MDB

MongoDB, Inc.

AI '25: Phase 2 Deployment BS Jobs '26: Bloated Operations in Tech Software '24: Database Management

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Overview

MongoDB, Inc. provides a flexible database platform for various data types. Its cloud-based Atlas service, comprising approximately 75% of total revenue, helps

MongoDB, Inc. provides a flexible database platform for various data types. Its cloud-based Atlas service, comprising approximately 75% of total revenue, helps developers and enterprises modernize applications and power AI workloads. The company also offers Enterprise Advanced for on-premise or hybrid use, serving a broad customer base including Fortune 500 companies, AI-native organizations, and government entities.

What They Do (Plain English & Analogies): MongoDB provides a modern, general-purpose database platform that acts like a highly flexible digital filing cabinet for all sorts of information, from structured data like customer names to unstructured data like social media posts or sensor readings. Unlike older, rigid filing systems (traditional relational databases) that require data to fit into predefined rows and columns, MongoDB's system is built for diverse and rapidly changing information, which is crucial for today's cloud-based applications and those powered by Artificial Intelligence (AI). Its flagship product, MongoDB Atlas, is a fully managed, 'set it and forget it' version of this filing cabinet in the cloud, automatically scaling to handle growing data needs and accessible from anywhere. It also offers an integrated suite for AI applications, including search, vector search, and embeddings, all within a single intelligent data layer. MongoDB also provides software for companies to manage their own databases (MongoDB Enterprise Advanced) and a free version for developers to get started (Community Server). The company helps customers run their most demanding, mission-critical workloads across on-premise, public clouds, and hybrid environments, and is increasingly chosen as the data platform for agentic AI applications.
Very Brief History: MongoDB was founded in 2007 as 10gen, Inc. by the team behind DoubleClick, aiming to solve scalability issues with traditional databases. The MongoDB database was publicly released in 2009, and the company rebranded to MongoDB, Inc. in 2013, going public on the Nasdaq in 2017. Key product advancements include the WiredTiger storage engine in 2015 and multi-document transactions in 2019. More recently, the company integrated vector search and acquired Voyage AI in February 2025, followed by the acquisition of Clarity Business Solutions in Q1 fiscal year 2027 (May 2026) to strengthen its U.S. federal vertical.
"Street Stereotype": MongoDB is generally perceived as a leading modern database platform, particularly dominant in the NoSQL and cloud database-as-a-service (DBaaS) market with its Atlas offering. The 'street stereotype' is that MDB is a high-growth, cloud-centric company benefiting significantly from ongoing digital transformation and is increasingly positioned as a foundational data platform for the AI era. There's a strong focus on its ability to capture AI-driven workloads and maintain a competitive edge against hyperscalers, though concerns about its premium valuation and potential consumption-based revenue volatility are also present.
Subsidiaries On Linked In*: Clarity Business Solutions — Acquired in Q1 FY27 to strengthen the U.S. federal vertical.; LinkedIn: clarity-business-solutions
Voyage AI — Acquired in February 2025, provides embedding and reranking models for AI applications.; LinkedIn: voyage-ai
Customer Sectors & Example Clients: MongoDB's customers span various sectors including financial services, healthcare, manufacturing, media and entertainment, telecommunications, e-commerce, software and technology, and government organizations. Specific clients mentioned or inferred include Zoom, Endor Labs (an AI-native application security platform), Zomato (a large food delivery company), Adobe, ElevenLabs, and various frontier labs.
New Customers / Segments They'Re Targeting: MongoDB is actively targeting AI-native companies, digital natives, frontier labs, and large enterprises for strategic platform commitments. They are also focusing on expanding their presence in the public sector, particularly strengthening their U.S. federal vertical through the acquisition of Clarity Business Solutions, and building out their presence in Japan. A key emerging segment is customers choosing MongoDB as the memory layer for AI agents themselves.
Supply Chain And Sourcing Geographies: As a software company, MongoDB's primary 'supply chain' is intellectual property, cloud infrastructure, and human capital. The provided transcript and existing text do not contain specific information about physical supply chain or sourcing geographies for products or components.
Sales Geographies And Expansion Plans: MongoDB currently has strong performance in North America, particularly with larger customers. The company is actively expanding its sales presence, with plans to build out its operations in Japan and strengthen its U.S. federal vertical. Management also sees tremendous opportunity in federal business not only in the United States but also in Europe and other places.
How Key Themes May Help/Hurt: The 'AI '25: Phase 2 Deployment' theme significantly helps MongoDB, as its integrated platform with Vector Search, Voyage embeddings, and flexible schema is purpose-built for scalable, cost-efficient, and secure AI deployment. Its role as a long-term memory layer for AI agents and deep integrations with frameworks like LangChain directly support the acceleration of task-specific AI agents into production. The hybrid deployment model (cloud, on-prem, hybrid) aligns with the growing trend of hybrid architectures for AI. The 'BS Jobs '26: Bloated Operations in Tech' theme also benefits MongoDB. Its platform can reduce operational friction and total cost of ownership by simplifying complex data estates and improving resilience, as demonstrated by Zoom. AI-native customer support platforms built on MongoDB, like Zomato's Nugget, can significantly reduce support costs and improve agent productivity, directly addressing bloated operations within enterprises. This modernization opportunity, driven by MongoDB, can lead to more efficient data management and application development.

3 Main Long-Term Bull Details

Generational Data Platform for AI and Multi-Cloud: MongoDB is solidifying its position as the foundational data platform for the AI era and multi-cloud environments. Its flexible document model, integrated vector search, and Voyage AI embeddings are critical for connecting Large Language Models (LLMs) with proprietary, real-time data, driving innovation for both core mission-critical applications and emerging AI workloads.
Strong Core Business & Enterprise Standardization: The core business, particularly Atlas, continues robust growth, driven by ongoing digital transformation and modernization efforts. Large enterprises are increasingly standardizing on MongoDB to power a wide spectrum of workloads, including high-volume transactional systems, real-time applications, and emerging AI workloads. The ability to serve both cloud (Atlas) and on-prem (EA) needs reinforces its strategic importance to large customers.
Developer-Centricity & Innovation: MongoDB's strong focus on developer productivity, ease of use, and continuous innovation (e.g., machine-friendly APIs, auto-scaling, auto-sharding for agents) fosters a loyal and expanding developer community. This developer-led adoption, coupled with a unified platform that simplifies complex architectures, creates high switching costs and significantly expands the company's total addressable market.

3 Main Long-Term Bear Details

Nascent AI Revenue Contribution: Despite its strong strategic positioning for AI, the material financial impact from AI-driven workloads on MongoDB's overall revenue is still in its early stages. Many enterprise AI initiatives are currently in prototyping or pilot phases, and widespread production deployment of AI agents that would significantly boost MongoDB's consumption is 'not yet' happening at scale in large enterprises across most verticals.
Intense Competition & Consumption Volatility: MongoDB faces significant competitive pressure from major cloud providers (AWS, Azure, Google Cloud) that offer their own managed database services, often with deep ecosystem integration. Additionally, entrenched relational database vendors (Oracle, PostgreSQL, MySQL) are continuously evolving. A substantial portion of MongoDB's revenue, particularly from its Atlas cloud offering, is consumption-based, which exposes the company to potential revenue volatility and sensitivity to macroeconomic headwinds, customer optimization efforts, or unpredictable changes in workload patterns.
Go-to-Market Leadership Transition: The company has undergone a significant transition in its go-to-market leadership, with new Chief Customer Officer and Chief Revenue Officer appointments. While management expresses confidence in a seamless transition, such changes can introduce uncertainty and potential disruption to sales execution and partner growth initiatives in the near term.

Competitors And Differentiation: MongoDB competes with major cloud providers offering their own managed database services (like AWS DynamoDB and DocumentDB, Azure, Google Cloud) and entrenched relational database vendors (such as Oracle, PostgreSQL, and MySQL). MongoDB differentiates itself through its flexible document schema, which is uniquely suited for unstructured data and how applications are built in the agentic AI era, as LLMs speak in document-shaped data. It offers a transactional, high-performance data platform built for how AI agents work, providing best-in-class retrieval through integrated Vector Search and Voyage embeddings and reranker models. The platform's ability to run anywhere—across all three major clouds, on-premise, and in hybrid environments—provides flexibility that competitors may lack. Furthermore, MongoDB is embedded in developer tools and agent frameworks like LangChain, with numerous native integrations for AI functionalities.
Recent Performance & What The Market'S Focused On: MongoDB delivered a strong first quarter fiscal year 2027, with total revenue of $688 million, up 25% year-over-year, exceeding the high end of guidance. Atlas revenue grew 29.4% year-over-year, reaching a $2 billion run rate, and now accounts for approximately 75% of total Q1 revenue. EA & other revenue grew 13% year-over-year. The company achieved a non-GAAP operating margin of 18% and ended the quarter with over 67,700 customers, adding 2,500 new customers. The total company net ARR expansion rate was 121%. MongoDB also acquired Clarity Business Solutions to strengthen its U.S. federal vertical. For Q2 FY27, MongoDB expects revenue of $729 million to $734 million (23% to 24% YoY growth) and non-GAAP operating income of $152 million to $156 million (approximately 21% operating margin). For the full fiscal year 2027, revenue is projected to be in the range of $2.92 billion to $2.96 billion (19% to 20% YoY growth), with a non-GAAP operating margin of approximately 20%. The market is currently focused on when AI workloads will genuinely become a material driver for consumption, the predictability and seasonality of Atlas revenue, the contribution from AI-native companies, data consolidation trends, the impact of new go-to-market leadership, and the opportunity within the federal business.

Revenue Segments And Estimated Mix: Atlas — Mix: ~75%; Source: Q1 FY27 earnings transcript; Trend: Grew 29.4% year-over-year, up from 72% in the year-ago quarter.
EA & other (formerly non-Atlas) — Mix: ~25%; Source: Q1 FY27 earnings transcript; Trend: Grew 13% year-over-year.
Product Brands: MongoDB
MongoDB Atlas
MongoDB Enterprise Advanced
Community Server
Voyage AI
Atlas Search
Atlas Vector Search
MongoDB Checkpointer
MongoDB Plugin

Bull / Bear Details

MongoDB solidifies its position as the generational data platform for the multi-cloud and AI era. Strong Q1 FY27 performance, with robust Atlas (29.4% YoY) and

Thesis

MongoDB solidifies its position as the generational data platform for the multi-cloud and AI era. Strong Q1 FY27 performance, with robust Atlas (29.4% YoY) and durable EA growth, coupled with accelerating AI capability adoption, reinforces market leadership. The strategic importance of its integrated AI features and hybrid offerings provides a structural advantage, driving significant expansion opportunities within enterprises and AI-native companies. (Updated: 2026-06-03)

Bull case

MongoDB delivered exceptional Q1 FY27 results, with total revenue up 25% year-over-year, accelerating from prior periods. Atlas revenue grew 29.4% year-over-year, reaching a $2 billion run rate, marking its fourth consecutive quarter of at least 29% growth. This consistent performance, along with a net ARR expansion rate of 121%, demonstrates robust demand and strong execution across its cloud offerings.
AI adoption is accelerating, with Voyage customers more than doubling quarter-over-quarter and Vector Search adoption far outpacing overall company growth. MongoDB's flexible schema and integrated platform, featuring search, vector search, and Voyage AI embeddings, are proving critical for agentic workloads. Competitive wins with AI-native companies like Endor Labs and enterprises like Zomato and Adobe highlight its architectural advantage and growing traction in the AI era.
The renewed importance of on-premises and hybrid deployments, particularly in regulated industries, strengthens MongoDB's strategy. Enterprise Advanced (EA) demonstrated durable 13% year-over-year growth in Q1, with Q2 guidance at 20%. The acquisition of Clarity Business Solutions and upcoming FedRAMP high certification for the U.S. federal vertical further expand its market reach and strategic importance to large customers.

Bear case

Despite accelerating adoption of AI capabilities, management explicitly states that AI is "not yet a material driver" to overall results. Large enterprises are still in early stages of deploying scaled, customer-facing agentic applications, with many initiatives remaining prototypes. The significant financial impact of AI tailwinds on MongoDB's overall revenue remains a near-term uncertainty.
A significant portion of MongoDB's Atlas revenue is consumption-based, leading to potential variability and limited visibility further out in the fiscal year. While EA & other revenue showed strong Q1 performance, the implied flat growth for the second half of FY27 due to tougher comparisons and the inherent difficulty in predicting large multiyear deals introduce potential headwinds and revenue volatility.
MongoDB faces intense competition from major cloud providers and evolving relational databases. While new go-to-market leadership is in place, the ongoing refinement of strategy, particularly for intercepting AI-native companies coming through self-serve, indicates a work in progress. This could introduce execution challenges or impact customer acquisition efficiency in a highly competitive market.

Bull / Bear Case

Bear Case: Despite accelerating AI capability adoption, management explicitly states that AI is "not yet a material driver" to overall results, with large enterprise AI deployments still in early stages, creating near-term revenue uncertainty. [cite: 2026-05-28] A significant portion of Atlas revenue is consumption-based, leading to potential variability and limited visibility further out in the fiscal year. [cite: 2026-05-28] The implied flat growth for Enterprise Advanced (EA) in the second half of FY27 due to tougher comparisons and unpredictable large multiyear deals introduces potential headwinds and revenue volatility. [cite: 2026-05-28] MongoDB faces intense competition from major cloud providers and evolving relational databases, and the ongoing refinement of its go-to-market strategy for AI-native companies indicates a work in progress, potentially impacting customer acquisition efficiency in a highly competitive market. [cite: 2026-05-28]
Bull Case: MongoDB delivered exceptional Q1 FY27 results, with total revenue up 25% year-over-year, accelerating from prior periods. Atlas revenue grew robustly at 29.4% year-over-year, reaching a $2 billion run rate, demonstrating consistent demand and strong execution across its cloud offerings. [cite: 2026-05-28] AI adoption is rapidly accelerating, evidenced by Voyage customers more than doubling and Vector Search adoption far outpacing overall company growth. [cite: 2026-05-28] MongoDB's flexible schema and integrated platform, featuring search, vector search, and Voyage AI embeddings, are proving critical for agentic workloads, securing competitive wins with AI-native companies and large enterprises. [cite: 2026-05-28] The company is strategically expanding its market reach into the U.S. federal vertical and is committed to expanding operating margins by 100-150 basis points in FY27, targeting a Rule of 40 performance. [cite: 2026-05-28]
More Compelling & Why: Bear. MongoDB's current valuation, with a forward Price/Sales ratio likely exceeding 10-12x, appears stretched given management's explicit statement that AI is "not yet a material driver" to overall results. [cite: 2026-05-28] While the long-term AI opportunity is significant, its near-term revenue impact remains uncertain, and the implied flat growth for Enterprise Advanced in H2 FY27 adds variability. [cite: 2026-05-28] The strongest argument for the bear case is the disconnect between a premium valuation, which seems to price in substantial future AI-driven growth, and the current reality of AI's nascent revenue contribution. My view would flip to bullish if MongoDB provides quantitative evidence of AI becoming a material revenue driver (e.g., specific revenue percentage or accelerated guidance directly attributed to AI) that justifies its premium multiple.

Key Factors5 rows

Key Factor	Why It Matters	What To Watch	What It Signals	Where/How To Track	Free Alt Data	Paid Alt Data
Non-GAAP Operating Margin Expansion and Rule of 40 Achievement	Continued expansion of non-GAAP operating margin demonstrates MongoDB's commitment to profitable growth and operational efficiency, which is crucial for long-term shareholder value, especially as the company targets a Rule of 40 performance.	Non-GAAP operating margin percentage for Q2 FY27 (guidance: ~21% at high end). Any updates to the full year FY27 non-GAAP operating margin guidance (100-150 bps expansion, targeting ~20% at high end).	Bullish if Q2 FY27 Non-GAAP Operating Margin exceeds 21%. Bullish if FY27 operating margin guidance is raised above 20%. Bullish if the company consistently achieves or exceeds the Rule of 40 target (20% revenue growth and 20% operating margin). Bearish if Q2 FY27 Non-GAAP Operating Margin is below 21%. Bearish if FY27 operating margin guidance is lowered. Bearish if the Rule of 40 target is missed.	MongoDB's Q2 FY27 earnings release and conference call.	N/A	N/A
Enterprise Advanced (EA) & Other Revenue Growth Rate	EA demonstrates MongoDB's ability to serve regulated industries and hybrid environments, providing a stable revenue stream and expanding its total addressable market, despite its lower growth rate compared to Atlas.	Year-over-year growth rate of EA & other revenue for Q2 FY27 (guidance: ~20%). Any updates to the full year FY27 EA & other revenue growth guidance (mid-single-digit growth, with implied flat H2 FY27). Announcements of new large multiyear EA deals.	Bullish if Q2 FY27 EA & other revenue growth exceeds 20% YoY. Bullish if FY27 EA & other guidance is raised above mid-single digits. Bullish if new large multiyear EA deals are announced that significantly impact future revenue. Bearish if Q2 FY27 EA & other revenue growth is below 20% YoY. Bearish if FY27 EA & other guidance is lowered. Bearish if the implied flat growth for H2 FY27 is worse than expected.	MongoDB's Q2 FY27 earnings release and conference call.	N/A	Thinknum: Enterprise Advanced related job postings by customers
MongoDB Atlas Revenue Growth Rate	Atlas is MongoDB's primary growth engine and central to its AI strategy. Its performance indicates success in cloud adoption and the monetization of AI-related workloads, driving investor confidence.	Year-over-year growth rate of MongoDB Atlas revenue for Q2 FY27. Also, any updates to the full year FY27 Atlas revenue growth guidance.	Bullish if Q2 FY27 Atlas revenue growth exceeds 26% YoY. Bullish if FY27 Atlas guidance is raised above 25% YoY. Bearish if Q2 FY27 Atlas revenue growth is below 26% YoY. Bearish if FY27 Atlas guidance is lowered below 23% YoY.	MongoDB's Q2 FY27 earnings release and conference call (expected in late August/early September 2026).	N/A	Thinknum: MongoDB Atlas customer count growth, MongoDB Atlas job postings
Acceleration of AI Workload Adoption (Voyage, Vector Search, Agentic Apps)	The transition of AI workloads from proof-of-concept to scaled production, driven by integrated AI capabilities like Voyage and Vector Search, is critical for MongoDB to capitalize on the AI era and drive future revenue growth.	Continued growth in Voyage customer additions (doubled QoQ in Q1 FY27), Vector Search adoption (far outpacing overall company growth in Q1 FY27), and new public examples of scaled, customer-facing agentic applications in large enterprises (e.g., Zomato, Adobe). Management commentary on AI's material revenue contribution.	Bullish if Voyage customer additions continue to double QoQ or accelerate. Bullish if Vector Search adoption continues to far outpace overall company growth. Bullish if new Fortune 500 customers announce significant production deployments of AI agents on MongoDB. Bullish if management provides quantitative evidence of AI becoming a material revenue driver (e.g., specific revenue percentage). Bearish if growth rates for Voyage/Vector Search adoption slow significantly. Bearish if management reiterates AI is 'not yet a material driver' without clearer milestones.	MongoDB's earnings releases, conference calls, investor presentations, product announcements, and customer case studies.	Google Trends: 'MongoDB Vector Search', 'MongoDB Voyage AI', 'LangChain MongoDB integration' search volume. Reddit: r/MachineLearning, r/MLOps for discussions on MongoDB in AI stacks.	Thinknum: Job postings mentioning 'MongoDB AI', 'Vector Search', 'LangChain' for enterprise roles
Performance and Stability of New Go-to-Market Leadership	The successful execution by the newly appointed Chief Revenue Officer (Ryan Mac Ban) and Chief Customer Officer (Erica Volini) is crucial for maintaining sales momentum, customer acquisition, and expansion, especially in a consumption-based model.	Management commentary on the effectiveness of the new go-to-market leadership. The total company net ARR expansion rate (121% in Q1 FY27). Any indications of changes in sales execution or strategy.	Bullish if management expresses continued confidence in the new leadership's impact and reports seamless execution. Bullish if the net ARR expansion rate remains strong (above 120%). Bearish if there are signs of sales execution challenges or a decline in the net ARR expansion rate below 120%.	MongoDB's Q2 FY27 earnings release and conference call.	LinkedIn: Public profiles of Ryan Mac Ban and Erica Volini for career updates. Glassdoor/Blind: Employee sentiment reviews for MongoDB.	Thinknum: Sales and customer success job postings growth/decline for MongoDB

Key Reported Metrics3 rows

Metric	Why It Matters	Last Period
EA & other Revenue Growth	This segment, encompassing Enterprise Advanced, demonstrates the company's ability to serve on-prem and hybrid environments, particularly in regulated industries, and its strategic importance to large customers.	13%
Non-GAAP Operating Margin	This metric demonstrates MongoDB's ability to drive profitable growth while strategically investing in AI capabilities and go-to-market expansion. It is key for assessing the company's efficiency and commitment to its long-term financial model.	18%
Atlas Revenue Growth	Atlas is MongoDB's primary growth engine, comprising approximately 75% of total revenue. Its performance indicates success in cloud adoption and the monetization of AI-related workloads, driving investor confidence.	29.4%

Key Questions

Can MongoDB Atlas sustain its accelerated growth trajectory and exceed its raised fiscal year 2027 revenue guidance of 23-25%, demonstrating continued momentum

Can MongoDB Atlas sustain its accelerated growth trajectory and exceed its raised fiscal year 2027 revenue guidance of 23-25%, demonstrating continued momentum despite its larger base and consumption-based variability?

Question 2: Will the accelerating adoption of MongoDB's AI capabilities, including Voyage embeddings and Vector Search, translate into a material revenue contribution from scaled enterprise AI agent deployments in the near term, moving beyond primarily core workload-driven growth?
Question 3: Can MongoDB's Enterprise Advanced (EA) business exceed its mid-single-digit FY27 revenue guidance, particularly given the implied flat growth in the second half and the impact of new go-to-market leadership and the federal acquisition, while simultaneously expanding overall non-GAAP operating margins towards the Rule of 40 target?

Rerating Thresholds3 rows

Metric	What'S Needed For Rerating	Why It Matters	Earnings Date
Subscription Revenue	For MongoDB (MDB) to rerate higher, Subscription Revenue growth needs to hit 23% or higher year-over-year for Q4 FY2026, surpassing the analyst consensus estimate of 21.1%. This acceleration should be primarily driven by MongoDB Atlas revenue growth exceeding 30% year-over-year. Additionally, strong initial fiscal 2027 guidance that is in-line to slightly ahead of consensus expectations is crucial.	Hitting this threshold signals reacceleration in MongoDB's core subscription business, especially Atlas, which is vital for its AI deployment thesis. This validates its competitive strength, justifies its premium valuation, and demonstrates effective monetization of AI-driven workloads, driving investor confidence and potential stock rerating.	2026-03-02
Total Revenue	For MongoDB, Inc. (MDB) to rerate higher, the Total Revenue metric needs to hit a year-over-year growth rate of 23% or more for the upcoming Q4 2026 earnings report. This would represent a significant beat over the current analyst consensus estimate of approximately 21.8-22% revenue growth and exceed the high end of the company's own guidance of 21.7% growth. Additionally, strong performance in MongoDB Atlas, with growth exceeding the 27% consensus and ideally reaching or surpassing 30%, would be crucial. Positive initial guidance for fiscal year 2027 that is in-line to slightly ahead of consensus expectations will also be key to sustaining a rerating.	Achieving Total Revenue growth of 23%+ validates MDB's role as a critical data platform for AI deployment, aligning with the investment thesis. This demonstrates accelerating customer adoption and consumption, particularly for Atlas, reinforcing its competitive position and justifying its premium valuation in a high-growth market.	2026-03-02
MongoDB Atlas Revenue	For MongoDB, Inc. (MDB) to rerate higher, MongoDB Atlas Revenue needs to sustain or re-accelerate to 30% or higher year-over-year growth for Q4 FY26. This would significantly exceed the company's guidance of approximately 27% and the analyst consensus of around 27.2-27.3%. Additionally, strong initial fiscal 2027 guidance for Atlas revenue growth, ideally above current consensus expectations, is a crucial near-term hurdle.	Atlas is MongoDB's primary growth engine, constituting 75% of total revenue. Sustained or re-accelerated 30%+ Atlas growth validates the AI investment thesis, demonstrating MDB's ability to capture AI-driven workloads and maintain its competitive edge against hyperscalers. This performance would justify its premium valuation and boost investor confidence, driving a positive rerating.	2026-03-02

Earnings Transcript Summary3 rows

2026-05-28 · 2027Q1 Earnings Call

3 Things Management Is Most Focused On	Call Takeaway & Tone	Prior Quarter'S Y/Y Growth By Segment	3 Things Analysts Most Pressed On (And Mgmt Responses)	Revenue Segments
1. Elevating MongoDB to a Strategic Platform: Management is focused on engaging directly with C-suite leaders to elevate MongoDB from a technical decision to a strategic platform commitment, connecting customer modernization and AI opportunities to MongoDB's unique solutions. 2. Accelerating AI-Driven Innovation: The company is committed to continuously feeding customer insights into product development to enhance AI capabilities, including Vector Search and Voyage embeddings, and expanding EA's product value with new and advanced features, positioning MongoDB as the generational data platform for the agentic era. 3. Expanding Go-to-Market and Operational Efficiency: Management is strengthening go-to-market efforts in key verticals like U.S. federal (highlighted by the Clarity Business Solutions acquisition) and new regions like Japan, while simultaneously driving operating margin and cash flow expansion.	The call conveyed a highly positive, confident, and optimistic tone. MongoDB delivered strong first-quarter results, exceeding all guidance ranges, driven by broad-based momentum across Atlas (29.4% y/y growth), Enterprise Advanced (13% y/y growth), and early but growing traction in AI workloads. Management expressed strong confidence in MongoDB's strategic positioning as the generational data platform for the AI era, emphasizing continued investment in AI capabilities, go-to-market expansion (including the U.S. federal vertical and Japan), and a commitment to expanding profitability while investing for growth. The company also highlighted new leadership appointments to strengthen its product and go-to-market teams.	In the prior quarter (Q4 FY26), Atlas revenue grew 29% year-over-year. Non-Atlas revenue (equivalent to EA & other) grew 20% year-over-year. [cite: 2026-03-02]	1. Agentic Workloads and Revenue Impact: Analysts questioned if agentic workloads are genuinely starting to move the needle on consumption. Management responded that it's still early but they are seeing very encouraging signs, are ready to scale, and large enterprises are showing excitement for MongoDB as an operational data layer and long-term memory for production agents at scale. 2. Atlas Revenue Guidance and Seasonality: Analysts inquired about the predictability of Atlas revenue guidance and expected seasonality. Management clarified that as Atlas has grown, it has become more predictable and less sensitive to individual customer movements, with Q2 guidance reflecting strong Q1 consumption. They do not expect significant year-over-year changes in seasonality but maintain prudent guidance for EA due to deal timing. 3. AI-Native Companies and Go-to-Market Strategy: Analysts pressed on the opportunity with AI-native companies and how MongoDB's go-to-market needs to evolve to address them. Management acknowledged it's a work in progress, with many AI-native companies coming through self-serve, and they are actively determining the optimal intervention point for field reps. They highlighted competitive wins where AI-native companies chose MongoDB for scalability and integrated capabilities over alternatives.	Total revenue grew 25% year-over-year to $688 million. Atlas revenue grew 29.4% year-over-year. EA & other revenue grew 13% year-over-year.

2026-03-02 · 2026Q4 Earnings Call

3 Things Management Is Most Focused On	Call Takeaway & Tone	Prior Quarter'S Y/Y Growth By Segment	3 Things Analysts Most Pressed On (And Mgmt Responses)	Revenue Segments
1. Relentlessly customer-focused: Management aims to deepen strategic partnerships and accelerate growth, particularly with large enterprises and AI-native customers, by actively engaging the C-suite and driving top-down strategic expansion conversations. 2. Accelerating innovation agenda: The focus is on empowering product and engineering teams to build the generational multi-cloud data platform for the AI era, which includes enhancing AI capabilities, further integrating Voyage, and bringing feature parity to Enterprise Advanced (EA) relative to Atlas. 3. Driving operational excellence and scaling go-to-market: This involves thoughtfully scaling the self-serve motion to expand adoption, especially among AI-native companies, and strengthening the go-to-market team through new leadership appointments to sustain durable, profitable growth.	The call conveyed a highly positive and confident tone. MongoDB delivered an exceptional fourth quarter, exceeding revenue and operating margin guidance, driven by strong Atlas and Non-Atlas growth, robust customer additions, and record new ARR. Management expressed strong confidence in MongoDB's foundation and its strategic positioning as the generational data platform for the AI and multi-cloud era. They highlighted continued investment in innovation (including AI capabilities and EA feature parity) and go-to-market execution, while committing to durable, profitable growth and margin expansion. While AI presents a massive long-term opportunity, management remains prudent about its immediate material revenue contribution from large enterprises. The leadership transition was presented as well-planned, with minimal disruption expected.	In the prior quarter (Q3 FY26), Atlas revenue grew 30% year-over-year. Non-Atlas ARR grew 8% year-over-year.	1. Go-to-market leadership transition (CRO search and Erica Volini's role): Analysts inquired about the status of the Chief Revenue Officer (CRO) search and the attributes sought in a successor, as well as the specific focus of Erica Volini as Chief Customer Officer. Management responded that they are in the final stages of the CRO search, seeking a strategic leader focused on high-end enterprise, consumption models, and AI-native companies. Erica Volini will focus on post-sales support and ensuring customer success. Management stated they do not expect material disruptions from the transition and have confidence in the existing regional leadership. 2. Momentum and future growth of the EA (Enterprise Advanced) business, especially regarding large multiyear deals and bundling: Analysts questioned if strong Q4 EA performance and renewed importance of on-premise deployments should lead to recalibrated growth expectations for EA in future years. Management affirmed the strategic importance of EA, particularly in regulated industries, and their investment in bringing it to feature parity with Atlas. However, they maintained a prudent low to mid-single-digit growth outlook for FY27 due to the inherent difficulty in forecasting large multiyear deals and their significant impact on revenue, noting that the Q4 bundling impact was from one exceptionally large transaction. 3. Impact and timing of AI on revenue growth and architectural suitability: Analysts asked about MongoDB's product and go-to-market strategy for agentic applications and how quickly AI could become a material revenue driver. Management emphasized their goal for 'agents to love MongoDB' through autonomous, machine-friendly APIs, auto-scaling, and integrated capabilities like vector search and embeddings. While optimistic about AI's long-term potential, management indicated that AI is not yet a material revenue driver, as large enterprises are still in early stages of deploying scaled, customer-facing agentic workloads.	Total revenue grew 27% year-over-year to $695 million. Atlas revenue grew 29% year-over-year, crossing the $2 billion run rate mark. Non-Atlas revenue grew 20% year-over-year, marking its best growth quarter in the last two years. Non-Atlas ARR grew 13% year-over-year. Adjusted for a large bundled deal, Atlas growth would have been approximately 30%.

2025-12-01 · 2026Q3 Earnings Call

3 Things Management Is Most Focused On	Call Takeaway & Tone	Prior Quarter'S Y/Y Growth By Segment	3 Things Analysts Most Pressed On (And Mgmt Responses)	Revenue Segments
1. Deepening customer relationships and expanding market penetration: CJ Desai emphasized meeting with over 30 customers, including Fortune 500 and AI-native companies, to understand their needs and expand MongoDB's footprint for mission-critical and AI workloads. He highlighted the immense expansion opportunity within existing enterprises and the goal to penetrate Fortune 500 at a higher rate. 2. Advancing innovation for the AI era and building a generational modern data platform: Management is focused on leveraging MongoDB's document model, integrated search, vector search, and Voyage embeddings to define the AI wave. CJ Desai specifically mentioned the importance of their embedding and reranking models, vector database, and operational platform for AI workloads, aiming to be the foundational data platform for the multi-cloud and AI era. 3. Driving durable, efficient growth and expanding profitability: Mike Berry reiterated commitment to the long-term financial model, focusing on continued revenue growth, strategic investments in engineering, marketing, and sales capacity, while also driving margin expansion and strong free cash flow conversion (expected to exceed 100% for fiscal '26).	The call conveyed a highly positive and confident tone, highlighting an exceptional third quarter with accelerating Atlas growth, robust customer additions, and significant operating margin outperformance. Management raised financial guidance for Q4 and the full fiscal year 2026, underscoring the strength of MongoDB's core business and its unique positioning to become the generational modern data platform for the AI era, all while driving durable and efficient growth. There was a note of prudence regarding Q4 seasonality and the early stage of enterprise AI adoption.	Atlas Revenue: 29% year-over-year; Non-Atlas ARR: 7% year-over-year.	1. CJ Desai's initial vision and strategy for the AI era and core business strength: Analysts inquired about CJ's immediate focus and long-term plans to position MongoDB as a foundational data platform for AI. Management responded that low-hanging fruit includes their embedding and reranking models, then the vector database, and eventually the operational store for AI workloads. They also clarified that core business strength is driven by modernization efforts and suitability for unstructured/semi-structured data, acknowledging that AI could potentially drive more modernization. 2. Reinvestment philosophy and the outlook for operating margins in fiscal '27: Analysts questioned how MongoDB plans to balance continued investment with margin expansion, especially given the strong margin performance in fiscal '26. Management stated they would continue strategic investments in engineering, marketing, and sales capacity, expecting OpEx to grow in fiscal '27, but reiterated their commitment to 100 to 200 basis points of margin expansion on average, primarily driven by revenue growth. 3. Atlas growth predictability and new customer ramp, particularly for AI-native companies: Analysts asked about the factors driving the more definitive Atlas guidance and if new customers, especially AI-native ones, are ramping faster. Management explained that increased visibility and better forecasting as Atlas scales allow for more precise guidance, while also being prudent due to Q4 seasonal holiday patterns. They noted that engineering efforts and the self-serve team have reduced friction for onboarding, but the revenue contribution from new customers remains relatively small initially. For AI-native companies, they can land with Voyage AI embeddings first, then expand to the vector database and operational database.	Total Revenue: 19% year-over-year; Atlas Revenue: 30% year-over-year; Non-Atlas ARR: 8% year-over-year.

Transcript Tidbits4 rows

2026-05-28

About Expanding Eligible Market	About Competition	About The Broader Industry	Where Things Are Headed	Updates On Theme	Broader Themes Emerging	Bullish-Leaning Quotes (Short)	Bearish-Leaning Quotes (Short)	Hiring
MongoDB is expanding its eligible market by engaging with a wide range of customers, from AI natives and digital natives to large enterprises and public sector organizations, for both core mission-critical workloads and AI-powered agentic applications. The company added 2,500 customers in Q1, bringing the total to over 67,700. AI adoption is accelerating, with Voyage customers more than doubling quarter-over-quarter and Vector Search adoption far outpacing overall company growth. MongoDB is becoming a strategic platform decision for customers like Zoom, which standardized multiple services on MongoDB Enterprise Advanced. The company is also seeing opportunities in frontier labs (plural), AI-native companies like Endor Labs, and enterprises deploying AI, such as Zomato and Adobe, which are using MongoDB as a memory layer for AI agents. MongoDB acquired Clarity Business Solutions to strategically increase its investment in the U.S. federal vertical, with plans for FedRAMP high certification this year. 45% of Atlas customers with at least $100,000 in ARR are leveraging two or more platform features, up from 37% a year ago.	MongoDB is demonstrating competitive wins against alternatives like DynamoDB and DocumentDB, which Zomato evaluated before choosing Atlas for its aggregation pipeline, write consistency, and flexible schema. The company highlights its architectural advantage over rigid relational schemas, which become a 'tax on every iteration' in the agentic era, and over analytical systems not designed for real-time agent behavior. MongoDB's native JSON format aligns with LLMs, which 'speak in unstructured documented shape data'. The company has deep integrations with LangChain, including MongoDB Checkpointer for LangSmith deployment, which 'collapses what used to be a dedicated Postgres instance per agent into a single, shared Atlas cluster'. AI-native companies like ElevenLabs moved to MongoDB after their previous data layers (first-party database and another search software) were 'choking' on performance and scale, with customers noting that Postgres 'completely choked on the performance'. MongoDB's integrated Search and Vector Search capabilities reduce the need for ETL to other search providers or struggling with open-source alternatives.	The industry is seeing a shift where core workloads and AI opportunities are not distinct but reinforce each other, with enterprises building agentic applications on existing data layers. MongoDB is increasingly becoming a 'strategic platform decision' rather than just a workload-by-workload evaluation. The assumption that 'every workload eventually migrates to the public cloud is being challenged by real factors: cost at scale, capacity challenges, latency requirements and regulatory mandates on data residency,' leading to a resurgence of hybrid and on-prem deployments. The 'agentic conversation seems to have really shifted even over the past 3 months from proof of concept into real production deployments'. There's a growing realization that 'data needs to be consolidated and cleaner' for AI. Software development is evolving, with a 'growing share of software... created through prompt-driven development, natural language iteration rather than line-by-line authorship'.	MongoDB is optimistic about its future, believing it is 'purpose-built to be generational data platform for the agentic era' and moving 'beyond a system of record to becoming the real-time system of intelligence'. The company is accelerating its innovation roadmap, with MongoDB 8.3 delivering significant performance improvements (up to 45% more reads, 35% more writes, 15% more ACID transactions). Automated Voyage AI embeddings entered public preview, enabling semantic search in minutes. MongoDB is expanding its integrations with agent frameworks like LangChain and launched a Plugin and agent skills on the Claude Code marketplace. The company has appointed two new CPOs: Ben Cefalo for core products (Atlas and EA) and Pablo Stern-Plaza for AI and Emerging Products, with Jim Scharf as CTO focusing on enterprise requirements. New go-to-market leaders, Erica Volini (Chief Customer Officer) and Ryan Mac Ban (Chief Revenue Officer), are partnering to capture opportunities. MongoDB is raising its fiscal '27 outlook, expecting Atlas revenue growth of approximately 26% in Q2 and 23% to 25% for the full year. EA and other revenue is expected to grow approximately 20% in Q2 and mid-single-digits for the full year. The company plans to expand operating margin by 100 to 150 basis points in fiscal '27, targeting a 'Rule of 40 performance' (20% revenue growth and 20% operating margin). Investments will focus on enhancing AI capabilities (Vector Search, Voyage), expanding EA's product value, building presence in Japan, and strengthening the U.S. federal vertical.	**Phase	The assumption that every workload eventually migrates to the public cloud is being challenged by real factors like cost at scale, capacity challenges, latency requirements, and regulatory mandates on data residency, indicating a broader trend towards hybrid cloud and on-prem deployments. A growing share of software is now created through prompt-driven development and natural language iteration, rather than traditional line-by-line authorship, signifying a fundamental shift in software creation. There is also an emerging realization in the industry that 'data needs to be consolidated and cleaner' for effective AI implementation.	We generated total revenue of $688 million, up 25% year-over-year, beating the high end of guidance and accelerating. Top line strength was driven by Atlas, which grew 29.4% year-over-year including a record $117 million year-over-year dollar growth. Now at a $2 billion run rate, this is the fourth quarter in a row Atlas delivered year-over-year growth of at least 29%. We delivered a non-GAAP operating margin of 18%, above the high end of the guidance. AI adoption of MongoDB technologies across our customer base continues to accelerate. Voyage customers have more than doubled quarter-over-quarter and Vector Search adoption is far outpacing overall company growth. MongoDB is purpose-built to be generational data platform for the agentic era. We are raising our outlook across the board for fiscal '27. Our business model continues to deliver operating margin and cash flow expansion. Total company net ARR expansion rate, which was 121% for the quarter compared to 119% a year ago. We had our second quarter in a row of GAAP profitability, which is a great trend. Operating cash flow for the quarter was $202 million versus $110 million last year, and free cash flow was $198 million versus $106 million last year. We are optimistic regarding our growth prospects, and we'll continue to invest responsibly to drive long-term shareholder value. I am really fired up about our innovation road map that is accelerating. MongoDB is on its way to becoming the generational data platform of choice for the AI era.	To be clear, our results today are driven primarily by core workloads. It's still early, Matt, just to be clear, because the security governance, observability, there are many, many aspects to the agents. For the full year, given Atlas is a consumption-based product, there's a little more room for variability as we go further out in the year. We'll always guide conservatively due to the uncertainty around the timing of the deals. This implies that EA and other revenue will be approximately flat during the second half of the year. It remains difficult to predict the duration of our EA deals.	MongoDB announced two new CPO appointments: Ben Cefalo as Chief Product Officer for core products and Pablo Stern-Plaza as Chief Product Officer for AI and Emerging Products. On the go-to-market side, Erica Volini joined as Chief Customer Officer and Ryan Mac Ban joined as Chief Revenue Officer. The company will 'continue to invest in quota-carrying headcount, marketing programs and developer awareness'. The acquisition of Clarity Business Solutions brings in 'deep domain expertise and high-level security clearances' to accelerate the U.S. federal vertical. While Ryan Mac Ban may make 'some tweaks next year' to the go-to-market organization, no significant changes are expected for the remainder of fiscal '27.

2026-03-02

About Expanding Eligible Market	About Competition	About The Broader Industry	Where Things Are Headed	Updates On Theme	Broader Themes Emerging	Bullish-Leaning Quotes (Short)	Bearish-Leaning Quotes (Short)	Hiring
MongoDB is seeing immense expansion opportunities, serving AI natives to Fortune 500 enterprises, with Atlas crossing the $2 billion run rate mark and non-Atlas achieving its best growth in two years. The company signed its largest TCV deal ever, a greater than $100 million transaction for Enterprise Advanced (EA) with a large financial institution, and a $90 million transaction with a large tech company for Atlas. Customer additions increased by 60% year-over-year, reaching over 65,200 customers. The number of customers leveraging vector search and Voyage embedding models has nearly doubled year-over-year. Large enterprises are increasingly standardizing on MongoDB for both core mission-critical applications and emerging agentic AI applications. There is a renewed importance of on-premises deployment, particularly in regulated industries, leading to long-term commitments for EA. MongoDB is investing in EA to bring it to feature parity with Atlas, expecting to accelerate its growth. The company aims to expand within its existing Fortune 500, Global 2000, and AI native customer base, and scale its self-serve motion with a focus on AI native companies. [cite: 2025-12-01]	MongoDB is demonstrating competitive wins, with Emergent Labs selecting Atlas over PostgreSQL to power AI agents. The company highlights its architectural advantage for AI and agentic applications, noting that its modern OLTP platform with integrated search, vector search, and embeddings is purpose-built to win in this platform shift, unlike traditional relational databases that struggle with unstructured and semi-structured AI workloads. [cite: 2025-12-01] Customers like ElevenLabs chose Atlas for critical long-term memory and knowledge bases for autonomous agents due to its real-time, global scale capabilities. MongoDB's integrated platform, offering native JSON with search, vector search, and embeddings in one, provides a strength for AI native companies needing performance and scale for both reads and writes. [cite: 2025-12-01]	The industry is at a true inflection point driven by major shifts across cloud, data, and AI, positioning MongoDB as a generational data platform for the AI and multi-cloud era. [cite: 2025-12-01] AI and agentic applications require a different architecture, demanding memory, state, and high-quality retrieval, which are native to MongoDB's modern OLTP platform. There is a renewed importance of on-premises deployment in enterprise architectures, especially in regulated industries, where customers view EA as mission-critical for operational resilience and data that will not move to the public cloud. The combined power of the document model, Atlas's performance and scale, multi-environment flexibility, and integrated AI functionality resonates strongly with customers. [cite: 2025-12-01]	MongoDB aims to become the generational data platform of choice in the AI and multi-cloud era, with a focus on deepening strategic customer partnerships, accelerating innovation for the AI era, scaling its self-serve motion for AI native companies, and driving operational excellence. The company remains committed to its long-term financial model, targeting Atlas revenue growth greater than 20% and achieving a Rule of 40 performance, primarily driven by revenue growth. For fiscal '27, Atlas revenue growth is expected to be 21% to 23%, and non-Atlas growth is projected at low to mid-single digits. MongoDB will invest in enhancing AI capabilities, integrating Voyage, achieving feature parity for EA with Atlas, expanding in Japan, and strengthening its U.S. federal business. The company expects to expand operating margin by 100 basis points in fiscal '27 and maintain cash conversion in the 80% to 100% range. While optimistic about AI natives, they are not yet meaningful revenue drivers. The vision is for agents to 'love MongoDB' as much as human developers do, with a roadmap for machine-friendly APIs, auto-scaling, and auto-sharding throughout the year. The modernization opportunity in enterprises remains massive, with AI tools assisting but customers still relying on MongoDB for critical workloads. [cite: 2025-12-01]	Deployment.	Major shifts across cloud, data, and AI are driving a multi-cloud and public cloud transformation expected to continue for 5 to 7 years. [cite: 2025-12-01] The advent of agentic coding tools is increasing the rate and pace of software development across industries. [cite: 2025-12-01] There is also a broader trend of renewed importance for on-premises deployment in enterprise architectures, leading to truly hybrid infrastructure solutions.	MongoDB's foundation is in great shape, and the company is well on its way to become the generational data platform of choice in the AI and multi-cloud era. Atlas, which grew 29% year-over-year crossing the $2 billion run rate mark for the first time. Non-Atlas grew 20% year-over-year, our best growth quarter in the last 2 years. Largest TCV deal in the history of MongoDB. We delivered a non-GAAP operating margin of 23%, more than 100 basis points above the high end of guidance. Achieving above a Rule of 40 performance and demonstrating that we can drive durable revenue growth while simultaneously expanding margin. Tremendous opportunity to expand within our existing Fortune 500, Global 2000 and AI native customer base. OLTP is the high ground and MongoDB is purpose-built to win. The caliber of these candidates is a testament to our momentum and the significant opportunity ahead. We sure hope to do better than that. Our results underscore that MongoDB's core business is firing on all cylinders even before any meaningful AI tailwinds. [cite: 2025-12-01]	While AI is not yet a material driver to our results, we are encouraged by the growth we are seeing with customers leveraging our AI capabilities. While this subset of customers has significant potential, many of them remain early in their MongoDB journey and are not yet meaningful drivers of revenue. Visibility is more limited in the back half of the fiscal year. Non-Atlas... it remains difficult to predict. We want to be mindful there could be risk that we do not have line of sight to at this time. While it adds a level of uncertainty, I want to underline what CJ said in his prepared remarks. We've been working on this for a while. I've not seen agents at scale that are customer facing or sometimes even employee-facing, they may have 10, 15, 20, but not that many compared to thousands of applications they run. [cite: 2025-12-01] The churn for some of these AI companies that deliver these tools is also very real. [cite: 2025-12-01] It's not if but when, okay? So right now, we do consider... where are you on your Agentic workloads? And I'm talking about Fortune 500... And the answer is still not yet.	Erica Volini joins MongoDB as Chief Customer Officer, reporting directly to the CEO, effective March 3, 2026. Cedric Pech, President of Field Operations, and Paul Keppambesis, Chief Revenue Officer, are leaving MongoDB, with Paul remaining through Q1 and serving as an adviser through Q2 for a seamless transition. The company is in the latter stages of a search for a new CRO. MongoDB will continue to invest in select quota-carrying headcount.

2026-03-02

About Expanding Eligible Market	About Competition	About The Broader Industry	Where Things Are Headed	Updates On Theme	Broader Themes Emerging	Bullish-Leaning Quotes (Short)	Bearish-Leaning Quotes (Short)	Hiring
MongoDB is seeing immense expansion opportunities, serving AI natives to Fortune 500 enterprises, with Atlas crossing the $2 billion run rate mark and non-Atlas achieving its best growth in two years. The company signed its largest TCV deal ever, a greater than $100 million transaction for Enterprise Advanced (EA) with a large financial institution, and a $90 million transaction with a large tech company for Atlas. Customer additions increased by 60% year-over-year, reaching over 65,200 customers. The number of customers leveraging vector search and Voyage embedding models has nearly doubled year-over-year. Large enterprises are increasingly standardizing on MongoDB for both core mission-critical applications and emerging agentic AI applications. There is a renewed importance of on-premises deployment, particularly in regulated industries, leading to long-term commitments for EA. MongoDB is investing in EA to bring it to feature parity with Atlas, expecting to accelerate its growth. The company aims to expand within its existing Fortune 500, Global 2000, and AI native customer base, and scale its self-serve motion with a focus on AI native companies. [cite: 2025-12-01]	MongoDB is demonstrating competitive wins, with Emergent Labs selecting Atlas over PostgreSQL to power AI agents. The company highlights its architectural advantage for AI and agentic applications, noting that its modern OLTP platform with integrated search, vector search, and embeddings is purpose-built to win in this platform shift, unlike traditional relational databases that struggle with unstructured and semi-structured AI workloads. [cite: 2025-12-01] Customers like ElevenLabs chose Atlas for critical long-term memory and knowledge bases for autonomous agents due to its real-time, global scale capabilities. MongoDB's integrated platform, offering native JSON with search, vector search, and embeddings in one, provides a strength for AI native companies needing performance and scale for both reads and writes. [cite: 2025-12-01]	The industry is at a true inflection point driven by major shifts across cloud, data, and AI, positioning MongoDB as a generational data platform for the AI and multi-cloud era. [cite: 2025-12-01] AI and agentic applications require a different architecture, demanding memory, state, and high-quality retrieval, which are native to MongoDB's modern OLTP platform. There is a renewed importance of on-premises deployment in enterprise architectures, especially in regulated industries, where customers view EA as mission-critical for operational resilience and data that will not move to the public cloud. The combined power of the document model, Atlas's performance and scale, multi-environment flexibility, and integrated AI functionality resonates strongly with customers. [cite: 2025-12-01]	MongoDB aims to become the generational data platform of choice in the AI and multi-cloud era, with a focus on deepening strategic customer partnerships, accelerating innovation for the AI era, scaling its self-serve motion for AI native companies, and driving operational excellence. The company remains committed to its long-term financial model, targeting Atlas revenue growth greater than 20% and achieving a Rule of 40 performance, primarily driven by revenue growth. For fiscal '27, Atlas revenue growth is expected to be 21% to 23%, and non-Atlas growth is projected at low to mid-single digits. MongoDB will invest in enhancing AI capabilities, integrating Voyage, achieving feature parity for EA with Atlas, expanding in Japan, and strengthening its U.S. federal business. The company expects to expand operating margin by 100 basis points in fiscal '27 and maintain cash conversion in the 80% to 100% range. While optimistic about AI natives, they are not yet meaningful revenue drivers. The vision is for agents to 'love MongoDB' as much as human developers do, with a roadmap for machine-friendly APIs, auto-scaling, and auto-sharding throughout the year. The modernization opportunity in enterprises remains massive, with AI tools assisting but customers still relying on MongoDB for critical workloads. [cite: 2025-12-01]	Deployment.	Major shifts across cloud, data, and AI are driving a multi-cloud and public cloud transformation expected to continue for 5 to 7 years. [cite: 2025-12-01] The advent of agentic coding tools is increasing the rate and pace of software development across industries. [cite: 2025-12-01] There is also a broader trend of renewed importance for on-premises deployment in enterprise architectures, leading to truly hybrid infrastructure solutions.	MongoDB's foundation is in great shape, and the company is well on its way to become the generational data platform of choice in the AI and multi-cloud era. Atlas, which grew 29% year-over-year crossing the $2 billion run rate mark for the first time. Non-Atlas grew 20% year-over-year, our best growth quarter in the last 2 years. Largest TCV deal in the history of MongoDB. We delivered a non-GAAP operating margin of 23%, more than 100 basis points above the high end of guidance. Achieving above a Rule of 40 performance and demonstrating that we can drive durable revenue growth while simultaneously expanding margin. Tremendous opportunity to expand within our existing Fortune 500, Global 2000 and AI native customer base. OLTP is the high ground and MongoDB is purpose-built to win. The caliber of these candidates is a testament to our momentum and the significant opportunity ahead. We sure hope to do better than that. Our results underscore that MongoDB's core business is firing on all cylinders even before any meaningful AI tailwinds. [cite: 2025-12-01]	While AI is not yet a material driver to our results, we are encouraged by the growth we are seeing with customers leveraging our AI capabilities. While this subset of customers has significant potential, many of them remain early in their MongoDB journey and are not yet meaningful drivers of revenue. Visibility is more limited in the back half of the fiscal year. Non-Atlas... it remains difficult to predict. We want to be mindful there could be risk that we do not have line of sight to at this time. While it adds a level of uncertainty, I want to underline what CJ said in his prepared remarks. We've been working on this for a while. I've not seen agents at scale that are customer facing or sometimes even employee-facing, they may have 10, 15, 20, but not that many compared to thousands of applications they run. [cite: 2025-12-01] The churn for some of these AI companies that deliver these tools is also very real. [cite: 2025-12-01] It's not if but when, okay? So right now, we do consider... where are you on your Agentic workloads? And I'm talking about Fortune 500... And the answer is still not yet.	Erica Volini joins MongoDB as Chief Customer Officer, reporting directly to the CEO, effective March 3, 2026. Cedric Pech, President of Field Operations, and Paul Keppambesis, Chief Revenue Officer, are leaving MongoDB, with Paul remaining through Q1 and serving as an adviser through Q2 for a seamless transition. The company is in the latter stages of a search for a new CRO. MongoDB will continue to invest in select quota-carrying headcount.

2025-12-01

About Expanding Eligible Market	About Competition	About The Broader Industry	Where Things Are Headed	Updates On Theme	Broader Themes Emerging	Bullish-Leaning Quotes (Short)	Bearish-Leaning Quotes (Short)	Hiring
MongoDB sees an immense expansion opportunity, already serving over 70% of the Fortune 100 and many of the world's largest banks, healthcare organizations, and manufacturers, with significant room to broaden its footprint within the enterprise. The multi-cloud and public cloud transformation efforts are expected to continue for at least another 5 to 7 years, ensuring a substantial total addressable market (TAM) for MongoDB. The company is also actively planting seeds with AI-native companies, aiming to become their underlying infrastructure.	MongoDB is demonstrating competitive wins against established and homegrown solutions. A fast-growing AI-native company switched from Postgres to MongoDB due to scaling issues. A global media company re-architected on MongoDB Atlas and Atlas Vector Search after their existing Elasticsearch stack hit a performance wall with new embedding models, resulting in a 90% latency reduction and 65% operational spend reduction. Relational databases are noted for not scaling well with unstructured and semi-structured AI workloads, giving MongoDB a structural advantage. MongoDB's Voyage embeddings and Atlas Vector Search are also replacing homegrown vector databases.	The industry is at a true inflection point driven by major shifts across cloud, data, and AI. AI applications require a different architecture than the last generation of software, needing to connect LLM knowledge with proprietary data, systems, and real-time context, which is fundamentally an information retrieval problem. Rapidly evolving AI models and the increased speed of application development mean rigid tabular stores and fixed database schemas cannot keep pace. The rate and pace of software development are expected to increase due to agentic coding and AI tools, acting as a tailwind for the database industry. In regulated industries, there are stringent requirements for security, durability, and performance for AI agents to move from prototype to production, including governance and auditability.	MongoDB aims to become the generational modern data platform for the multi-cloud and AI era, an opportunity that comes once in a lifetime. The company is positioned to help define the AI wave as adoption accelerates. CJ Desai's immediate focus includes deepening customer relationships, advancing the innovation agenda, scaling go-to-market efforts, and supporting employees. MongoDB remains committed to its long-term financial model, targeting 100 to 200 basis points of margin expansion and 80% to 100% free cash flow conversion on average.	Deployment.	Major shifts across cloud, data, and AI are driving a multi-cloud and public cloud transformation expected to continue for 5 to 7 years. The advent of agentic coding tools is increasing the rate and pace of software development across industries.	Atlas performance was strong, accelerating to 30% year-over-year growth, up from 29% in Q2 and 26% in Q1. Q3 was an exceptional quarter that was driven by our continued go-to-market execution and the broad-based demand we are seeing across business. We significantly outperformed on operating margin, demonstrating that we can drive durable revenue growth while simultaneously expanding profitability. The expansion opportunity in front of us is immense. MongoDB's positioned not just to participate in the wave, but to help define it. We are raising our financial guidance for the fourth quarter and the full fiscal year 2026 and reiterating our commitment to the long-term financial model. Our results underscore that MongoDB's core business is firing on all cylinders even before any meaningful AI tailwinds.	Some of these planned investments have taken longer to implement than expected and have shifted into the fourth quarter of fiscal '26 and fiscal '27, which has benefited our operating margin during fiscal '26. Q4, we want to be prudent because there are some seasonal holiday patterns that can be somewhat unpredictable, and we've seen that play out in the past Q4s. I've not seen agents at scale that are customer facing or sometimes even employee-facing, they may have 10, 15, 20, but not that many compared to thousands of applications they run. The churn for some of these AI companies that deliver these tools is also very real.	MongoDB is continuing to make strategic investments in engineering, marketing, and direct sales capacity to drive continued growth. Some planned investments, including headcount adds, have shifted into Q4 fiscal '26 and fiscal '27.

Earnings Results3 rows

Total revenue grew 27% year-over-year to $695 million, exceeding the rerating trigger of 23% and the high end of company guidance. Atlas revenue also showed str

Metric	Prior Quarter	Rerating Trigger	Actual Reported	Hit Target?	Notes
Total Revenue	19%	For MongoDB, Inc. (MDB) to rerate higher, the Total Revenue metric needs to hit a year-over-year growth rate of 23% or more for the upcoming Q4 2026 earnings report. This would represent a significant beat over the current analyst consensus estimate of approximately 21.8-22% revenue growth and exceed the high end of the company's own guidance of 21.7% growth. Additionally, strong performance in MongoDB Atlas, with growth exceeding the 27% consensus and ideally reaching or surpassing 30%, would be crucial. Positive initial guidance for fiscal year 2027 that is in-line to slightly ahead of consensus expectations will also be key to sustaining a rerating.	$695 million (27% y/y growth)	Yes	Total revenue grew 27% year-over-year to $695 million, exceeding the rerating trigger of 23% and the high end of company guidance. Atlas revenue also showed strong growth at 29% (or 30% adjusted), surpassing the 27% consensus mentioned in the trigger. The company provided initial fiscal year 2027 guidance for total revenue in the range of $2.86 billion to $2.9 billion, representing 16% to 18% full-year growth, and non-GAAP income from operations of $545 million to $565 million for an operating margin of approximately 19.5% at the high end.
MongoDB Atlas Revenue	30%	For MongoDB, Inc. (MDB) to rerate higher, MongoDB Atlas Revenue needs to sustain or re-accelerate to 30% or higher year-over-year growth for Q4 FY26. This would significantly exceed the company's guidance of approximately 27% and the analyst consensus of around 27.2-27.3%. Additionally, strong initial fiscal 2027 guidance for Atlas revenue growth, ideally above current consensus expectations, is a crucial near-term hurdle.	29% y/y growth	Partially	Atlas revenue grew 29% year-over-year. While this was slightly below the 30% rerating trigger, management noted that adjusting for a large bundled deal, Atlas growth would have been approximately 30%. This indicates underlying strength. The company also provided initial fiscal 2027 guidance for Atlas revenue growth of approximately 21% to 23%.
Subscription Revenue	19%	For MongoDB (MDB) to rerate higher, Subscription Revenue growth needs to hit 23% or higher year-over-year for Q4 FY2026, surpassing the analyst consensus estimate of 21.1%. This acceleration should be primarily driven by MongoDB Atlas revenue growth exceeding 30% year-over-year. Additionally, strong initial fiscal 2027 guidance that is in-line to slightly ahead of consensus expectations is crucial.	27% y/y growth (Total Revenue)	Yes	While 'Subscription Revenue' was not explicitly broken out, total revenue, which is predominantly subscription-based, grew 27% year-over-year, exceeding the 23% rerating trigger. Atlas revenue, a key component of subscription revenue, grew 29% (or 30% adjusted), aligning with the driver mentioned in the trigger. The company also provided strong initial fiscal 2027 guidance.

NotesTable

Date	Comment	Comment Type	Comment Sentiment	Link	IS CHANGE	Price Reaction
2026-05-28	MongoDB's Q1 FY27 earnings significantly beat expectations, with total revenue up 25% and Atlas revenue growing 29.4%. The company raised its full-year FY27 guidance, citing strong demand and emerging AI opportunities. The market initially perceived this very positively, with the stock surging over 20% post-earnings. However, some gains were later pared, indicating that while the results were strong and guidance increased, investors are becoming more discerning about growth valuations despite AI tailwinds.	Earnings Transcript	Neutral		False	N/A

Upcoming Events11 rows

Catalyst ID	Estimated Timing	Estimated Date Start	Estimated Date End	Catalyst	Why It Matters	Ticker Or Theme Specific	Transcript Date	Source Type
MDB_013741b3	for the fourth quarter and full fiscal year 2026	2026-01-01	2026-01-31	Guidance upgrade for the fourth quarter of fiscal 2026 and the full fiscal year 2026.	Signals stronger demand and potential margin expansion; could lift valuation and investor sentiment if results meet or exceed the raised guidance.	Ticker	2025-12-01	earnings_transcript
MDB_801d38c8	January 15, 2026	2026-01-15	2026-01-15	.local San Francisco developer-focused event relaunch to engage AI-native developers and showcase MongoDB's platform capabilities.	Could accelerate developer adoption and Atlas usage, potentially boosting demand and sentiment if well received.	Ticker	2025-12-01	earnings_transcript
MDB_41d2c48c	Cap calls related to 2026 notes maturing in January 2026	2026-01-01	2026-01-31	Cap calls on 2026 notes maturing January 2026; company expects to receive over 1 million shares of stock as part of the cap-call settlements.	Dilution risk and share-count implications could impact EPS and sentiment; timing and execution could influence stock volatility.	Ticker	2025-12-01	earnings_transcript
MDB_36cb8026	Paul will remain CRO through Q1 and serve as an adviser through Q2	2026-03-02	2026-07-31	Appointment of a new Chief Revenue Officer (CRO) for MongoDB.	A successful CRO appointment is crucial for maintaining go-to-market execution and accelerating growth, particularly in large enterprises and AI-native customers. An unsuccessful or delayed appointment could disrupt sales momentum.	Ticker	2026-03-02	earnings_transcript
MDB_185764de	throughout this coming year	2026-03-02	2027-01-31	Release of new product innovations, including machine-friendly APIs, auto-scaling, and auto-sharding capabilities, specifically designed to enhance MongoDB's appeal and functionality for AI agents.	These innovations are critical for MongoDB to solidify its position as the preferred data platform for AI and agentic applications, potentially driving increased adoption and consumption from AI-native companies and enterprises building AI workloads.	Ticker	2026-03-02	earnings_transcript
MDB_a20b2525	During the upcoming year	2026-03-02	2027-01-31	Acceleration of MongoDB's partner growth engine, focusing on deepening relationships with hyperscalers, strategic system integrators for modernization efforts, and key players in the AI native ecosystem.	A more robust partner ecosystem can significantly expand MongoDB's reach, accelerate customer acquisition, and drive adoption of its platform for both core and AI workloads, impacting revenue growth and market share.	Ticker	2026-03-02	earnings_transcript
MDB_258e5473	throughout fiscal '27	2026-03-02	2027-01-31	Achievement of feature parity between MongoDB Enterprise Advanced (EA) and Atlas.	Bringing EA to feature parity with Atlas can enhance its competitiveness, especially in regulated industries and for customers preferring on-premise deployments, potentially driving stronger growth and larger multi-year deals for the EA business.	Ticker	2026-03-02	earnings_transcript
MDB_4850795d	still early, Matt, just to be clear, because the security governance, observability, there are many, many aspects to the agents and what kind of outcomes they deliver if it is agents at scale. But we feel that we are ready and just yesterday, Matt, I was with a Fortune 25 firm. And when we outlined what we already have, where MongoDB can not only act as an operational data layer, but can also act as a long-term memory and some of the things that we are building right now they got really, really excited as they think about rolling out production agents at scale. So early but I'm seeing very encouraging signs, and we are ready.	2026-08-01	2027-01-31	Material revenue contribution from widespread production deployment of customer-facing agentic AI applications by large enterprises.	This would significantly accelerate Atlas revenue growth beyond current core workload drivers, validating MongoDB's strategic positioning as the data platform for the AI era and positively impacting valuation and investor sentiment.	Theme	2026-05-28	earnings_transcript
MDB_28ffb3cc	this year	2026-06-01	2027-01-31	MongoDB achieving FedRAMP High certification for its U.S. federal offerings.	This certification will allow MongoDB to properly sell and serve U.S. federal customers, unlocking a significant new market (large TAM) and driving increased revenue from this vertical.	Ticker	2026-05-28	earnings_transcript
MDB_6a191a5a	second half of the year	2026-08-01	2027-01-31	EA and other revenue performance in the second half of fiscal '27, with the potential to exceed or fall short of the 'approximately flat' projection due to the unpredictable timing of large multiyear deals.	Exceeding the 'approximately flat' projection would signal stronger-than-expected demand for on-premise/hybrid deployments and large multiyear deals, positively impacting total revenue and investor sentiment. Falling short would be bearish.	Ticker	2026-05-28	earnings_transcript
MDB_ac3a311f	work in progress	2026-05-01	2027-01-31	Successful refinement and execution of MongoDB's go-to-market strategy to effectively intercept and scale with AI-native companies, moving them from self-serve to managed accounts.	A successful strategy would accelerate customer acquisition and revenue growth from the rapidly expanding AI-native segment, validating MongoDB's product fit and go-to-market efficiency for this critical customer cohort.	Ticker	2026-05-28	earnings_transcript