Compare moats
Up to three covered companies, band by band. Every call is a curated editorial judgment, never a disclosed figure — and every band carries its cited basis.
| Nebius Group | Applied Digital | Snowflake | |
|---|---|---|---|
| Moat rating | narrow The FY2025 20-F positions Nebius as 'one of the few global, at scale, multi-tenant clouds purpose built for AI,' but the same filing names its central dependency plainly: 'We currently rely on Nvidia for the GPU chips we use' — a purpose-built neocloud renting a supply the hyperscalers it competes with also control, which is a real but narrow position. | none The FY2026 10-K (filed 2026-07-29) shows contracted revenue, not a demonstrated competitive edge. About 1,410 MW is leased under 15-year take-or-pay, non-cancellable base terms worth about $36.2 billion, but only about 100 MW of the roughly 1.5 GW that is contracted and either operating or under construction was operating and earning revenue at May 31, 2026, and Item 1A says "lessees may have the right to terminate applicable leases if there are significant delays in construction." Item 1A also concedes "We do not have the resources to compete with larger providers of similar products or services at this time," and the Competition section names 13 power-advantaged developers the company competes with. Signed leases give revenue visibility, but the filing does not show a durable advantage. | narrow Narrow, not wide, because the FY2026 10-K documents a strong installed base and a competitive position the company itself says is under erosion. On the asset side: revenue of $4.7 billion (29% growth in each of the last three fiscal years), 13,328 total customers up from 10,996, 790 of the Forbes Global 2000 contributing about 43% of revenue, 733 customers above $1 million in trailing-12-month product revenue up from 576, a 125% net revenue retention rate, and more than 1,050 issued U.S. patents. Against that, Item 1A states plainly that adopting open data formats like Apache Iceberg means 'there is less customer “lock in” when our products are used in external environments' and that 'our support of open data formats may also reduce switching costs between us and our competitors'; that AWS, Azure and GCP 'generally compete in all of our markets' while also supplying the infrastructure a 'substantial majority of our business is run on'; and that the company remains loss-making at $1.3 billion of net loss for the year. |
| Moat type | cost scale The moat the filing describes is engineering: designs that 'optimize power and cooling efficiency, lower latency' plus 'a consistent track record of being one of the first-to-deploy the latest generation of NVIDIA GPU chips' — density and time-to-deploy at scale, not a switching lock. | none The 10-K claims three advantages: power-advantaged sites (it believes securing power and interconnection ahead of demand is 'the principal constraint on new HPC capacity and a core differentiator for us from many of our competitors'), a standardized 'franchise-style' design, and hyperscaler master service and master telecom service agreements 'that are difficult to obtain.' The filing does not show any of them to be durable. Its Competition section says competition 'centers on securing and developing sites with access to large-scale, reliable, and cost-competitive power and interconnection' and names 13 power-advantaged developers going after the same leases, and Item 1A concedes it lacks the resources to compete with larger providers. Signed leases are take-or-pay and non-cancellable, so a tenant leaving for convenience owes 'the full remaining contractual value,' but that is contractual lock-in on each lease rather than a moat source, so no moat type is assigned. | switching costs The filing makes its own affirmative claim of network effects — 'Our business benefits from powerful network effects. ... The more customers adopt our platform, the more data can be exchanged with other Snowflake customers, partners, data providers, and data consumers' — but the load-bearing, quantified evidence in the document points to switching costs. The platform is sold as the way to 'consolidate data into a single source of truth,' and the disclosed economics of that consolidation are a 125% net revenue retention rate and 733 customers above $1 million in trailing product revenue. Item 1A confirms the mechanism by naming what is at risk: open formats produce 'less customer “lock in”' and 'may also reduce switching costs.' The filing frames lock-in, not network density, as the thing erosion would take away. |
| Leadership | fast follower The 20-F's own claim is 'one of the FEW global, at scale' AI clouds — a differentiated challenger to the hyperscalers it names as the competitive field, not a claimed leader of it; the first-to-deploy record is a follower's speed advantage, not category leadership. | behind The 10-K makes no leadership claim and gives no ranking or share figure. Item 1A concedes "We do not have the resources to compete with larger providers of similar products or services at this time" and that some rivals have "substantially greater liquidity and financial resources than we do." Its Competition section places APLD against established operators (Digital Realty, Equinix), hyperscalers that build their own capacity, independent developers and 13 named power-advantaged developers (IREN, Cipher Digital, TeraWulf, Hut 8, Riot, CleanSpark, HIVE, Core Scientific, Bitdeer, Galaxy Digital, Fermi, Keel Infrastructure, MARA). | co leader The 10-K contains no ranking, market-share figure, or claim of leadership, and it names no non-hyperscaler competitor by name. The band rests on disclosed scale — $4.7 billion of revenue, 13,328 customers, 9,060 employees across 36 countries — set against the filing's own statement that 'many of our competitors have substantially greater brand recognition, customer relationships, and financial, technical, and other resources than we do.' Co-leader among independent cloud data platforms; not a leader over AWS, Azure and GCP, which the filing says compete in all of its markets. |
| Pricing power | weak The filing frames a 'highly competitive' market with 'frequent introduction of new or improved solutions' and a GPU cost base set by a single supplier (NVIDIA) — a renter of compute competing on efficiency has little list-price control. | weak Item 1A says "Due to the limited number of hyperscalers, we expect that a limited number of customers will continue to account for a high percentage of our revenue for the foreseeable future," and that if customers' equipment usage declines or they discontinue use of its facilities, APLD "may be compelled to lower our lease prices in some instances or risk losing a significant customer." One customer was 59% of FY2026 revenue from continuing operations. Take-or-pay, non-cancellable terms protect contracted revenue over the base term, and Note 19 reports a $39.1M HPC Hosting segment profit on $385.3M of segment revenue in FY2026, but those terms are agreed with a small group of concentrated buyers. | moderate The consumption model plus 125% net revenue retention shows real expansion pricing, and the filing argues it competes on 'pricing transparency and optimized price-performance.' But Item 1A limits how far that goes: competition 'may negatively impact our ability to acquire new customers ... put downward pressure on our prices and gross margins'; the company 'may not be able to ... offer as many discounts or free services as our competitors'; results depend on 'changes in our pricing model, including in response to significant price discounts by our competitors' and on 'customer optimization efforts that result in reduced consumption.' On the cost side, 'our costs and gross margins are significantly influenced by the prices we are able to negotiate with these public cloud providers, which in certain cases are also our competitors.' |
| Summary | Nebius sells a 'unified full-stack AI cloud that spans the complete AI journey – from compute capacity to software and services,' with hardware and software built in-house — the neocloud pitch of hyperscaler reliability at purpose-built efficiency, and a first-to-deploy record on new NVIDIA silicon. Two things bound the moat, both from the filing: it 'currently rel[ies] on Nvidia for the GPU chips,' the same constraint every neocloud shares, and it is a Nasdaq 'Controlled Company' whose founding shareholder holds concentrated voting power. The three non-core segments (Toloka, Avride, TripleTen) are separate businesses, not the cloud moat. | Applied Digital designs, builds and operates purpose-built, liquid-cooled HPC data centers, which it calls 'AI factories', and leases the capacity to CoreWeave and investment-grade hyperscalers. At May 31, 2026 its 10-K lists five campuses (Polaris Forge 1-3 and Delta Forge 1-2) with about 1,410 MW contracted under roughly 15-year take-or-pay, non-cancellable leases worth about $36.2 billion over the base terms. The filing claims three sources of advantage: it controls power-advantaged sites, it uses a standardized 'franchise-style' design built to deliver about 150 MW in about 14 to 18 months, and it holds hyperscaler master agreements that are 'difficult to obtain.' The same document shows how early the company is. About 100 MW was operating and earning revenue. One customer was 59% of FY2026 revenue from continuing operations. It competes with Digital Realty, Equinix, hyperscalers that build their own capacity and 13 named power-advantaged developers, and it concedes that it lacks the resources to compete with larger providers. Signed leases give long-dated revenue visibility, but the filing does not show a durable competitive advantage. | Snowflake's advantage in its FY2026 10-K rests on being the consolidation point for enterprise data: a multi-cluster shared-data architecture with proprietary columnar storage and automatic micro-partitioning, delivered across three major public clouds and 53 interconnected regional deployments, that customers adopt as a single governed source of truth and then expand on — 125% net revenue retention, 790 of the Forbes Global 2000 as customers. The filing layers a collaboration claim on top, with sharing 'generally without copying or moving the underlying data' and a Marketplace of 'hundreds of live, ready-to-query third-party data sets and data products.' The same document is unusually candid about the counter-pressure: Iceberg and open formats reduce lock-in by the company's own account, the three hyperscalers compete across every market while setting the cloud costs that 'significantly influence' gross margins, and frontier AI model providers 'may seek to vertically integrate ... by expanding into the data storage and management layers.' |
| Chain position | Layer-8 neocloud — a purpose-built AI compute provider reselling NVIDIA silicon at scale. | Developer and landlord of power-advantaged, liquid-cooled AI data-center capacity, leased long-term to CoreWeave and investment-grade hyperscalers. | Sits at the enterprise data and governance layer of the AI stack, and the AI exposure is explicit rather than incidental: the filing brands the product the 'AI Data Cloud,' lists AI as a product category, and put Snowflake Intelligence, Cortex Agents and a Managed MCP Server into general availability during the fiscal year. It is a buyer of hyperscaler compute and of third-party frontier models — 'strategic partnerships with foundational model providers deliver state-of-the-art models natively within Snowflake Cortex AI,' with stated 'model neutrality' — and a supplier of governed enterprise data and GPU-backed managed compute to AI applications built on top. |
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| Long-horizon vote | -0.01 at weight 0.20 · swarm neutral Editorial prior, not backtested. | -0.20 at weight 0.20 · swarm neutral Editorial prior, not backtested. | +0.13 at weight 0.20 · swarm neutral Editorial prior, not backtested. |