EPS of $-0.74 decreased by 39.6% from previous year
Gross margin of 73.2%
Net income of -54.53M
"AI continues to be an additional long-term opportunity for our business." - Dev Ittycheria
MongoDB Inc (MDB) QQ2 2025 Results Analysis — Atlas Momentum, MAAP AI Push, and Strategic Outlook
Executive Summary
MongoDB delivered a solid QQ2 2025 showing of top-line momentum and continued strength in its Atlas platform, with revenue of $478.1 million, up 13% year over year, and Atlas representing 71% of total revenue after a 27% year-over-year ascent. The company posted non-GAAP operating income of $52.5 million (11% non-GAAP operating margin) and ended the quarter with more than 50,700 customers, underscoring durable demand for its run-anywhere data platform. Management remains cautiously optimistic about the AI opportunity, anchored by MAAP (MongoDB AI Applications Program), Vector Search, and streaming capabilities, while acknowledging near-term macro headwinds that could influence consumption patterns in the back half of the year. On the balance sheet, MongoDB holds a robust liquidity position (~$2.3 billion in cash and equivalents and short-term investments) and is guiding to a higher starting Atlas ARR for H2, while signaling a planned increase in EA-related bookings and a commitment to margin expansion toward a mid-teens operating margin in the near term. Overall, the QQ2 2025 results reinforce a multi-year growth thesis centered on AI-enabled data workloads and legacy-modernization opportunities, but investors should monitor macro consumption trends, AI monetization timing, and incremental investment needs.
Key Performance Indicators
Revenue
478.11M
QoQ: 6.11% | YoY:12.82%
Gross Profit
349.86M
73.17% margin
QoQ: 7.59% | YoY:9.86%
Operating Income
-71.44M
QoQ: 27.24% | YoY:-45.79%
Net Income
-54.53M
QoQ: 32.34% | YoY:-45.04%
EPS
-0.74
QoQ: 32.73% | YoY:-39.62%
Revenue Trend
Margin Analysis
Key Insights
Revenue: $478.1 million, up 13% YoY and above the high end of guidance; QoQ growth ~+6.11% (Q1 revenue $450.6M).
Atlas vs Non-Atlas: Atlas revenue grew 27% YoY and accounted for 71% of total revenue; Non-Atlas revenue declined ~13% YoY due to tough prior-year license timing; Atlas mix driving gross margin pressure.
Operating performance (non-GAAP): Non-GAAP operating income $52.5 million; non-GAAP operating margin approximately 11% for the quarter.
Net income / EPS (GAAP vs non-GAAP): GAAP net income reported as $59 million (per the earnings call) or -$54.5 million in the data set depending on accounting treatment; non-GAAP metrics imply a positive operating trajectory. GAAP per-share figures were around $0.70 based on ~83.8 million diluted shares; management highlighted non-GAAP guidance for the coming quarters.
Financial Highlights
Key QQ2 2025 metrics and commentary:
- Revenue: $478.1 million, up 13% YoY and above the high end of guidance; QoQ growth ~+6.11% (Q1 revenue $450.6M).
- Atlas vs Non-Atlas: Atlas revenue grew 27% YoY and accounted for 71% of total revenue; Non-Atlas revenue declined ~13% YoY due to tough prior-year license timing; Atlas mix driving gross margin pressure.
- Gross Profit / Margin: Gross profit $360.8 million; gross margin 75% (vs 78% YoY); margin pressure driven by higher Atlas mix and lower high-margin upfront license revenue.
- Operating performance (non-GAAP): Non-GAAP operating income $52.5 million; non-GAAP operating margin approximately 11% for the quarter.
- Net income / EPS (GAAP vs non-GAAP): GAAP net income reported as $59 million (per the earnings call) or -$54.5 million in the data set depending on accounting treatment; non-GAAP metrics imply a positive operating trajectory. GAAP per-share figures were around $0.70 based on ~83.8 million diluted shares; management highlighted non-GAAP guidance for the coming quarters.
- Cash flow and liquidity: Cash, cash equivalents, and short-term investments totaled roughly $2.3 billion. Operating cash flow was negative ~$1.4 million; free cash flow around -$4.0 million. Q2 included a cash inflow of $170.6 million from capped-call settlements related to 2024 convertible notes. Management notes front-loaded cloud-provider prepayments will cap near-term cash flow by about $20 million per quarter in H2, with IPv4 address acquisitions (~$20–$25 million in CapEx in Q3) anticipated to lower long-term cloud costs.
- Customer/trend metrics: Total customers >50,700; Atlas customers >49,200; 2,189 customers with at least $100k ARR; Net ARR expansion rate ≈ 119% (lower than peak levels due to smaller incremental expansion from larger customers).
- Guidance (Q3 and FY25): Q3 revenue guidance of $493–$497 million; non-GAAP OI of $57–$60 million; non-GAAP EPS of $0.65–$0.68 (based on ~84.6M diluted shares). Full-year FY25 guidance: revenue $1.92–$1.93 billion; non-GAAP OI $187–$195 million; non-GAAP EPS $2.33–$2.47 (based on ~84.3M diluted shares). A non-GAAP tax provision of ~20% is assumed for the quarter and year.
Income Statement
Metric
Value
YoY Change
QoQ Change
Revenue
478.11M
12.82%
6.11%
Gross Profit
349.86M
9.86%
7.59%
Operating Income
-71.44M
-45.79%
27.24%
Net Income
-54.53M
-45.04%
32.34%
EPS
-0.74
-39.62%
32.73%
Key Financial Ratios
currentRatio
5.03
grossProfitMargin
73.2%
operatingProfitMargin
-14.9%
netProfitMargin
-11.4%
returnOnAssets
-1.74%
returnOnEquity
-4%
debtEquityRatio
0.9
operatingCashFlowPerShare
$-0.02
freeCashFlowPerShare
$-0.03
priceToBookRatio
13.62
priceEarningsRatio
-85.09
Net Income vs. Revenue
Expense Breakdown
Management Commentary
Management and Q&A insights by theme:
- Strategy and AI positioning: Dev Ittycheria emphasised the enduring AI opportunity and MongoDB’s run-anywhere strategy as core differentiators, stating that 'AI continues to be an additional long-term opportunity for our business' and that MongoDB is the 'ideal data layer for AI apps.' He highlighted MAAP (MongoDB AI Applications Program) as a vehicle to accelerate AI deployments via partnerships with AWS, Azure, GCP, Accenture, Anthropic, and Cohere. Quote: 'MAAP brings together a unique ecosystem including the three major cloud providers, AWS, Azure, and GCP, as well as Accenture and AI pioneers like Anthropic and Cohere.'
- Platform momentum and execution: Michael Gordon noted Atlas growth of 27% YoY and Atlas now representing 71% of revenue, signaling successful shift to a higher-margin, cloud-first business model. He observed Atlas consumption was 'modestly ahead of updated expectations' in Q2, even as overall guidance assumed more challenging headwinds. Quote: 'Atlas grew 27% in the quarter and now represents 71% of the total revenue.'
- Macro context and demand environment: Dev explained macro softness in Q1 affecting consumption of existing workloads, with Q2 showing similar trends but with continued strength in new business, reinforcing the view that the macro impact is primarily on consumption, not new customer wins. Quote: 'In Q1, we did see broad-based consumption growth slowdown, suggesting some macro softening.'
- AI design and data architecture: Dev articulated MongoDB’s architectural advantages for AI workloads, noting the ability to unify source, vector, metadata, and generated data alongside live operational data, and emphasized RAG-based approaches with flexible LLMs. Quote: 'AI-driven workloads require the underlying database to be capable of processing queries against rich and complex data structures quickly and efficiently.'
AI continues to be an additional long-term opportunity for our business.
— Dev Ittycheria
Atlas grew 27% in the quarter and now represents 71% of revenue.
— Michael Gordon
Forward Guidance
Assessment of management guidance and outlook:
- Revenue trajectory: Q3 revenue guidance of $493–$497 million and full-year $1.92–$1.93 billion imply sequential growth aided by stronger-than-expected Atlas momentum and a more constructive EA pipeline entering H2. Management attributes Atlas’s higher starting ARR for H2 and EA pipeline strength as primary drivers of the raised outlook.
- Margin trajectory: The company is guiding to ~10% operating margin at the midpoint for FY25, supported by revenue outperformance and disciplined spend timing. The path to higher margins remains contingent on mix benefits (Atlas vs EA), continued cost discipline, and moderation of AI-related investments.
- Cash flow and capital allocation: Cash flow will be buffered by upfront cloud-payments that boost gross margins but depress operating cash flow by roughly $20 million per quarter in H2. Capex in Q3 (~$20–$25 million for IPv4 addresses) aims to reduce cloud costs over the long term.
- Risks and monitoring factors: Monitor Atlas consumption growth versus the base, the timing of AI monetization, and macro-driven demand dynamics, particularly consumption softness in existing workloads. Key investor watchpoints include MAAP adoption rates, Vector/Search usage growth, enterprise migrations from relational databases, and the durability of EA pipeline beyond initial AI-driven pilots.
- Bottom line assessment: The guidance suggests management is confident in continued share gain in a large, under-penetrated market with meaningful AI-enabled opportunities. Achievability hinges on sustaining Atlas growth, converting EA pipeline into revenue, and managing operating expenses amid ongoing product investments.
Competitive Position
Company
Gross Margin
Operating Margin
Return on Equity
P/E Ratio
MDB Focus
73.17%
-14.90%
-4.00%
-85.09%
CRWD
75.40%
1.42%
1.65%
301.08%
OKTA
76.00%
-2.94%
0.47%
136.55%
NET
77.80%
-8.61%
-1.71%
-474.16%
PANW
74.70%
11.70%
40.10%
15.48%
Gross Profit Margin
Operating Profit Margin
Return on Equity
P/E Ratio Comparison
Investment Outlook
MDB presents a differentiated multi-year growth thesis anchored in Atlas-driven cloud-native expansion and a rising AI monetization path via MAAP, Vector/Search, and streaming capabilities. The QQ2 2025 results validate a durable demand backdrop for a modern, flexible data layer capable of supporting AI workloads and legacy modernization projects. Management’s guidance for FY25 implies continued revenue growth with improving margins and measured capital allocation (cloud prepayments and IPv4 capex) to improve cost structure over time. The primary investment considerations are: (1) the pace of AI monetization and customer adoption, (2) macro demand signals and how they affect consumption, and (3) execution efficiency to convert EA pipeline into sustained revenue. With substantial liquidity, a large addressable market (>$80B legacy relational database opportunity), and a credible AI-enabled product roadmap, MDB warrants a bullish but data-driven stance for a 12–24 month horizon, subject to macro sensitivity and AI monetization progression.
Key Investment Factors
Growth Potential
MongoDB benefits from a multi-pronged growth runway: (1) Atlas-driven cloud-native database growth across 118 cloud regions and three hyperscalers; (2) AI-enabled data workloads via MAAP, Vector Search, and streaming capabilities; (3) enterprise modernization of legacy relational databases, backed by AI-assisted code modernization pilots with strong early feedback; (4) EA as a complementary and durable recurring revenue stream with multi-year sizing; (5) potential cross-sell opportunities into EA customers leveraging the run-anywhere strategy. Management underscored the enduring tailwinds of AI and the cost-efficiency of building AI-enabled apps on MongoDB, suggesting a long runway for revenue expansion.
Profitability Risk
Key risks include: (1) macro consumption softness that could persist and pressure existing workload growth; (2) timing and monetization risk around AI apps, given a high degree of enterprise experimentation; (3) competitive pressure from relational ecosystems and evolving database technologies; (4) execution risk in maintaining high-velocity Atlas growth while achieving meaningful AI monetization; (5) potential margin compression if AI-related investments accelerate beyond plan or if Atlas mix shifts unfavorably.
Financial Position
The company maintains a robust liquidity position with roughly $2.3 billion in cash, cash equivalents, and short-term investments, and a net debt position of about -$66 million (net cash). Total assets stand at approximately $3.13 billion, with long-term debt of about $1.21 billion. The balance sheet supports ongoing investments in AI and platform enhancements, while recent capex and upfront cloud-prepayment strategies are expected to improve gross margins over time and reduce cloud infrastructure costs. The business exhibits strong ARR growth indicators (Net ARR expansion ~119%, >50k customers including >49k Atlas customers) but remains margin-resilient only via continued mix optimization and efficient go-to-market execution.
SWOT Analysis
Strengths
Strong Atlas growth and high share of revenue (Atlas ~71% of total in QQ2 2025) with 50,700+ total customers.
Run-anywhere platform with multi-cloud flexibility (118 global regions across 3 hyperscalers) supporting diverse customer needs.
MAAP (AI Applications Program) accelerates AI adoption via ecosystem partnerships (AWS, Azure, GCP, Accenture, Anthropic, Cohere).
Robust liquidity position (approx. $2.3B in cash and equivalents) and data-driven upsell opportunities (EA, vector/search, streaming).
Weaknesses
Near-term GAAP profitability challenges; margin pressure from higher Atlas mix and gradual AI monetization.
Cash flow sensitivity to upfront prepayments and capex for IPv4 addresses; potential volatility in free cash flow in H2 2025.
Relatively high valuation metrics (e.g., price-to-sales in the ~38x range) reflect growth expectations and AI upside, which heightens sensitivity to guidance misses.
Opportunities
AI-enabled workloads as a primary growth lever (Vector Search, Search, Streaming) and accelerated modernization of legacy relational databases.
Expansion of EA with larger multi-year deals and cross-sell within existing customers following Atlas adoption.
Global enterprise migrations and on-prem to cloud transitions leveraging run-anywhere architecture.
Threats
Macro headwinds impacting consumption of existing workloads could dampen near-term revenue growth.
Competitive pressure from Postgres/open-source ecosystems and other cloud-native databases; risk of migration inertia in large enterprises.
Execution risks in AI monetization, regulatory/compliance concerns, and potential shifts in AI tooling ecosystems.
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