定有關這些代理的管理政策。

We think that the underlying platform needs to be able to support those things while there's a lot more work needs to be done, the underlying architecture that we have in MongoDB is well suited to address those needs. And we think that we'll be positioned to be a winner as people deploy more and more agents in their enterprise.

我們認為底層平台需要能夠支援這些功能，雖然還有很多工作要做，但 MongoDB 中的底層架構非常適合滿足這些需求。我們認為，隨著人們在企業中部署越來越多的代理，我們將成為贏家。

All right, very helpful. Thank you so much.

好的，非常有幫助。太感謝了。

Thank you.

謝謝。

And with that, we conclude the Q&A session, and I will pass it back to Dev Ittycheria for his final comments.

至此，我們的問答環節就結束了，我將把內容交還給 Dev Ittycheria 徵求他的最後評論。

Sure. Thank you again for joining us today. In summary, I think it's clear that we delivered another strong quarter, highlighted by the accelerating Atlas growth, the continued adoption of -- for AI applications and our expanding profitability. We are raising our revenue and operating margin guidance for the full year fiscal year 2026.

當然。再次感謝您今天加入我們。總而言之，我認為很明顯我們又​​度過了一個強勁的季度，突出表現是 Atlas 的加速成長、人工智慧應用的持續採用以及我們盈利能力的不斷提高。我們正在提高 2026 財年全年的營收和營業利潤率預期。

And these results really reinforce that MongoDB is well positioned to capture the next wave of AI application development, while driving durable and efficient growth. So with that, thank you, and we'll talk to you soon. Take care.

這些結果確實證明，MongoDB 已做好準備，抓住下一波人工智慧應用開發的浪潮，同時推動持久高效的成長。所以，謝謝您，我們很快就會再與您聯絡。小心。

Thank you. And this concludes our conference. Thank you for participating, and you may now disconnect.

謝謝。我們的會議到此結束。感謝您的參與，您現在可以斷開連接了。