Cloud provider comparison
Compare cloud provider technology stacks using real source-linked deployments: top AI services, technology breadth, capability patterns, recent activity, and the use cases behind each provider signal.
3,300
281
546
3
Real AI implementations using Microsoft Azure, Azure AI Foundry, Azure OpenAI, Copilot, Microsoft Fabric, and related services.
2,158
Indexed cloud provider cases
Technology signals
Real AI implementations using Amazon Web Services, including Bedrock, SageMaker, Amazon Q, and cloud-native AI services.
612
Indexed cloud provider cases
Technology signals
Real AI implementations using Google Cloud, including Gemini, Vertex AI, BigQuery, and enterprise AI services.
512
Indexed cloud provider cases
Technology signals
Real AI implementations using Oracle Cloud Infrastructure, including OCI Generative AI, Select AI, Oracle Digital Assistant, and AI embedded in Fusion Applications.
1
Indexed cloud provider cases
Technology signals
Real AI implementations using IBM watsonx, including watsonx.ai, watsonx Orchestrate, watsonx Assistant, and Granite models.
6
Indexed cloud provider cases
Technology signals
Real AI implementations using Alibaba Cloud, including Model Studio, Qwen (Tongyi Qianwen) models, and Platform for AI (PAI).
11
Indexed cloud provider cases
Technology signals
Top technologies · cases scaled to the leader
Top technologies · cases scaled to the leader
Top technologies · cases scaled to the leader
Top technologies · cases scaled to the leader
Top technologies · cases scaled to the leader
Top technologies · cases scaled to the leader
Technology readout
Microsoft Azure currently has the largest indexed cloud provider evidence footprint with 2,158 cases in this comparison.
AWS spans 175 sampled technologies, led by Amazon Bedrock, Amazon S3.
Microsoft Azure has the strongest recent signal in the latest sampled evidence with 90 cases from the last 180 days.
Google Cloud shows the broadest sampled technology adoption context across 17 industries and 30 countries.
Side-by-side table
| Provider | Indexed cases | Share | Recent | Avg. innovation | Top technologies | Technology breadth | Capability pattern | Top industry |
|---|---|---|---|---|---|---|---|---|
| Microsoft | 2,158 | 65% | 90 | Not scored | Microsoft 365 Copilot, Copilot Studio, Azure OpenAI | 148 | Agents, Copilot | Professional Services |
| 612 | 19% | 90 | Not scored | Amazon Bedrock, Amazon S3, AWS Lambda | 175 | Agents, RAG | Finance | |
| GCP | 512 | 16% | 90 | Not scored | BigQuery, Vertex AI, Google Kubernetes Engine | 174 | Agents, Multi-agent | Tech & Comms |
| 1 | 0% | 0 | Not scored | Cohere Command A, Microservices, Oracle Cloud Infrastructure (OCI) Kubernetes Engine | 4 | Agents, RAG | Healthcare | |
| 6 | 0% | 5 | Not scored | IBM watsonx Orchestrate, IBM Bob, IBM Cloud Pak for Business Automation | 9 | Agents, Multi-agent | Manufacturing | |
| Alibaba | 11 | 0% | 6 | Not scored | ApsaraDB RDS for MySQL, Alibaba Cloud, Alibaba Cloud Elastic Compute Service | 47 | Voice | Other |
Crawlable comparison pages
Evidence examples
Network Rail, the UK railway infrastructure operator, uses Microsoft Power Platform to digitize frontline processes and govern low-code development at enterprise scale.,The company built an end-to-end safety close-call reporting solution used by all employees, with offline access through Dataverse, notifications through Power Automate, external reporting through Power Pages, and secure data sharing through a custom API.,Network Rail also deployed a Copilot Studio AI support agent for maker support, used AI Builder OCR for meter readings, and used Plans in Power Apps and generative pages to accelerate solution creation.
MiniMax is a global AI foundation model company that experienced rapid growth in 2024, pushing user data volumes to tens of petabytes and exposing bottlenecks from fragmented cloud stacks, low development efficiency, high operational overhead, and poor cost/utilization for large-scale data processing.,Alibaba Cloud helped MiniMax build a globally unified cloud-native data warehouse centered on DataWorks, MaxCompute, Hologres, Realtime Compute for Apache Flink, OSS, and MaxFrame to support real-time/offline data collaboration and a managed Data+AI preprocessing platform.
Resorts World Genting (Genting Malaysia Berhad) partnered with Alibaba Cloud to develop and deploy a Virtual Queue (VQ) solution for Genting SkyWorlds.,The system uses AI-driven crowd analysis and prediction to dynamically manage attraction demand, show real-time waiting periods and VQ slots, and recommend optimized itineraries and incentives through a mobile app.,The solution also supports online booking and migration-related cloud infrastructure to help the resort handle seasonal traffic and deliver a more seamless guest experience.
Sanofi built Concierge in-house on AWS as a unified, agentic AI companion for its global workforce, using Amazon Bedrock for model flexibility and planning to add Amazon Bedrock AgentCore for orchestration.,The system gives employees a single conversational interface for finding information, generating content, completing tasks, and discovering specialized agents across the company.
Papa Johns International adopted Gemini Enterprise Agent Platform and the Food Ordering AI agent to let customers place pizza orders using natural language and voice with no taps required.,The implementation sits on Google Cloud data infrastructure including BigQuery, CloudSQL, and Google Maps to support personalization, analytics feedback loops, and delivery tracking.,Papa Johns says the approach aims to improve conversion, basket size, customer satisfaction, and ordering speed while also improving productivity and analytics quality.
Resorts World Genting (Genting Malaysia Berhad) is a major leisure and hospitality operator in Malaysia.,The company needed to manage crowd dynamics and reservation traffic for its Genting SkyWorlds theme park while improving guest experience and reducing waiting times.
Television Broadcasts Limited (TVB) is a major TV broadcasting and on-demand video streaming provider in Hong Kong.,As viewership grew, TVB needed better application scalability, performance stability, and cost control during peak traffic hours across its television and streaming platforms.
GCash partnered with Alibaba Cloud to migrate a legacy on-premise platform to a scalable cloud architecture for its digital payments super app in the Philippines.,The platform supports high-concurrency transactions, secure storage, batch and real-time analytics, and AI model development for risk modeling, fraud detection, and user insights.,Alibaba Cloud services used include Elastic Compute Service (ECS), Object Storage Service (OSS), MaxCompute, Hologres, Machine Learning Platform for AI (PAI), Web Application Firewall (WAF), Log Service (SLS), and ZOLOZ Real ID.
Banco Bradesco, one of Brazil's largest private financial groups, built a scalable generative AI platform called BRIDGE on Microsoft Azure Red Hat OpenShift.,The platform integrates multiple AI models, supports modular multi-agent creation for business teams, and connects to Azure OpenAI while embedding governance, security, and regulatory controls.,BRIDGE serves internal support, development, operations, technology, and customer-service use cases across the bank.
FAQ
Microsoft Azure has the largest indexed cloud provider footprint in this view with 2,158 matching cases.
Microsoft Azure shows the strongest recent sampled activity with 90 cases from the last 180 days.
The page compares Microsoft Azure, AWS, and Google Cloud using indexed case totals from the filtered dataset. Industry, country, partner, technology, recent activity, and innovativeness signals are calculated from the latest 90 matching cases per provider.
Use the evidence links on each provider card or open the use case ranking with the same provider and industry filters applied.
