Hyperscale cloud growth accelerates for a fifth consecutive quarter; cloud software demand improves but the market bar rises as well

Overview

The report uses 2Q26 results from AWS, Microsoft Azure, and Google Cloud as leading indicators to assess demand for cloud infrastructure software. The three major cloud vendors’ combined revenue reached approximately $97.857 billion, up 48.1% year over year and accelerating meaningfully from the prior quarter. Demand improvement is coming not only from AI compute but also from cloud migration, core infrastructure, databases, and data analytics consumption, creating a positive read-through for DDOG, SNOW, and MDB. However, related stocks trade at high valuations, and investors’ requirements for growth and guidance are also rising.

Core views

First, artificial intelligence is shifting from buildout-driven to consumption-driven and is driving non-pure-compute demand such as CPU, core cloud resources, databases, agent memory, and retrieval. Second, momentum in cloud migration and core infrastructure is strengthening, indicating that demand improvement has a broad base. Third, data and analytics and databases remain strong areas, with Azure PostgreSQL revenue growing approximately 55% YoY and Fabric paid customers exceeding 40,000, up approximately 60% YoY. Fourth, DDOG benefits from observability spending and AI-native customer consumption, giving it the strongest fundamental read-through, but the market may require 2Q revenue growth of 35% to 36% and only modest deceleration in the second half. Fifth, SNOW benefits from AWS and analytics workload growth; MDB’s long-term AI opportunity is clear, but a significant inflection should not yet be expected this quarter, and it faces competition from managed PostgreSQL and other offerings.

Analysis framework

The report uses a hyperscale cloud vendor growth mapping approach, mapping AWS, Azure, and Google Cloud revenue growth, management demand commentary, and database and analytics product metrics to cloud software companies’ consumption trends; it also evaluates risk-reward by combining company growth expectations, free cash flow forecasts, comparable company valuations, and discounting methods.

Methodology notes

• Demand analysisHyperscale cloud vendor demand mapping

  Use large cloud platform results as leading indicators of cloud software consumption

  By comparing AWS, Azure, and Google Cloud revenue growth, net new revenue, and management commentary, the report assesses the demand impact of cloud migration, artificial intelligence, databases, and analytics workloads on DDOG, SNOW, and MDB.

• Valuation analysisFree cash flow multiple valuation

  Estimate value based on forward free cash flow and growth-adjusted multiples

  DDOG uses CY28 free cash flow per share of $4.65 and a 69x valuation multiple, discounted back one year; MDB references approximately $1.096 billion of free cash flow in 2029 and an approximately 37x multiple; SNOW uses approximately $4.2 billion of CY30 free cash flow and an approximately 39x enterprise value to free cash flow multiple, discounted to CY27 at an 11.1% discount rate.

• Relative valuationGrowth-adjusted comparable company valuation

  Measure the reasonableness of valuation premiums relative to growth rates

  The report compares DDOG with AI beneficiaries such as PLTR, CRWD, NET, and SNOW, and uses sales or free cash flow multiples divided by growth rates to test whether high valuations are supported by growth.

Asset mapping & comparison

Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).

• DDOG

  Cloud growth, AI workloads, and core infrastructure consumption increase observability demand, creating a direct positive catalyst.

  Strengths

  Enterprise core business may continue to improve from approximately mid-20% growth in 1Q; AI-native customer consumption is expected to accelerate; platform consolidation and new product adoption can support growth and margins.

  Weaknesses

  Valuation is high, and the market has strict requirements for 2Q growth and second-half guidance; adoption of non-observability products still needs to be validated.

  Comparison

  Among the infrastructure software companies covered in the report, DDOG and PLTR show the strongest partner channel growth signals; DDOG’s valuation is close to AI-beneficiary peers.

  Risks

  Intensifying competition, customers shifting to lower-cost alternatives, weak adoption of new products, and growth failing to meet the 35% to 36% market bar.

• SNOW

  Most consumption runs on AWS, so AWS growth acceleration and analytics workload expansion provide a positive read-through to product revenue.

  Strengths

  Data warehouse market share expansion, data-sharing network effects, and penetration into transactional workloads can expand the long-term market opportunity.

  Weaknesses

  The target price listed in the report is below the contemporaneous share price, and the current valuation already reflects strong growth expectations.

  Comparison

  Compared with MDB, SNOW has higher direct sensitivity to AWS consumption acceleration; compared with DDOG, its core read-through is more concentrated in data platform and analytics demand.

  Risks

  Competition may pressure pricing, growth, and margins, while expansion into adjacent data management and transaction processing scenarios may fall short of expectations.

• MDB

  AI agents’ demand for memory, retrieval, document databases, and vector databases provides a medium-term growth opportunity.

  Strengths

  Adoption of AI-optimized databases is accelerating; multi-cloud channel expansion, partner scaling, and replacement of legacy databases may support growth above 20%.

  Weaknesses

  The report does not expect a clear AI-driven inflection this quarter; the opportunity is more likely to materialize in later stages of CY26.

  Comparison

  Compared with SNOW and DDOG, MDB’s AI benefits are likely to materialize later, while its competition with Azure PostgreSQL, cloud-vendor-native databases, and open-source products is more direct.

  Risks

  Competition from legacy vendors, open-source databases, and cloud-native alternatives may intensify; Atlas customer expansion or consumption may slow; progress toward profitability and positive free cash flow may be slower than expected.

• PLTR

  Used as an AI-beneficiary comparable company and a company with strong partner growth to gauge cloud software valuation and demand sentiment.

  Strengths

  AI-related demand and partner channel growth are strong.

  Weaknesses

  This report does not provide an independent in-depth analysis of its fundamentals.

  Comparison

  Together with DDOG, CRWD, NET, and SNOW, it forms the AI-beneficiary comparable company group.

  Risks

  High valuation may amplify volatility if growth falls short of expectations.

Key data

• Combined 2Q26 cloud revenue of the three major cloud vendors$97,857 millionUp 48.1% YoY, versus 39.3% YoY growth in 1Q26.
• AWS 2Q26 revenue growthApproximately 37% YoYAccelerated for a fifth consecutive quarter, the fastest growth in 18 quarters; revenue was approximately $42,232 million.
• Microsoft Azure 2Q26 revenue growthApproximately 43% YoY in constant currencyApproximately 39% in the prior quarter, with management still indicating demand exceeded available capacity.
• Google Cloud 2Q26 revenue growthApproximately 81.8% YoYApproximately 63.4% in the prior quarter; the current quarter included initial TPU system sales revenue for the first time, but growth still accelerated significantly excluding this factor.
• AWS AI business annualized revenueOver $25 billionMaintained triple-digit YoY growth.
• Azure PostgreSQL revenue growthApproximately 55% YoYAccelerated for a third consecutive quarter, but also reflects competitive pressure facing MDB.
• Microsoft Fabric paid customersOver 40,000Up approximately 60% YoY, supporting the view that data and analytics demand remains strong.
• DDOG earnings market bar2Q revenue growth of approximately 35% to 36% YoYInvestors may also require second-half guidance to show only modest deceleration.
• DDOG target price and current price$300 / $288.15Corresponds to approximately 4.1% static implied upside.
• MDB target price and current price$380 / $380.04Corresponds to approximately 0.0% static implied upside.
• SNOW target price and current price$300 / $316.77Corresponds to approximately -5.3% static implied upside.

Impact & implications

At the industry level, broad-based acceleration in hyperscale cloud vendor growth validates improvement in the cloud consumption cycle, with artificial intelligence driving broader software demand across databases, data analytics, observability, and core compute. At the company level, DDOG receives the most direct benefits from consumption and observability, SNOW benefits from AWS and analytics demand, and MDB’s AI opportunity is more medium term. At the investment level, fundamental signals are positive, but upside from target prices relative to current prices is limited, meaning near-term returns depend more on materially better-than-expected results, upward guidance revisions, or further valuation expansion.

Risks

• Cloud software valuations and investor expectations are already elevated, so even with improving fundamentals, results that merely meet expectations may be insufficient to drive share prices.
• Hyperscale cloud vendor growth may be affected by capacity constraints, TPU system sales, and other structural changes, and may not fully pass through to software suppliers.
• Cloud-vendor-native databases, managed PostgreSQL, open-source products, and legacy vendors may intensify pricing and market share competition.
• Customer spending optimization or slowing consumption growth may affect DDOG observability, SNOW product revenue, and MDB Atlas growth.
• If AI investment does not translate into sustained software consumption and production workloads, current growth expectations may be revised downward.
• If new product adoption, platform consolidation, transactional workload expansion, and margin improvement fall short of expectations, valuation support will weaken.
• Morgan Stanley has shareholding, investment banking, or other service relationships with multiple covered companies, so conclusions should be read together with disclosures when assessing potential conflicts of interest.

What to watch

• Whether DDOG 2Q26 revenue growth can reach approximately 35% to 36%, and whether second-half guidance shows only modest deceleration.
• Whether SNOW product revenue and consumption trends can follow AWS growth acceleration and validate the pass-through of AI and data analytics demand.
• Whether MDB sees an AI database consumption inflection in subsequent quarters of CY26, and the trend in Atlas customer expansion.
• Whether AWS, Azure, and Google Cloud growth can continue to accelerate, and when Azure supply constraints will ease.
• Whether AI consumption continues to drive non-training workloads such as CPU, core cloud migration, databases, agent memory, and retrieval.
• The competitive impact of Azure PostgreSQL, Cosmos DB, and cloud-vendor-native products on independent database companies.
• Earnings thresholds, target price adjustments, and changes in growth-adjusted valuation multiples for high-valuation software companies.