The cloud pricing comparison question seems like it should have a clean answer. It doesn’t — and any article that gives you one without significant caveats is oversimplifying. AWS, Azure, and Google Cloud have hundreds of services each, price them differently, structure their discount programs differently, and involve infrastructure costs that vary dramatically based on your workload profile.
What this guide gives you is an honest framework, real benchmark numbers across the most important cost dimensions, and the perspective you need to make an informed procurement decision — or a better argument in your next cloud contract renewal.
The Cloud Market Reality in 2025
AWS holds approximately 31% of the global cloud market. Azure holds approximately 25%. Google Cloud holds approximately 11%. The remaining 33% is fragmented across smaller providers.
Market share matters in this context because it signals ecosystem maturity, service breadth, and available talent. AWS has the largest service catalog (200+ services) and the deepest talent pool. Azure has the strongest enterprise integration story and the Microsoft ecosystem advantage. Google Cloud has the strongest data and AI platform and the most aggressive committed-use discount structure.
Compute Pricing Comparison: What a VM Actually Costs
Let’s compare a workhorse general-purpose instance across providers. We’ll use a roughly equivalent configuration: 8 vCPUs, 32GB RAM, running in US East (for all three providers).
AWS (m5.2xlarge):
- On-demand: $0.384/hour | $276/month | $3,312/year
- 1-year Reserved Instance (all upfront): $0.235/hour | $2,059/year (38% savings)
- 3-year Reserved Instance (all upfront): $0.152/hour | $1,332/year (60% savings)
- Savings Plan (flexible): ~$0.265/hour with 1-year commitment
Azure (D8s v5):
- On-demand: $0.384/hour | $276/month (closely matched to AWS for equivalents)
- 1-year Reserved VM: $0.243/hour | ~$2,128/year (37% savings)
- Azure Hybrid Benefit (Windows Server licenses with Software Assurance): Additional 40% discount where applicable — this is a significant advantage for Windows-heavy workloads
Google Cloud (n2-standard-8):
- On-demand: $0.388/hour | $279/month
- 1-year Committed Use Discount (CUD): $0.253/hour | ~$2,216/year (35% savings)
- 3-year CUD: $0.175/hour | ~$1,533/year (55% savings)
- Sustained Use Discounts: Google automatically applies up to 30% discounts on instances running more than 25% of a month — no commitment required
At on-demand rates, the three providers are nearly identical for compute. The differences emerge in the discount structure. Google’s automatic Sustained Use Discounts benefit organizations that run workloads continuously but don’t want to commit upfront. AWS Savings Plans offer more flexibility than Reserved Instances for variable workloads. Azure Hybrid Benefit is transformatively valuable for Windows Server and SQL Server workloads.
Storage Pricing Comparison: S3 vs Azure Blob vs Google Cloud Storage
Object storage is a significant cost driver for data-intensive organizations. Comparing the most common storage tier (standard/hot) in US East:
- AWS S3 Standard: $0.023/GB/month for first 50TB. Data retrieval: $0.0004/1,000 GET requests, $0.09/GB egress to internet (first 10TB/month). This egress cost is frequently the surprise line item in AWS bills.
- Azure Blob Storage (Hot): $0.018/GB/month for first 50TB. Operations and egress fees apply similarly. Azure’s pricing is modestly cheaper on raw storage, though Microsoft charges for operations that some organizations find surprising.
- Google Cloud Storage (Standard): $0.020/GB/month. Google provides free egress to other Google Cloud services in the same region — a meaningful advantage for data flowing between Cloud Storage and BigQuery or other GCP services.
Enterprise Discount Programs: Where the Real Savings Live
The on-demand vs. committed pricing gap is table stakes. The more interesting comparison for large enterprises is the commitment program structure:
AWS Enterprise Discount Program (EDP): For organizations committing $1M+ annually, AWS offers custom discount tiers (typically 10–25% off contracted services) negotiated directly with AWS account teams. EDP is the primary commercial vehicle for large enterprises and is highly negotiable based on growth commitment, workload profile, and competitive dynamics.
Microsoft Azure Consumption Commitment (MACC): Similar to EDP — organizations committing substantial Azure spend (typically $250K–$1M+ over 1–3 years) receive program discounts and credits. MACC also counts qualifying purchases through the Azure Marketplace, which is an underutilized lever — Databricks, Snowflake, and many other SaaS/PaaS vendors sell through Azure Marketplace, meaning those purchases can count against your MACC commitment.
Google Cloud Committed Use Contracts: Google’s equivalent program offers 28–57% discounts on committed resources versus on-demand pricing. Google is generally considered more flexible in their committed use negotiations than AWS or Azure, particularly for organizations where Google Cloud represents a strategic investment rather than a workload migration.
Networking and Egress Costs: The Line Item That Kills Cloud Budgets
Here’s the dirty secret of cloud pricing that every CTO eventually learns the hard way: moving data out of the cloud is expensive, and the big three all monetize egress aggressively.
Standard internet egress rates (first 10TB/month, US East):
- AWS: $0.09/GB
- Azure: $0.087/GB
- Google Cloud: $0.08/GB
For an organization moving 100TB/month out of cloud to end users or hybrid workloads, egress alone costs $8,000–$9,000/month, $96,000–$108,000/year. Intra-cloud traffic (between regions or availability zones within the same provider) also carries transfer fees that compound at scale.
The European Union’s Data Act (effective 2024) explicitly addressed cloud egress costs as an anti-competitive practice. AWS has adjusted some egress policies in response; Azure and Google have followed. Egress to on-premises is now free for certain scenarios — check your current provider’s policies, as they’ve changed recently.
Which Cloud Should Your Organization Choose?
After all the numbers, the honest framework:
Choose AWS if: You value service breadth, ecosystem maturity, and the largest available talent pool. If you’re building a net-new cloud infrastructure without existing enterprise software commitments, AWS is the most flexible choice. AWS also leads on global infrastructure footprint — most regions and availability zones.
Choose Azure if: You’re a Microsoft shop. Office 365, Dynamics 365, SQL Server, Windows Server, Active Directory — if any of these are central to your IT environment, Azure’s native integration and Hybrid Benefit discounts make the economics difficult to ignore. Azure AD (now Entra ID) as your identity provider also pulls SSO and security tooling toward Azure.
Choose Google Cloud if: Your organization prioritizes data analytics, machine learning, and AI. BigQuery remains the most capable serverless analytics engine at scale. Vertex AI and Google’s foundation model investments are the most mature in the market. GCP’s pricing for data-intensive workloads, combined with no egress fees between GCP services, makes it genuinely cost-competitive for analytics-centric architectures.
Multi-Cloud Reality: What the Data Shows
The majority of large enterprises operate on two or more cloud providers today. The pragmatic reality is that workload fit, existing vendor relationships, and regulatory requirements (data residency, compliance) often dictate that different workloads live in different clouds.
Multi-cloud governance — managing cost, security, and operations across providers — is where organizations consistently underinvest. A FinOps practice (cloud financial management) that actively tracks and optimizes spend across providers typically generates 15–30% in cloud cost savings at enterprise scale. It’s worth the investment.