Financial Data and Key Metrics Changes - Total revenue for the third quarter was $628 million, representing a 19% year-over-year increase and at the high end of guidance [9][19] - Non-GAAP operating income was $123 million, resulting in a 20% operating margin, an improvement from 19% in the previous year [23] - Net income for the quarter was $115 million, or $1.32 per share, compared to $98 million, or $1.16 per share, in the year-ago period [23] Business Line Data and Key Metrics Changes - Atlas revenue grew 30% year-over-year, now accounting for 75% of total revenue, up from 68% in the same quarter last year [19][22] - Non-Atlas revenue grew 8% year-over-year, reflecting consistent trends and expansion within the existing customer base [21] - The total customer count increased to over 62,500, with 2,600 new customers added in the quarter, marking a 65% growth in customer additions year-to-date [9][22] Market Data and Key Metrics Changes - Strong performance in Atlas was driven by large customers in the US and broad-based strength in EMEA [19] - The net annual recurring revenue (ARR) expansion rate increased to 120%, up from 119% in the previous quarter [20] Company Strategy and Development Direction - The company aims to become a foundational data platform for the AI era, leveraging its strengths in operational data and emerging AI workloads [6][10] - There is a focus on deepening customer relationships and advancing innovation to build a generational modern data platform [17] - The company is committed to strategic investments in engineering, marketing, and sales to drive growth [26][31] Management's Comments on Operating Environment and Future Outlook - Management expressed confidence in the continued momentum of Atlas and the strategic importance of the platform for customers [17][26] - The company raised its financial guidance for the fourth quarter and the full fiscal year 2026, reflecting strong performance and underlying fundamentals [17][29] - Management noted that while AI adoption is still early, there are encouraging signs of growth and demand for MongoDB's solutions [10][12] Other Important Information - The company ended the quarter with $2.3 billion in cash and cash equivalents, and operating cash flow was $144 million [24] - The company repurchased approximately 514,000 shares during the quarter under a $1 billion share repurchase authorization [24][28] Q&A Session Summary Question: What are the initial steps to make MongoDB a foundational data platform for the AI era? - Management highlighted the need for real-time operational data and the right context to support AI workloads, emphasizing the company's structural advantages [35][36] Question: How are the workloads for calendar year 2025 shaping up? - Management noted strength in larger customers and ongoing growth in existing workloads, indicating a positive outlook for future workloads [40] Question: What are the repeated themes in customer conversations? - Key themes include modernization efforts and the ongoing transformation to multi-cloud environments, with a focus on AI workloads [45][46] Question: How does the company plan to increase developer engagement? - The company is relaunching initiatives in the Bay Area to engage with AI-native companies and developers, aiming to increase mind share [72] Question: What is the philosophy around M&A for MongoDB? - Management expressed a preference for organic growth but remains open to strategic acquisitions that can accelerate the roadmap [82]

MongoDB (NasdaqGM:MDB) Q3 2026 Earnings Call December 01, 2025 05:00 PM ET Company ParticipantsDev Ittycheria - Board MemberJess Lubert - VP of Investor RelationsSanjit Singh - Executive DirectorMike Berry - CFOCJ Desai - President and CEORaimo Lenschow - Managing DirectorBrad Reback - Managing DirectorMatt Martino - Vice PresidentConference Call ParticipantsKarl Keirstead - Managing Director and Software Equity Research AnalystAlex Zukin - Managing Director and Senior AnalystRyan MacWilliams - Software Equ ...

Financial Data and Key Metrics Changes - Total revenue for Q3 2026 was $628 million, representing a 19% year-over-year increase and at the high end of guidance [7][17] - Non-GAAP operating income was $123 million, resulting in a 20% operating margin, an improvement from 19% in the previous year [20] - Net income for the quarter was $115 million, or $1.32 per share, compared to $98 million, or $1.16 per share, in the year-ago period [20] Business Line Data and Key Metrics Changes - Atlas revenue grew 30% year-over-year, up from 29% in Q2 and 26% in Q1, now representing 75% of total revenue [7][17] - Non-Atlas ARR grew 8% year-over-year, reflecting consistent trends in the non-Atlas business [18] - The total customer count increased to over 62,500, with 2,600 new customers added in the quarter, marking a 65% growth in customer additions year-to-date [7][19] Market Data and Key Metrics Changes - Strong performance was noted in the U.S. and broad-based strength in EMEA, driven by both new workloads and growth of existing workloads [17] - The net ARR expansion rate increased to 120% in Q3, up from 119% in the previous quarter [18] Company Strategy and Development Direction - The company aims to deepen customer relationships and advance its innovation agenda to build a generational modern data platform for the multi-cloud and AI era [15] - The focus is on expanding within existing accounts and penetrating the Fortune 500 market more effectively [78] - Strategic investments in engineering, marketing, and sales capacity are planned to drive continued growth [24] Management's Comments on Operating Environment and Future Outlook - Management expressed confidence in the strong momentum of Atlas and the healthy fundamentals of the business, leading to raised financial guidance for Q4 and the full fiscal year 2026 [15][25] - The company is optimistic about the potential of AI workloads and the role MongoDB can play in supporting enterprises in their AI transformations [11][33] Other Important Information - The company ended the quarter with $2.3 billion in cash and cash equivalents, and operating cash flow was significantly above expectations at $144 million [20][21] - The company is executing a share buyback program to offset dilution from employee equity awards [24] Q&A Session Summary Question: What are the initial steps to make MongoDB a foundational data platform for the AI era? - Management highlighted the need for real-time operational data and the right context to support AI workloads, emphasizing the importance of MongoDB's capabilities in this area [32][34] Question: How are the workloads for calendar year 2025 shaping up? - Management noted strength in larger customers and ongoing growth in existing workloads, indicating a positive trend for future workloads [36][37] Question: What are the repeated themes in customer conversations? - Key themes include modernization efforts and the ongoing transformation to multi-cloud environments, with a focus on AI workloads [40][41] Question: What is driving the new customer strength within Atlas? - The engineering team's successful product launches and the self-serve team's efforts to reduce friction for onboarding new customers were cited as key factors [69][71] Question: How does management view M&A in relation to MongoDB? - Management expressed a preference for organic growth but remains open to strategic acquisitions that can accelerate the roadmap [73]

AI Data Platform - OpenText unveiled its Next-Generation AI Data Platform to interpret, organize, and act on enterprise information at massive scale [1] AI Verification - Verifying how conclusions are derived becomes a core requirement when AI becomes the interface to an organization's source-of-truth data [1]

Industry Focus - Data platforms should prioritize updates to enhance functionality [1] - The update is considered significantly undervalued within the data platform landscape [1]

Collaboration and Technology - Chineka collaborates with DDN for almost 10 years to support large-scale systems like Leonardo and Galileo 100 [1][2] - DDN's platform enables Chineka to process 30% more data, crucial for civil protection scenarios like geological hazards [2] - DDN is synonymous with performance for AI workloads, handling massive data ingestion and processing [5] Project Outcomes and Impact - Projects improve human research in areas from weather prediction to artificial intelligence, nuclear fusion, and astrophysics [1] - Digitalization projects preserve Italian and European history by creating digital twins of historical sites [3] - Data simulation time reduced from 40 minutes to 5 minutes, significantly improving efficiency [4] - Leonardo supported research to find medicine against COVID-19, contributing to the development of a treatment [4] Future Strategy - Chineka is transitioning between High-Performance Computing (HPC) and Artificial Intelligence (AI) ecosystems [5] - Chineka's mandate is to support both HPC and AI ecosystems, requiring systems capable of managing petabyte and exabyte-level data [5] - DDN technology enables Chineka to manage petabyte-scale data now and exabyte-scale data in the future [5]

Investment Rating - The report assigns a "Buy" rating to Snowflake Inc. with a target price of $208.61 [18]. Core Insights - The report emphasizes the central role of platforms like Databricks and Snowflake in enterprise AI transformation, highlighting their rapid innovation and the shift of value from infrastructure to platforms and applications [1][5]. - Databricks' product innovations, including Lakebase, Agent Bricks, and Databricks Apps, are designed to enhance AI adoption and streamline the development of AI-driven applications [1][4]. - The demand for data and analytics solutions remains strong, with enterprises increasingly moving AI workloads into production, indicating a higher maturity in enterprise AI compared to the previous year [6][8]. Summary by Sections Databricks Innovations - Databricks introduced Lakebase, a serverless database designed for AI applications, which offers low-latency performance and autoscaling capabilities [4]. - The company reported that Databricks Apps has become its fastest-growing product, with over 2,500 customers and more than 20,000 applications created since its launch [5][9]. - Agent Bricks provides a framework for building enterprise-grade AI agents, reflecting the growing trend of deploying Agentic AI in enterprises [5][6]. Market Dynamics - Partner feedback indicates a healthy demand environment for data solutions, with enterprises willing to invest in AI technologies [6][8]. - The competitive landscape is evolving, with Snowflake narrowing the gap with Databricks in AI services and features [8]. - Enterprises like JPMorgan are deploying numerous AI use cases, with significant annual spending on AI, reinforcing the sustainability of AI growth [5][6]. Financial Performance - Databricks reported over $2.6 billion in revenue for FY25, representing more than 60% growth, and is targeting a revenue run-rate of $3.7 billion for the upcoming quarter [9]. - The company reached free cash flow breakeven in FY25 and emphasized its commitment to innovation and R&D, with R&D spending at 32% of revenue [9].