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Short answer: compare Oracle, Amazon Web Services (AWS), Microsoft Azure and Google Cloud on like-for-like reporting periods and segment definitions before ranking them. Oracle is much smaller than the hyperscalers, but its database-led cloud strategy and management’s forecast for more than 40% total-cloud growth in FY2026 give it a faster-growth profile than its FY2025 infrastructure figures alone suggest. AWS remains the scale and disclosed cloud-profit leader. Azure reported strong growth but does not provide a directly comparable Azure operating-profit line in the cited annual report. Google Cloud has become materially profitable, although Alphabet’s company-wide artificial-intelligence spending is not allocated to that segment.
The right investment choice depends on what you value: growth acceleration, current cloud profit, balance-sheet resilience, AI capacity, customer diversification or valuation. No single winner can be declared from the cited figures because they cover different fiscal periods and do not include a synchronized market-multiple snapshot.
Start by making the comparison fair
Cloud companies use different fiscal calendars, segment names and disclosure policies. A headline percentage can therefore look more precise than it is. Oracle’s infrastructure cloud services and license support figure combines infrastructure-related cloud revenue with license-support revenue, while AWS reports a distinct cloud segment. Microsoft publishes Azure growth but not a standalone Azure operating-income line in the cited annual report. Alphabet reports Google Cloud revenue and operating income, but costs for research and development at the Alphabet level are not allocated in the same way as a pure-play cloud statement.
Before ranking any stock, create a worksheet with one column for each company and record the period, currency basis, segment definition and whether each number is reported, calculated or management guidance. Keep Oracle FY2025 separate from Amazon’s 2025 reporting year, Microsoft FY2025 and Alphabet’s 2025 results. If you combine periods, label the result as an approximation rather than a direct comparison.
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Use the narrowest comparable revenue measure
- Oracle: separate infrastructure cloud services and license support from broader cloud applications and other cloud-related revenue. The infrastructure figure is not a pure OCI-only measure.
- AWS: use the AWS segment’s reported sales and operating income.
- Azure: use the disclosed Azure and other cloud services growth rate, but do not manufacture an Azure operating margin from Microsoft’s consolidated accounts.
- Google Cloud: use the Google Cloud segment’s operating income and run-rate commentary, while distinguishing that from Alphabet’s consolidated results.
This discipline prevents a common error: comparing Oracle’s support-inclusive infrastructure number with a hyperscaler’s entire cloud segment and then treating the difference as market share.
What the latest disclosed figures actually show
| Company and measure | Reported figure | Period and qualification | How to interpret it |
|---|---|---|---|
| Oracle infrastructure cloud services and license support | $24.646 billion; 16% reported growth, or 17% in constant currency | Oracle FY2025; includes license support, so it is broader than infrastructure consumption alone | A smaller base with meaningful growth, but not directly equivalent to AWS, Azure or Google Cloud segment revenue |
| Oracle total-cloud outlook | Growth expected to rise from 24% to more than 40% | Management forecast from FY2025 to FY2026; forward-looking and dependent on capacity and demand | Evidence of expected acceleration, not a guaranteed result or a reported FY2026 outcome |
| AWS sales | Approximately $128.7 billion, up 20% | Amazon 2025 reporting year | The largest disclosed cloud scale in this comparison |
| AWS operating income | $45.606 billion | Amazon 2025 reporting year | The clearest disclosed cloud operating-profit pool among the four |
| Azure and other cloud services growth | 34% | Microsoft FY2025 | Strong growth, but Microsoft does not provide a directly comparable Azure operating-income line in the cited annual report |
| Google Cloud operating income | $13.910 billion, versus $6.112 billion in 2024 | Alphabet 2025 | Profitability improved sharply, although Alphabet-level AI research costs are not allocated to Google Cloud |
| Google Cloud annual run rate | More than $70 billion | Alphabet commentary at the end of 2025 | A forward-looking scale indicator, not the same as recognized annual revenue |
Oracle: smaller scale, database-led optionality
Oracle’s FY2025 infrastructure cloud services and license support revenue was $24.646 billion, with reported growth of 16%, or 17% on a constant-currency basis. Because license support is included, this line should not be described as OCI infrastructure consumption alone. It is best used as a measure of Oracle’s infrastructure-related recurring cloud and support economics.
Oracle reported FY2025 GAAP operating income of $17.7 billion. That is a company-wide figure, not a standalone OCI margin, so it should not be placed in the same margin column as AWS or Google Cloud without a segment bridge. The figure does, however, show that Oracle already operates a profitable software and cloud-support business while it expands infrastructure capacity.
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Management forecast total cloud growth rising from 24% in FY2025 to more than 40% in FY2026. This is a forecast rather than a reported result. It depends on Oracle delivering enough data-center capacity, converting signed demand into billable usage and sustaining customer spending. A forecast above 40% can materially change the growth ranking, but investors should test it against quarterly revenue, remaining performance obligations, capital spending and delivery timing as results arrive.
The multicloud database angle
Oracle’s strategic distinction is the placement of its database and related services on competing clouds. Larry Ellison said, “MultiCloud database revenue from Amazon, Google and Azure grew 115% from Q3 to Q4.” Treat that statement as management commentary, not as independent market-share evidence. The useful investment question is whether multicloud placements expand Oracle’s distribution and retention without forcing it to fund every element of the customer’s infrastructure.
A database that remains embedded in an enterprise application estate can create switching costs, but those costs are not automatically equivalent to hyperscaler-wide infrastructure scale. Evaluate contract duration, workloads that have actually migrated, consumption growth and the economics Oracle keeps after paying for partner-cloud capacity.
AWS: the benchmark for disclosed cloud scale and profit
AWS reported approximately $128.7 billion in 2025 sales, up 20%, and $45.606 billion in operating income. On the disclosed figures, AWS has the largest revenue base and the largest operating-profit pool in this comparison. That scale can support a broad service catalog, a large developer ecosystem and geographically distributed infrastructure, while also giving management more data from which to optimize utilization.
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What the scale does and does not prove
AWS’s size is a powerful competitive advantage, but it is not a guarantee of superior stock returns. A large business must add substantial absolute revenue to maintain a high growth rate. Its infrastructure footprint also requires continuing investment in data centers, networking and specialized AI hardware. When evaluating AWS, compare incremental operating income and free-cash-flow conversion with the capital required to support the next growth phase.
The $45.606 billion operating-income figure is segment operating income, making it more useful for cloud profitability comparisons than a parent-company margin. It still does not reveal the return earned on every dollar of infrastructure or the profitability of each service family, so pair it with capital-intensity and return-on-invested-capital measures.
Azure: strong disclosed growth with a reporting limitation
Microsoft reported 34% growth for Azure and other cloud services in FY2025. That rate is higher than Oracle’s FY2025 infrastructure cloud-services-and-license-support growth, but the definitions and periods differ. Azure’s label includes “other cloud services,” and Microsoft does not provide a directly comparable Azure operating-income line in the cited annual report.
How to analyze Azure without inventing a margin
- Record the 34% growth rate with the Microsoft FY2025 period and the exact “Azure and other cloud services” definition.
- Use Microsoft’s reported company and segment disclosures for revenue, gross-profit commentary and cash flow where available, but do not divide an unrelated Microsoft operating-profit figure by Azure revenue and call it an Azure margin.
- Assess Azure’s growth quality through commercial bookings, enterprise commitments, usage expansion and the mix of infrastructure, platform and AI services when Microsoft discloses those details.
- Compare Microsoft’s capital spending and depreciation with the growth of its broader cloud and AI businesses, recognizing that those costs support more than Azure alone.
Azure can rank highly on growth while remaining difficult to rank on standalone operating profit. That is a disclosure issue, not proof that Azure is either more or less profitable than AWS or Google Cloud.
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Google Cloud: a clearer profitability inflection
Google Cloud reported $13.910 billion of operating income in 2025, up from $6.112 billion in 2024. The improvement indicates that the segment has moved beyond a scale-only narrative and is producing a material operating contribution. Alphabet also said Google Cloud’s annual run rate exceeded $70 billion at the end of 2025.
Read the run rate correctly
An annual run rate extrapolates a recent revenue pace; it is not identical to recognized revenue for the full year. Use the more-than-$70-billion figure to discuss current scale and momentum, not to replace reported revenue in a valuation multiple.
Account for Alphabet-level AI spending
Alphabet’s consolidated 2025 revenue was $402.836 billion and its operating margin was 32%. Those company-wide figures include businesses and costs outside Google Cloud. In particular, Alphabet-level AI research costs are not allocated to Google Cloud in the cited segment reporting. Google Cloud’s $13.910 billion operating income therefore should not be interpreted as the fully loaded economic profit of every AI capability that supports the segment.
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The correct comparison is to place Google Cloud’s segment operating income beside AWS’s segment operating income, then separately discuss the allocation boundary. Do not infer that Google Cloud would earn the same margin if all parent-level AI research and infrastructure costs were charged to it.
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| Dimension | Current read from the disclosures | Investor question to answer next |
|---|---|---|
| Cloud growth | Oracle reports 16% growth for its infrastructure cloud services and license support line and guides to more than 40% total-cloud growth in FY2026; AWS grew 20%; Azure and other cloud services grew 34%; Google Cloud’s disclosed run rate exceeded $70 billion | Is acceleration converting into recurring, profitable consumption, or is it a temporary capacity or comparison effect? |
| Segment operating profit | AWS reports $45.606 billion; Google Cloud reports $13.910 billion; Oracle’s $17.7 billion is GAAP company-wide; Azure’s comparable line is not stated in the cited annual report | Which costs are included in each segment, and how much parent-company spending sits outside the segment? |
| Capital intensity | All four businesses require data-center, networking and AI infrastructure investment; synchronized capex and depreciation figures are not provided here | How much revenue and free cash flow does each incremental infrastructure dollar produce? |
| Free cash flow | No synchronized free-cash-flow figures are supplied for the four cloud segments | Use each parent’s same-period cash-flow statement and reconcile operating cash flow, capital expenditure and working capital. |
| Balance-sheet risk | No synchronized net-debt or liquidity snapshot is supplied | Measure net debt, maturities, lease commitments, interest coverage and the ability to fund AI capacity through a downturn. |
| AI capacity | AI demand is a major reason for infrastructure expansion, but capacity delivery and cost recovery remain execution risks | Are accelerators available when customers need them, and do prices cover depreciation, power and financing costs? |
| Customer concentration | Comparable concentration percentages are not stated | Check whether a few large contracts or AI customers drive reported growth and whether those commitments are cancellable. |
| Valuation | The cited filings do not provide a synchronized market-multiple snapshot | Refresh prices, shares, debt, cash and forward estimates on one date before drawing a valuation conclusion. |
Capital intensity, free cash flow and returns
Cloud revenue growth can coexist with weaker near-term cash conversion when a company builds capacity ahead of demand. AI infrastructure makes this tension more visible because accelerators, high-bandwidth networking, power systems and data-center construction require large upfront outlays. Depreciation follows the deployment schedule, while customer revenue may ramp later.
Build a comparable cash-flow bridge
- Collect each parent company’s operating cash flow and capital expenditure for the same reporting period.
- Separate maintenance spending from growth spending where the company discloses the distinction. If it does not, mark the split as unavailable rather than estimating it.
- Review depreciation and amortization, finance leases, construction commitments and purchase obligations, because reported capex alone may understate the resources committed to capacity.
- Calculate free cash flow as operating cash flow minus capital expenditure using the company’s stated definitions, then explain any nonstandard adjustments.
- Compare free-cash-flow growth with cloud-revenue growth and segment operating income. A widening gap can indicate deliberate capacity investment, lower pricing, working-capital pressure or weaker collection.
- Use return on invested capital only when invested capital is defined consistently. Do not compare an asset-light software calculation with a data-center-heavy calculation without adjusting the denominator.
AWS’s large operating-profit pool can fund expansion, while Oracle’s smaller base may produce faster percentage growth if capacity arrives on schedule. Google Cloud’s improved operating income is encouraging, but the parent-level allocation boundary matters. Azure requires the most caution because a standalone operating-profit figure is not provided in the cited report.
Scale, moat and switching costs
Scale is more than revenue. Examine the installed enterprise base, application and database dependencies, developer tools, geographic availability, service breadth, reliability history and the cost of moving data and workloads.
Oracle’s database and enterprise relationships
Oracle can use existing database and enterprise-application relationships to place workloads across its own infrastructure and partner clouds. That may lower customer acquisition friction and support multicloud adoption. The trade-off is that Oracle’s infrastructure footprint and service breadth are smaller than those of the hyperscalers, so capacity, geography and service coverage must be checked for each workload.
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Hyperscaler ecosystems
AWS, Azure and Google Cloud each combine infrastructure with platform services, developer tooling and AI products. Their ecosystems can raise switching costs because a customer may depend on identity, data pipelines, observability, databases, security controls and proprietary APIs. Ecosystem breadth is valuable only when customers use those services deeply enough to make migration expensive; logo counts alone do not measure lock-in.
Customer concentration
Large cloud contracts can accelerate growth while increasing concentration risk. Ask whether a small number of AI or enterprise customers account for a material share of new capacity, whether commitments are take-or-pay, and how quickly a provider could redeploy hardware if a customer delays deployment. Use disclosed concentration data; when it is not available, mark the risk as unresolved rather than assuming diversification.
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AI capacity: opportunity and execution test
AI workloads can increase demand for compute, networking and storage, but the economics depend on utilization and pricing. A provider may report strong bookings before it has delivered the required capacity, or it may deploy expensive hardware whose useful life and resale value are uncertain.
- Capacity delivery: verify data-center, power and accelerator availability against the timing of customer commitments.
- Utilization: track whether deployed hardware is producing billable usage rather than sitting idle while customers wait for software or data migration.
- Unit economics: compare revenue per accelerator or cluster with depreciation, energy, networking, support and financing costs.
- Supply and obsolescence: consider delivery lead times and the risk that a new accelerator generation reduces the economic life of existing equipment.
- Customer funding: distinguish customer-funded commitments from capacity built speculatively on the provider’s balance sheet.
Oracle’s more-than-40% FY2026 total-cloud forecast is especially sensitive to capacity delivery and customer demand. AWS’s scale advantage comes with heavy infrastructure investment. Google Cloud’s profitability improvement demonstrates operating leverage, but it does not eliminate parent-level AI research costs. Azure’s growth rate is compelling, yet Microsoft’s reporting structure makes the return on AI investment harder to isolate.
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Multicloud can be either a growth channel or a margin complication. Oracle’s database availability on AWS, Azure and Google Cloud can expand distribution and let customers keep data near existing applications. The same arrangement may also require revenue sharing, interoperability work and support across organizational boundaries.
When analyzing Oracle’s multicloud strategy, track four items separately:
- Revenue recognized by Oracle for database and related services.
- Capacity or hosting costs paid to partner clouds.
- Net retention and expansion of customers using the service across multiple clouds.
- Whether multicloud deployments lead to additional Oracle applications, support or infrastructure consumption.
Management’s statement that multicloud database revenue from Amazon, Google and Azure grew 115% from Q3 to Q4 indicates rapid sequential momentum, but it does not state the starting dollar base, annual growth rate or market share. A small base can produce a large percentage increase. Use the statement as a strategic signal and wait for reported revenue and margin evidence before assigning a long-term valuation premium.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to compare valuation without a misleading multiple
The cited filings do not provide current, synchronized share prices, market capitalizations, net debt, forward enterprise-value-to-sales, enterprise-value-to-EBIT or free-cash-flow yields. Any article or spreadsheet that ranks these stocks on a single current multiple without specifying the date and estimate set is mixing inputs.
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A repeatable valuation process
- Choose one market-close date and record the share price for each company on that date.
- Multiply diluted shares outstanding by the share price to obtain equity value, using the same share-count convention across companies.
- Add debt and lease liabilities and subtract cash and marketable securities according to a clearly stated enterprise-value policy.
- Use forward revenue, operating income and free-cash-flow estimates from the same forecast vintage. Do not pair a current share price with an old estimate for one company and a newer estimate for another.
- Calculate EV/sales, EV/operating income and free-cash-flow yield, then compare those multiples with growth, margin, capital intensity and balance-sheet risk.
- Run a sensitivity table for slower cloud growth, delayed AI capacity, lower utilization and higher capital spending. A high-growth stock can still underperform if the market has already priced in an aggressive forecast.
Oracle’s AI-infrastructure growth may be partly priced in at any given moment, but the supplied financial figures do not establish a current premium or discount. That question requires a synchronized market-data snapshot and explicit forward estimates.
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Which company fits which investment thesis?
| Investment priority | Candidate to investigate first | Why, and what could disprove the thesis |
|---|---|---|
| Largest disclosed cloud scale and current segment profit | AWS | Its $128.7 billion sales and $45.606 billion operating income provide the strongest disclosed scale and profit base; heavy infrastructure spending could reduce future cash returns. |
| Fast growth with a database-led multicloud angle | Oracle | FY2026 guidance above 40% total-cloud growth and multicloud distribution are attractive; capacity delivery, partner economics and the support-inclusive revenue definition require verification. |
| Strong reported percentage growth inside a broad enterprise platform | Azure | 34% FY2025 growth is substantial; the absence of a directly comparable Azure operating-income line limits margin analysis. |
| Improving standalone cloud profitability | Google Cloud | Operating income rose to $13.910 billion from $6.112 billion; parent-level AI research costs and the distinction between run rate and recognized revenue complicate fully loaded returns. |
This table identifies starting points, not recommendations. The same company can fit different portfolios depending on valuation, risk tolerance and the investor’s expected holding period.
A practical worksheet for quarterly updates
Update the comparison after every company reports, preserving the prior period so acceleration and deceleration are visible. Record the following fields:
- Fiscal period, currency and segment name exactly as reported.
- Cloud revenue, year-over-year growth and constant-currency growth where available.
- Operating income, operating margin and the costs included in the segment.
- Capital expenditure, depreciation, construction commitments and lease obligations.
- Operating cash flow, free cash flow and the company’s definition of each measure.
- Net debt, cash, maturities and interest expense.
- AI capacity delivered, utilization indicators and customer commitments when disclosed.
- Multicloud revenue, partner payments and retention metrics for Oracle.
- Largest customers or concentration measures, with “not stated” where no figure is provided.
- Share price, diluted shares, enterprise value and forward consensus estimates captured on one date.
Flag every number as reported, calculated or guided. That simple label prevents a management forecast such as Oracle’s more-than-40% FY2026 target from being mistaken for an achieved growth rate, and it keeps Google Cloud’s more-than-$70-billion run rate separate from annual recognized revenue.
Common comparison mistakes
Mixing fiscal years
Oracle FY2025, Amazon’s 2025 reporting year, Microsoft FY2025 and Alphabet 2025 do not automatically cover identical months. Show the period beside every percentage and use trailing-twelve-month calculations only when the underlying quarters are available.
Calling every Oracle cloud dollar OCI revenue
The $24.646 billion Oracle figure includes infrastructure cloud services and license support. Treating it as pure infrastructure consumption exaggerates the precision of an OCI-versus-AWS comparison.
Creating an Azure margin
Microsoft’s 34% Azure and other cloud services growth is valid as disclosed. Dividing Microsoft-wide operating income by Azure revenue is not a valid Azure margin. Leave the comparable cell unreported until Microsoft supplies the necessary segment data.
Ignoring allocation boundaries
Google Cloud’s operating income excludes Alphabet-level AI research costs that are not allocated to the segment. AWS and Google Cloud segment profits are useful, but they are not identical measures of fully loaded economic profit.
Equating growth with cash returns
AI capacity can lift revenue while depressing near-term free-cash-flow conversion. Always place capex, depreciation, commitments and utilization next to growth.
Using an unsynchronized stock multiple
A valuation comparison is only meaningful when price, share count, debt, cash and forward estimates come from the same date and methodology. The available disclosures do not supply that synchronized snapshot.
Bottom-line decision rule
Use AWS as the benchmark for disclosed cloud scale and segment operating profit, Oracle as the higher-upside but execution-sensitive database and multicloud case, Azure as a strong-growth platform whose standalone margin is not disclosed on a comparable basis, and Google Cloud as the clearest profitability-improvement story. Then test each thesis against capital intensity, free cash flow, balance-sheet risk, AI capacity, customer concentration and valuation on the same date. That process is more reliable than choosing a winner from one growth percentage or one headline multiple.
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