A vendor-neutral comparison across compute, databases, pricing, enterprise integration, and regional availability — with a five-factor decision framework and a real engagement case study showing when multi-cloud actually pays off.
Choosing between AWS, Azure, and Google Cloud shapes architecture, hiring, vendor relationships, and infrastructure costs for years. Frame the decision around your actual workload requirements, not vendor marketing.
Sherdil Cloud has deployed production workloads on all three major platforms (plus Alibaba Cloud) since 2014. As an AWS Advanced Partner and Official Alibaba Cloud Partner with extensive Azure and GCP experience, we bring a vendor-neutral perspective that most consultancies cannot offer. This guide compares the three platforms honestly across the dimensions that actually matter.
AWS vs Azure vs GCP at a glance
| Provider | Launch | Market share (Q4 2024) | Primary strength | Best for |
|---|---|---|---|---|
| AWS | 2006 | ~31% | Service breadth and maturity (200+ services) | Cloud-native teams; broadest service selection |
| Microsoft Azure | 2010 | ~25% | Enterprise integration with Microsoft stack | Organizations on Microsoft 365, Windows Server, .NET, AAD |
| Google Cloud (GCP) | 2008 | ~11% | Data analytics, ML, Kubernetes | Analytics-heavy workloads; ML-driven products; container-first |
Market share figures per Synergy Research Group Q4 2024 cloud infrastructure data. The remaining ~33% includes Alibaba Cloud, IBM Cloud, Oracle Cloud, and other providers.
Market position and strengths
Breadth & maturity
The AWS catalog lists 200+ fully featured services. Most have been in production for years with unmatched documentation and community support.
Enterprise integration
Azure Active Directory integrates with Office 365, Dynamics 365, and Windows Server environments. The natural choice for Microsoft-centric organizations running hybrid Windows and cloud.
Data & AI
Leads in data analytics (BigQuery), ML (Vertex AI, TensorFlow), and Kubernetes (Google invented K8s; GKE is widely considered the strongest managed offering).
Compute services compared
For most general-purpose workloads, all three platforms deliver comparable performance at similar price points. Differentiation comes from specialized instance types and ecosystem integration.
| Capability | AWS | Azure | GCP |
|---|---|---|---|
| Virtual machines | EC2 (600+ configurations) | Azure VMs (strong Windows licensing) | Compute Engine (custom machine types) |
| Spot / preemptible | Spot Instances (up to 90% savings, most mature spot market) | Azure Spot VMs | Preemptible and Spot VMs |
| Serverless functions | Lambda (multi-language, generous free tier) | Azure Functions (best .NET support) | Cloud Functions, Cloud Run (excellent for containers without K8s) |
| GPU / ML hardware | Broadest GPU selection | Strong GPU availability, NVIDIA partnerships | TPU hardware purpose-built for ML |
| Hybrid management | AWS Outposts | Azure Arc | Anthos |
Sherdil Cloud’s cloud and DevOps consulting services help organizations evaluate compute requirements and select the platform that delivers the best price-performance ratio for their specific workload profiles.
Database and storage services
Database services often drive cloud platform decisions because migration between providers is costly and complex.
| Database type | AWS | Azure | GCP |
|---|---|---|---|
| Managed relational | RDS, Aurora (5x performance) | Azure SQL Database (deep SQL Server integration) | Cloud Spanner (globally distributed relational, no AWS/Azure equivalent) |
| NoSQL / document | DynamoDB; DocumentDB (MongoDB compatible) | Cosmos DB (multi-model, 5 consistency levels) | Firestore; Bigtable |
| Graph | Neptune | Cosmos DB Gremlin API | (no direct equivalent) |
| Data warehouse | Redshift | Azure Synapse Analytics | BigQuery (industry-leading serverless) |
| Object storage | S3 (11 nines durability, industry reference) | Azure Blob Storage | Cloud Storage |
- Analytics & data warehousing → GCP BigQuery. Best price-performance at petabyte scale, zero infrastructure management.
- Globally distributed NoSQL → Azure Cosmos DB. Five consistency models is a unique capability.
- Globally distributed relational → GCP Cloud Spanner. Horizontal scaling for relational workloads.
- Broadest portfolio → AWS. If you need an exotic database type, AWS likely has a managed option.
Pricing models and cost comparison
On-demand pricing is roughly comparable across all three providers for equivalent instance types. The differences lie in discount mechanisms.
| Discount mechanism | AWS | Azure | GCP |
|---|---|---|---|
| Reserved capacity | Reserved Instances (1-3 yr, 30-72%) | Reserved VM Instances | Committed Use Discounts (1-3 yr, up to 57%) |
| Flexible commitments | Savings Plans | Azure Savings Plans | (covered by CUDs) |
| Spot / interruptible | Spot Instances (up to 90%) | Spot VMs | Preemptible / Spot VMs |
| Automatic discounts | (requires commitments) | (requires commitments) | Sustained use discounts (auto-applied up to 30%) |
| License optimization | (none for MS licenses) | Azure Hybrid Benefit (up to 85% on Windows VMs) | (none for MS licenses) |
| Billing granularity | Per-second (most services) | Per-minute or per-second | Per-second |
For equivalent workloads, the actual cost difference between providers is typically 5-15% depending on workload characteristics and discount optimization. The operational cost of managing multi-cloud complexity often exceeds the savings from price-shopping between providers. For organizations with existing Microsoft Enterprise Agreements, Azure Hybrid Benefit can shift the math dramatically.
Enterprise integration and hybrid capabilities
This is where the three platforms diverge most significantly.
Robust hybrid, no native productivity suite
Outposts, Direct Connect, and Transit Gateway for hybrid networking. Integration with Microsoft or Google collaboration tools requires additional configuration.
Unmatched Microsoft integration
Azure Active Directory SSO, native Microsoft 365 / Teams / SharePoint / Dynamics integration, Azure DevOps. Eliminates the integration friction AWS and GCP introduce for Microsoft shops.
Google Workspace + Kubernetes leadership
Integrates with Google Workspace (Gmail, Drive, Docs). Anthos extends GCP management across environments. GKE is widely considered the strongest managed Kubernetes for cloud-native organizations. See our hybrid vs multi-cloud guide.
Regional availability and compliance
Geographic presence matters for latency, data residency, and regulatory compliance. Numbers below are current as of Q1 2026.
| Provider | Regions | Availability zones | Distinguishing capability |
|---|---|---|---|
| AWS | 33 | 105 AZs | Broadest global footprint; compliance for most regulated industries |
| Azure | 60+ | Multiple AZs per region | Most regions of any provider; Azure Government and Government Secret for US gov workloads |
| GCP | 40 | 121 zones | Network performance often cited as superior due to Google’s private fiber backbone |
For organizations operating in Pakistan, the Middle East, and Southeast Asia, Alibaba Cloud offers competitive regional presence with data centers in markets where the big three have limited coverage. As an Official Alibaba Cloud Partner, Sherdil Cloud helps organizations integrate Alibaba Cloud alongside AWS, Azure, or GCP for optimal regional coverage.
Making your decision: a five-factor framework
Rather than choosing based on feature lists, evaluate the platform decision across five factors specific to your organization.
Existing technology investments
Microsoft 365 / Windows Server / .NET / AD shops → Azure reduces integration complexity substantially. Google Workspace + containerized workloads → GCP. No strong allegiance → AWS offers the broadest selection.
Primary workload type
Data analytics and ML workloads favor GCP. General-purpose web apps and microservices are well-served by all three. Enterprise apps with Microsoft dependencies favor Azure. Workloads requiring the broadest service selection favor AWS.
Team expertise
The platform your team already knows reduces time-to-production by months. Retraining costs and learning curves are real expenses that factor into total cost of ownership.
Geographic requirements
Map customer locations, data residency requirements, and latency needs against each provider’s regional footprint. Include Alibaba Cloud for Asia-Pacific or Middle East markets.
Long-term vendor strategy
Decide whether to go all-in with a single provider (simplicity, deeper discounts, unified tooling) or adopt multi-cloud (vendor flexibility, best-of-breed services, reduced lock-in). For most organizations, single-cloud with a documented exit strategy beats multi-cloud price-shopping.
A real engagement: UAE ecommerce platform evaluation
In a 2024 engagement with a UAE-based ecommerce client (approximately 60 engineers, ~$30M revenue), we ran a structured cloud platform evaluation. The engineering leadership had pre-committed to AWS based on team familiarity. The evaluation surfaced two findings that changed the recommendation.
Key evaluation findings
| Finding | Detail | Decision impact |
|---|---|---|
| Analytics workload TCO | 22% TCO advantage on GCP BigQuery for reporting and customer segmentation | Migrate data layer to GCP |
| Commerce stack inertia | Existing services on AWS, team expertise on AWS, no Microsoft dependencies | Keep commerce on AWS |
Implementation
Hybrid AWS + GCP architecture: commerce platform on AWS Bahrain, BigQuery in GCP Tokyo for analytics, with daily incremental data sync via Cloud Storage Transfer Service.
Year-one outcomes
For organizations evaluating broader infrastructure decisions, see our analysis on maximizing ROI with infrastructure improvement strategies. Sherdil Cloud’s cloud infrastructure services include platform evaluation engagements that map your specific requirements against all major providers with no vendor bias influencing the recommendation.
Free cloud platform assessment
Our architects will map your workloads against AWS, Azure, GCP, and Alibaba Cloud across the five decision factors, with no vendor allegiance influencing the recommendation.
Request your free assessment →Frequently asked questions
Which cloud platform is cheapest: AWS, Azure, or GCP?
Pricing across AWS, Azure, and GCP typically differs by 5-15% for equivalent workloads. GCP offers automatic sustained use discounts without commitments, making it slightly cheaper for steady-state workloads. Azure provides the best value for organizations with existing Microsoft Enterprise Agreements through Azure Hybrid Benefit (up to 85% savings on Windows VMs). AWS offers the deepest discounts through Reserved Instances and Savings Plans but requires active management.
Can we use multiple cloud providers at once?
Yes, and many organizations adopt multi-cloud strategies. Multi-cloud adds operational complexity, requires expertise across multiple platforms, and can increase costs through data egress charges (AWS charges roughly $0.085-$0.09 per GB outbound). Recommended only when specific workloads are significantly better served by different providers or when geographic requirements demand it.
How do AWS, Azure, and GCP compare for machine learning workloads?
GCP leads in ML with Vertex AI, TensorFlow integration, and TPU hardware designed specifically for ML training. AWS SageMaker provides a comprehensive ML platform with the broadest pre-built algorithms and GPU instance types. Azure Machine Learning integrates with Microsoft development tools and offers strong MLOps capabilities. For cutting-edge ML, GCP has an edge; for production ML deployment, all three are capable.
How long does it take to migrate from one cloud to another?
Migration timeline depends on workload complexity. Simple web applications migrate in two to four weeks. Complex enterprise applications with multiple database dependencies and integrations typically take three to six months per application. Full organizational migrations spanning dozens of applications take 12-24 months when executed in phased waves.
Does Sherdil Cloud recommend one cloud platform over others?
No. As an AWS Advanced Partner and Official Alibaba Cloud Partner with extensive Azure and GCP experience, we recommend the platform that best fits each client’s specific requirements. Our consulting engagements begin with a structured evaluation that maps business requirements, technical constraints, team capabilities, and geographic needs against each platform’s strengths. The right platform varies by organization. There is no universal best choice.
Sources and further reading
- Synergy Research Group, Cloud Infrastructure Quarterly Market Share Reports. srgresearch.com
- AWS, Global Infrastructure regions and availability zones. aws.amazon.com/about-aws/global-infrastructure
- Microsoft Azure, Azure geographies and regions. azure.microsoft.com/…/geographies
- Google Cloud, Cloud locations. cloud.google.com/about/locations
- AWS, Products and services catalog. aws.amazon.com/products
- Microsoft, Azure Hybrid Benefit savings calculator. azure.microsoft.com/…/hybrid-benefit
- Google Cloud, Vertex AI documentation. cloud.google.com/vertex-ai
