Report:

Magic Quadrant for Strategic Cloud Platform Services

Top Vendor Products for Strategic Cloud Platform Services in 2025

• Amazon Web Services
• Google
• Microsoft
• Oracle

Strategic Cloud Platform Services Vendor Product Comparisons 2025

• Amazon Web Services - Leader
  

  Pros:

  • Largest public cloud community: AWS has built strong global community engagement for cloud professionals, providing significant opportunities for those who want to better understand and utilize AWS or deepen their skills. In addition to its flagship re:Invent conference, the company is hosting other in-person events for engaging technical and business audiences, including AWS re:Inforce and AWS Summits.
  • Cloud-inspired silicon: AWS has leveraged its global-scale cloud computing experience to develop custom silicon designs for both general-purpose (Graviton) and AI-specific (Inferentia and Trainium) application use cases. Custom chip design opens up opportunities for tighter and more performant integrations between hardware and software, as well as improved overall power efficiency and greater end-to-end control of supply chains.
  • Global scale and operational execution: AWS's significant share of global cloud market revenue has enabled it to build a larger and more robust network of integration partners than some other providers in this analysis, which in turn helps organizations successfully adopt cloud. AWS has had a robust overall availability record for many years, effectively navigating IT supply chain disruptions throughout the COVID-19 pandemic, as well as recent global demands for AI training GPU hardware.

  Cons:

  • Lagging in SaaS and nascent low-code capabilities: AWS lacks an extensive portfolio of SaaS applications, and does not appear in 2024's Gartner's list of top 20 SaaS vendors by global revenue, unlike other vendors in this analysis. In the emerging market for low-code application platforms, the company's recent launch of Amazon Q Apps and Amazon App Studio comes several years after some competitors' efforts to address the needs of modern business technologists building application workflows.
  • Minimal multicloud support: Only a few components of the AWS platform — such as Amazon ECS Anywhere, Amazon EKS Anywhere, Amazon Athena and AWS Systems Manager — can operate outside the AWS cloud; many services are restricted to AWS cloud or distributed cloud with branded AWS hardware only. While the company's 2024 announcement of a database partnership with Oracle is a good first step, there are many more areas where strategic multicloud partnerships will become important to enterprise customers in the years ahead, especially where GenAI is concerned.
  • A "marketplace" approach for GenAI models: AWS offers a range of AI models through partnerships and its Bedrock platform, including its own, such as Amazon Nova, which lag in industry benchmarks. While offering a wide range of GenAI models benefits customers, less performant first-party models provide less competitive differentiation in the intensely competitive AI landscape, as "AI gravity" begins to influence customer decisions.


• Google - Leader
  

  Pros:

  • A Google-wide AI strategy: The "new way to cloud" vision has driven innovations that position Google Cloud as a relevant platform for organizations seeking business transformation. This strategy aims to accelerate digital transformation through AI-powered innovation, establish a modern and adaptable infrastructure to support agile enterprise operations, ensure enterprise-class security and compliance, leverage enterprise data, and enhance collaboration through offerings such as Google Search and Google Workplace.
  • Leading the AI solutions stack: Google is a clear leader in AI services, providing best-of-breed solutions across all layers of the AI stack. Its capabilities begin at the infrastructure layer, with efficient custom silicon chips — such as Tensor Processing Units (TPUs) — designed to support frontier model training and inference. The Gemini family of AI models is recognized as among the highest-rated in industry benchmarks. Google further extends its AI capabilities through Agentspace to combine AI agents and AI-powered enterprise search.
  • A partner sovereign cloud offering: Google provides a comprehensive portfolio tailored to address the diverse and evolving sovereignty needs of customers across various industries, geographies and regulatory landscapes. Its offerings include the Google Cloud Data Boundary, which enables customers to utilize public regions with an added layer of control from a local partner; Google Cloud Dedicated, which offers a dedicated and isolated cloud region operated by a local partner; and the Google Cloud air-gapped solution, which can be dedicated to a single customer or operated by local partners to offer a trusted community cloud.

  Cons:

  • Support and account management consistency and quality: Gartner clients have raised concerns that Google has shown inconsistency in the quality of its technical field operations, including aftercare support for premium customers and support to their partner ecosystem, particularly outside North America.
  • Legacy application sensitivity: Google's innovations are grounded in cloud and AI, while it continues to enhance its support for legacy applications and processes. Google has made progress in supporting legacy requirements through its expanded partnership with VMware and support for enterprise applications such as SAP, but alienates some customers with its focus on cloud-native architectures and AI.
  • Loose integration between GCP and Google Workspace: Google has a broad portfolio of offerings spanning infrastructure, platform services and applications. However, there is no explicit and clear integration between GCP and Google Workspace. As a result, customers get little leverage between investments made in these offerings.


• Microsoft - Leader
  

  Pros:

  • AI integration: Microsoft was the first offering GenAI services and since then has successfully integrated AI into its broad portfolio. The company led all vendors in this evaluation at delivering AI into the hands of end users, culminating in real productivity gains.
  • A cross-product strategy: Azure uniquely and natively integrates with the company's broader portfolio — Microsoft 365, Dynamics 365, Fabric, Entra, Defender, Copilot, Teams and other offerings — to reduce complexity and risk and to improve productivity and collaboration. Additionally, Microsoft has integrated Azure services with its ecosystem of general-purpose developer tools (such as Power Platform, GitHub and Visual Studio) as well as third-party tools (such as Red Hat and Databricks products), making Azure compelling to developers worldwide.
  • Multicloud support: Through its Azure Local, Azure Arc and Azure IoT offerings, Microsoft enables consistent, centralized management across on-premises, edge and multicloud environments. IT engineers can leverage a unified control plane for resource management, governance and policy enforcement across all environments.

  Cons:

  • Capacity shortages: Gartner clients continue to report capacity shortages in multiple Azure regions, which have led to offering restrictions. Inconsistent availability of Azure capacity complicates the customer's ability to deploy new workloads or implement failover strategies for existing workloads, especially in regions where an explicit region pairing exists.
  • Purchasing and account management: Gartner clients often cite challenges in managing and optimizing their Azure expenditures, including frustration with the various Azure purchasing programs. These issues are exacerbated by changes in account team priorities, such as the push for Microsoft Customer Agreement Enterprise, as reported by many Gartner clients.
  • Emergent in-house AI capabilities: Unlike some other Leaders that have a fully developed in-house AI stack at the silicon and model layers, Microsoft relies heavily on industry investments and partnerships, notably with OpenAI.


• Oracle - Leader
  

  Pros:

  • Wide sovereignty portfolio: Oracle provides multiple options for distributed and sovereign clouds, while maintaining consistent cloud services and pricing across all environments. OCI offers standard commercial, private, sovereign and partner-operated regions, with OCI Superclusters for large-scale private AI/ML use cases.
  • Broad global footprint: Based on its unique distributed cloud architecture, which allows the solution to be scaled down as well as up, OCI offers services from 51 public cloud regions in 26 countries. While not all of these regions have multiple availability domains, OCI's services are delivered in countries where no other major hyperscaler is available.
  • Multicloud support: OCI delivers direct integration with other cloud provider environments. The Oracle Database runs in all major providers, and OCI embeds its own Exadata-based managed database services directly into selected regions of Microsoft Azure, AWS and Google Cloud. Additionally, no egress fees are applied on top of the high-performance interconnects to Azure and Google Cloud.
  • AI strategy: OCI is focused on delivering AI infrastructure capabilities to model builders, selected large accounts and partners as it actively promotes high-performing infrastructure for AI and partnerships with high-profile AI/GenAI providers. This strategy has risks, because model builders can easily move to other vendors if OCI falls behind on technical capabilities or pricing. As an organization, Oracle is focused on embedding GenAI capabilities into its business applications.

  Cons:

  • Lack of trust over reported breach: Oracle has recently suffered from exfiltration of encrypted credentials and associated data from Oracle Cloud Classic. The company's initial denial of the breach, coupled with delays in disclosure, has resulted in a lack of clarity and transparency, raising concerns among some Gartner clients and leading to confusion and an erosion of trust in Oracle's extended portfolio of cloud services, including OCI.
  • Industry strategy focused on Oracle applications: Unlike immediate competitors that offer industry use cases directly on their cloud platforms, Oracle delivers industry solutions separately through products such as Oracle Fusion and Oracle Industry Applications. Positioning OCI solely as infrastructure still limits access to industry use cases for many customers using non-Oracle applications.


• Alibaba Cloud - Challenger
  

  Pros:

  • Robust digital ecosystem and digital transformation enablement: Alibaba Cloud leverages its parent company's e-commerce, digital payments, logistics and entertainment ecosystem to deliver comprehensive digital transformation solutions for Chinese enterprises expanding globally. Strategic alliances with global technology leaders like SAP, VMware and Salesforce help Alibaba to further provide integrated solutions that meet complex business needs.
  • Significant AI investment and generative AI expertise: Alibaba Cloud plans to expand its AI infrastructure and accelerate the deployment of AI applications like Bailian (Model Studio), Platform for AI (PAI) and big data solutions. Currently, it has open-sourced more than 200 models, resulting in over 100,000 derivative models, establishing it as the world's largest open-source model cluster. The Qwen3 series, a new generation of hybrid reasoning models, has also been fully open-sourced.
  • Flexible and competitive pricing models: Alibaba Cloud offers a wide range of pricing models to fulfill diversity requirements, including Elasticity Assurance (EA), a flexible option allowing customers to pay a small fee to reserve guaranteed resources for a set period. In 2024, it also implemented aggressive discount campaigns for both cloud core services and large language model API prices in both global and China markets.

  Cons:

  • Limited partner ecosystem in North America and EMEA: Alibaba's international presence primarily targets Chinese enterprises expanding into global markets. Compared with other vendors in this evaluation, Alibaba Cloud's sales, consulting, technology and service teams remain predominantly focused on China and the Asia/Pacific region, limiting its appeal to partners in North America and EMEA.
  • Slow global market momentum: Alibaba Cloud holds a substantial IaaS market share in Asia; however, it lacks a significant presence in other regions. Even with 2024 price cuts, its IaaS market share declined, and the growth of enterprises adopting Alibaba Cloud in EMEA and North America remains slow.
  • Limited international availability of AI and ML technologies: Alibaba's AI and ML proprietary technologies, developed in response to trade tensions impacting Chinese vendors' access to global hardware innovations, include resources such as Lingjun intelligent cloud computing, Yitian 710, Hanguang 800 and PAI-Lingjun — Alibaba's flagship AI platform. However, these technologies have either not been released internationally or are available only in select regions.


• Huawei Cloud - Niche Player
  

  Pros:

  • Proven success with large accounts in emerging markets: Huawei Cloud leverages its parent company's strong reputation and established presence in emerging markets. Its proven track record with large enterprises and governments provides Huawei Cloud with a competitive edge over rivals in emerging markets such as the Middle East and Latin America, positioning it favorably for hybrid cloud and digital sovereignty opportunities.
  • In-house AI infrastructure and industry models: Huawei Cloud has made substantial investments in the R&D of AI infrastructure and comprehensive AI/ML services and products. This includes the AI CloudMatrix 384, featuring Ascend processors interconnected in an all-to-all mesh network, AI-native storage and high-performance network clustering. Additionally, the AI agent and Pangu Doer form a unified AI intelligent system that integrates Pangu models with cloud services, enhancing the traditional cloud experience.
  • Unique industry approach: To better support its main target industries — such as finance, telecommunications, coal, healthcare and the public sector — Huawei Cloud leverages its "Industry Legion" resources. These "legions" integrate marketing, sales, R&D, product and services teams, along with the ecosystem, to deliver comprehensive industry cloud solutions, or enterprise cloud offerings tailored to the specific requirements of industrial enterprises.

  Cons:

  • Impact of international sanctions and geopolitical tension: Trade and diplomatic relations between China and the U.S. and its allies are strained, and this has created high barriers to trust for Huawei in some western nations. In these geopolitically challenging times, clients in international markets are showing renewed interest in Huawei Cloud; however, Huawei still faces direct bans or restrictions on the use of its hardware and Ascend chipset in some of those markets.
  • Capacity and availability challenges: Not all Huawei Cloud services are available in sufficient quantities internationally, and even common compute instance types may exhibit capacity limitations. Notably, most of Huawei's newest AI/ML infrastructure, modern processors and services have not yet been deployed outside of China. Examples include M9, deployed only in LA Mexico City; and CloudMatrix-based AI computing services, only available in the Chinese mainland.
  • Geographic strategy to meet nonnative needs: Huawei Cloud's aggressive global expansion strategy targets both local customers and Chinese enterprises seeking to "go overseas." However, there remains a need for the company to more clearly articulate how its resources, skills and product offerings are tailored to meet the specific needs of regions outside the Chinese mainland, either directly or through partnerships.


• IBM - Niche Player
  

  Pros:

  • IBM Power Virtual Servers: IBM aims to provide its IBM Power customers with a cloud-like experience for their IBM AIX, IBM i and Linux on Power workloads. IBM Power Virtual Server (VS), along with the company's recently launched distributed cloud option, enables customers to run IBM Power-based logical partitions on IBM Cloud or in the customer's data center.
  • Multiplatform AI: The new IBM Telum II processor for IBM Z mainframes and the IBM Spyre Accelerator for IBM Power and IBM Z introduce in-system AI inferencing for IBM enterprise systems. This allows regulated environments to utilize IBM AI services and use cases, such as fraud detection and watsonx Code Assistant, with low latency and within the boundaries of their core systems.
  • Guided industry cloud strategy: IBM Cloud's strategy to deliver industry cloud solutions at scale primarily relies on IBM Consulting. Unlike other market contenders that must partner with system integrators and independent software vendors, IBM can provide infrastructure and industry-specific outcomes within a single contract.

  Cons:

  • Missed mainframe as a service (MFaaS) opportunities: IBM Cloud misses the opportunity to offer a cloud-like experience for IBM Z mainframes that integrates its mainframes with value-added cloud services and provides easy access for training and education. IBM Wazi as a Service — the only IBM Cloud service based on mainframe — supports only nonproduction workloads and a limited subset of capabilities of the IBM Z platform.
  • Loosely integrated portfolio of services: Most of IBM's differentiating products — such as Red Hat, Apptio, Turbonomic and HashiCorp — are only loosely integrated with IBM Cloud. As a result, customers must navigate various products, interfaces and skill sets to access the breadth of services, which is a relatively disjointed experience compared with what's offered by Leaders in this Magic Quadrant.
  • Limited number of cloud regions and multiple architectures: IBM Cloud operates in 17 locations worldwide — a limited footprint compared with other vendors in this evaluation. Within these locations, customers must navigate multizone regions, single-campus multizone regions, classic data centers and Power VS. Different location types require distinct architectural best practices, have different constraints, offer varying cloud services and may necessitate different skills.


• Tencent Cloud - Niche Player
  

  Pros:

  • Scalable services: Through its historical support for some of the largest gaming and social media applications in the world, Tencent Cloud has optimized its infrastructure and platform services to support highly scalable distributed applications.
  • Price discounts: Tencent Cloud offers discounts that are significantly higher than U.S. cloud providers and moderately higher than Chinese providers. These prices may be attractive to customers looking to deploy workloads on Tencent Cloud at a low cost.
  • Industry cloud services: Tencent offers technology building blocks, such as AI-enabled media services and SuperApp solutions, that enable organizations to accelerate their digital initiatives. This approach is particularly effective for industries such as gaming, media and entertainment, public sector, financial services, and telecommunications.

  Cons:

  • Product and solution clarity: While Tencent Cloud offers a full complement of IaaS and PaaS services internationally, its production documentation and transparency for these services lags those of other vendors in the evaluation.
  • Highly targeted focus: Tencent is concentrating on delivering customized services for some of the world's largest and most demanding customers in industries such as media, entertainment and gaming. However, its ability to provide these services does not scale effectively to a broader and more diverse customer base.
  • Small partner ecosystem: While Tencent has a large ecosystem in China, the range and size of its implementation partners outside of China continues to be very limited. Customers must vet third-party integrators carefully for their level of expertise with Tencent Cloud.

Reference

• Gartner, Magic Quadrant for Strategic Cloud Platform Services, 4 August 2025, ID G00826104

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