AWS vs Azure vs GCP 2025 Complete Comparison: Features, Pricing, Selection Guide

Choosing a cloud platform is one of the most important decisions in enterprise digital transformation. AWS, Azure, and GCP each have their advocates, and most comparison articles online are biased or outdated. This article analyzes the strengths and weaknesses of the three major platforms from 2025's latest data with a neutral perspective to help you make the best choice for your business needs.

If you're evaluating cloud platforms, preparing for cloud migration, or want to know which cloud your competitors use, this article will be a practical reference.

Still undecided? Schedule a consultation directly

Each cloud has pros and cons; choosing wrong could waste over half a year in migration costs. CloudInsight provides neutral cloud selection consulting. Schedule a free consultation, let us help analyze which platform best suits your business.

Three Major Cloud Platforms Overview

Before diving into detailed comparisons, let's quickly understand the background and positioning of the three platforms.

Market Share and Development History

Platform	Parent Company	Founded	2025 Market Share	Positioning
AWS	Amazon	2006	~31%	Most comprehensive services, market leader
Azure	Microsoft	2010	~25%	Enterprise integration, Microsoft ecosystem
GCP	Google	2008	~11%	Data analytics, AI/ML, open-source friendly

AWS is the pioneer of the cloud industry. Since launching S3 and EC2 in 2006, it has built the most complete service ecosystem. Currently with 200+ services, it's the cloud platform with the broadest service range.

Azure caught up quickly, leveraging Microsoft's deep roots in the enterprise market, with particularly high adoption among existing Windows Server, Office 365, and Dynamics users. It has grown fastest in recent years.

GCP has the smallest market share but unique advantages in specific areas—BigQuery data analytics, Kubernetes (GKE), and AI/ML (Vertex AI, Gemini) are industry benchmarks.

Core Advantages of Each Platform

Platform	Core Advantages	Weaker Areas
AWS	Most services, largest community, most documentation	More complex interface, less intuitive pricing
Azure	Microsoft integration, strong hybrid cloud capabilities	Some services need stability improvements
GCP	Data analytics, AI/ML, network performance	Fewer services, enterprise features arrived later

If you're not familiar with AWS services, you can first refer to the AWS Complete Guide.

Compute Services Comparison

Compute is the most fundamental cloud service, and the three platforms' virtual machine services each have their characteristics.

Virtual Machine Service Comparison

Comparison Item	AWS EC2	Azure VM	GCP Compute Engine
Instance Families	600+ types	500+ types	200+ types
Max vCPU	448	416	416
Max Memory	24 TB	12 TB	12 TB
GPU Support	NVIDIA (A100, H100), Trainium	NVIDIA, AMD	NVIDIA, TPU
Spot Discount	Up to 90%	Up to 90%	Up to 91%
Reserved Discount	Up to 72% (3 years)	Up to 72% (3 years)	Up to 57% (3 year CUD)

Serverless Compute

Comparison Item	AWS Lambda	Azure Functions	GCP Cloud Functions
Free Tier	1 million/month	1 million/month	2 million/month
Max Execution Time	15 minutes	230 sec (consumption) / unlimited (dedicated)	60 minutes (2nd gen)
Max Memory	10 GB	14 GB	32 GB
Supported Languages	Python, Node, Java, Go, .NET, Ruby	C#, JavaScript, Python, Java, PowerShell	Node, Python, Go, Java, .NET, Ruby, PHP
Cold Start	Medium	Slower	Faster

Comparison Conclusion:

• Choice Diversity: AWS > Azure > GCP
• Price Competitiveness: GCP (Spot) ≈ AWS ≈ Azure
• Serverless: Each has advantages, GCP has highest free tier

For deep dive into AWS compute services, see AWS EC2 Complete Tutorial and AWS Lambda Getting Started Guide.

Storage Services Comparison

Object storage is the most commonly used cloud storage type and an important revenue source for all three platforms.

Object Storage Comparison

Comparison Item	AWS S3	Azure Blob Storage	GCP Cloud Storage
Durability	99.999999999% (11 nines)	99.999999999%	99.999999999%
Availability SLA	99.99%	99.99%	99.99%
Storage Classes	8 types	4 types	4 types
Lifecycle Management	Supported	Supported	Supported
Version Control	Supported	Supported	Supported

Object Storage Pricing (US East Region, per GB/month)

Storage Class	AWS S3	Azure Blob	GCP Cloud Storage
Standard	$0.023	$0.018	$0.020
Infrequent Access	$0.0125	$0.01	$0.01
Archive (Coldest)	$0.00099 (Glacier Deep Archive)	$0.00099 (Archive)	$0.0012 (Archive)

Pricing Conclusion: Azure and GCP are slightly cheaper for standard storage, but AWS S3 has the most granular storage classes for more precise cost optimization.

Block Storage Comparison

Comparison Item	AWS EBS	Azure Managed Disks	GCP Persistent Disk
SSD IOPS Limit	256,000	160,000	100,000
SSD Throughput Limit	4,000 MB/s	2,000 MB/s	2,400 MB/s
Snapshots	Incremental	Incremental	Incremental
Cross-region Replication	Supported	Supported	Supported

Comparison Conclusion: AWS EBS has the highest performance specs, suitable for I/O-intensive workloads.

Database Services Comparison

Databases are the core of enterprise applications, and all three platforms offer rich managed database services.

Relational Databases

Comparison Item	AWS RDS / Aurora	Azure SQL Database	GCP Cloud SQL / AlloyDB
Supported Engines	MySQL, PostgreSQL, MariaDB, Oracle, SQL Server	SQL Server (native), MySQL, PostgreSQL	MySQL, PostgreSQL, SQL Server
Serverless	Aurora Serverless v2	Azure SQL Serverless	AlloyDB Serverless
Read Replicas	Up to 15	Up to 4	Up to 10
Auto Scaling	Aurora supports	Supported	AlloyDB supports

Featured Services:

• AWS Aurora: MySQL/PostgreSQL compatible, 3-5x performance improvement
• Azure SQL: Best native SQL Server support, highest .NET integration
• GCP AlloyDB: PostgreSQL compatible, optimized for analytical workloads

NoSQL Databases

Comparison Item	AWS DynamoDB	Azure Cosmos DB	GCP Firestore / Bigtable
Type	Key-Value, Document	Multi-model	Document (Firestore), Wide-column (Bigtable)
Global Distribution	Global Tables	Multi-region writes	Multi-region
Latency	Milliseconds	Milliseconds	Milliseconds
Serverless	Native Serverless	Native Serverless	Firestore native, Bigtable requires configuration

Comparison Conclusion:

• Simple key-value: DynamoDB most intuitive
• Multi-model needs: Cosmos DB most flexible
• Large-scale time-series data: Bigtable is the benchmark

AI/ML Services Comparison

AI is the main battleground for cloud competition in recent years, with all three platforms heavily investing in generative AI.

Generative AI Platforms

Comparison Item	AWS Bedrock	Azure OpenAI	GCP Vertex AI
Exclusive Models	Claude (Anthropic)	GPT-4, GPT-4o, o1 (OpenAI)	Gemini (Google)
Open Source Models	Llama, Mistral	Llama	Llama, Gemma
Image Generation	Stable Diffusion, Titan	DALL-E 3	Imagen
Enterprise Features	Knowledge Bases, Agent	Azure AI Search, Copilot Studio	Vertex AI Search, Agent Builder
Pricing Model	Per Token	Per Token	Per Token / Character

Model Pricing Comparison (per million tokens, 2025)

Model	Platform	Input Price	Output Price
Claude 3.5 Sonnet	AWS Bedrock	$3.00	$15.00
GPT-4o	Azure OpenAI	$2.50	$10.00
Gemini 1.5 Pro	GCP Vertex AI	$1.25	$5.00
Llama 3.1 70B	All three platforms	$0.90-2.65	$0.90-3.50

Comparison Conclusion:

• Want Claude: Choose AWS Bedrock
• Want GPT-4: Choose Azure OpenAI
• Want Gemini: Choose GCP Vertex AI
• Lowest Cost: GCP Gemini series has most affordable pricing

For deep dive into AWS AI services, see AWS AI Services Complete Guide.

Machine Learning Platforms

Comparison Item	AWS SageMaker	Azure ML	GCP Vertex AI
Notebook Environment	SageMaker Studio	Azure ML Studio	Vertex AI Workbench
AutoML	Autopilot	Automated ML	AutoML
MLOps	SageMaker Pipelines	Azure ML Pipelines	Vertex AI Pipelines
Model Monitoring	Model Monitor	Model Monitor	Model Monitoring
Features	Most comprehensive	Azure DevOps integration	BigQuery integration, TPU

Comparison Conclusion:

• Feature completeness: SageMaker > Azure ML ≈ Vertex AI
• Data analytics integration: Vertex AI (native BigQuery integration)
• Microsoft ecosystem integration: Azure ML

Price Comparison

Price is one of the key factors in choosing a cloud platform, but also the most complex comparison item.

Billing Model Differences

Billing Model	AWS	Azure	GCP
On-Demand	On-Demand	Pay-as-you-go	On-Demand
Reserved Discount	Reserved Instances, Savings Plans	Reserved VM, Savings Plan	Committed Use Discounts (CUD)
Spot/Low Priority	Spot Instances (up to 90% off)	Spot VMs (up to 90% off)	Preemptible / Spot VMs (up to 91% off)
Sustained Use Discount	None	None	Auto Sustained Use Discount (up to 30%)
Billing Currency	USD	Multi-currency	USD

GCP's Unique Advantage: Sustained Use Discount applies automatically without commitment—as long as your VM runs more than 25% of the month, discounts start. This is friendly for teams without prepayment ability.

Same-Spec VM Monthly Cost Comparison

Using 4 vCPU, 16 GB RAM, 100 GB SSD VM as example (US East region, on-demand pricing):

Spec	AWS	Azure	GCP
Instance Type	m6i.xlarge	Standard_D4s_v5	n2-standard-4
Monthly Estimate	~$138	~$140	~$135
Spot/Preemptible	~$50	~$50	~$40
1-Year Reserved	~$89	~$85	~$96 (CUD)
3-Year Reserved	~$56	~$54	~$68 (CUD)

Conclusion: On-demand prices are similar across all three, but AWS and Azure have deeper long-term reserved discounts, while GCP has the lowest Spot prices.

Free Tier Comparison

Item	AWS Free Tier	Azure Free	GCP Free Tier
New User Period	12 months	12 months	90 days + permanent free items
Free Credit	None	$200 (within 30 days)	$300 (within 90 days)
EC2/VM Free	750 hours t2.micro/month	750 hours B1S/month	1 e2-micro (permanent)
Storage Free	5 GB S3	5 GB Blob	5 GB Cloud Storage
Database Free	750 hours RDS	250 GB SQL	1 GB Firestore/day

Conclusion: GCP's permanent free VM is most friendly for long-term learning or small projects; Azure's $200 credit is suitable for short-term trials.

For deep dive into AWS cost optimization, see AWS Pricing Complete Guide.

Taiwan Market Support Comparison

For Taiwan enterprises, local support is an important consideration.

Taiwan Data Center Information

Item	AWS	Azure	GCP
Taiwan Data Center	Launched 2025 (ap-northeast-4)	None (nearest: Hong Kong, Japan)	None (nearest: Hong Kong)
Latency (from Taipei)	<5ms (Taiwan), 40ms (Tokyo)	30-40ms (Hong Kong)	30-40ms (Hong Kong)
Data Residency	Available in Taiwan	Requires Hong Kong or Japan	Requires Hong Kong or Tokyo

Major Difference: AWS is currently the only major cloud provider with a data center in Taiwan, a decisive advantage for applications with data residency requirements or latency sensitivity.

Taiwan Partners and Support

Item	AWS	Azure	GCP
Number of Partners	10+ (eCloudvalley, CKmates, CloudRiches, etc.)	5+ (Systex, Acer Cloud, etc.)	3+ (CloudMile, PRHD, etc.)
Chinese Technical Support	Through partners, limited Chinese from AWS direct	Through partners, Chinese from Microsoft	Through partners
Taiwan Office	Yes (Taipei)	Yes (Taipei)	Yes (Taipei)
Local Events	Summit, active User Groups	Ignite, community events	Cloud Summit, community events

Conclusion: All three platforms have considerable support in Taiwan. AWS partner ecosystem is most mature; Azure is most convenient for existing Microsoft customers.

For more AWS Taiwan resources, see AWS Taiwan Resources Complete Guide.

Each platform has pros and cons; the key is finding the best fit for your business

Cloud selection needs to consider existing tech stack, team capabilities, budget, compliance requirements, and multiple factors. CloudInsight provides neutral cloud consulting services, with no preference for any platform—we only recommend what's best for you. Schedule a free consultation.

How to Choose a Cloud Platform

After all these comparisons, how do you decide? Here are practical recommendations.

Choose by Industry

Industry	Recommended Platform	Reason
Finance	AWS, Azure	AWS has most compliance certifications, Azure has Microsoft financial industry experience
Manufacturing	Azure, AWS	Azure IoT integration strong, AWS industrial IoT services complete
Retail/E-commerce	AWS	EC2 Auto Scaling mature, most CDN locations
Gaming	AWS, GCP	AWS GameLift, GCP network performance excellent
Media/Entertainment	AWS, GCP	AWS media services most complete, GCP YouTube infrastructure experience
Startups	GCP, AWS	GCP best free tier, AWS most community resources
Government/Public Sector	AWS, Azure	Both have GovCloud solutions

Choose by Technical Requirements

Requirement	Recommended Platform	Reason
Microsoft Tech Stack (.NET, SQL Server)	Azure	Best native integration
Open Source Stack (Linux, PostgreSQL)	AWS, GCP	Both have good support
Kubernetes	GCP	GKE is K8s best implementation
Big Data Analytics	GCP	BigQuery is industry benchmark
AI/ML (Using Pre-trained Models)	Depends on which model	Claude→AWS, GPT-4→Azure, Gemini→GCP
AI/ML (Training Custom Models)	AWS, GCP	SageMaker most comprehensive, Vertex AI excellent BigQuery integration
Hybrid Cloud	Azure	Azure Arc has strongest cross-cloud management
Need Taiwan Data Residency	AWS	Currently only one with Taiwan data center

Choose by Budget

Budget Consideration	Recommended Strategy
Limited Starting Capital	GCP permanent free VM + $300 credit
Can Prepay Commitment	AWS/Azure 3-year Reserved has deepest discounts
Don't Want to Prepay but Want Savings	GCP auto Sustained Use Discount
Unstable Workloads	All three Spot/Preemptible work, GCP slightly cheaper
Need Local Invoices	Buy through local partners (all three available)

Multi-Cloud Strategy Considerations

More enterprises are adopting multi-cloud strategies, but this doesn't mean "use everything":

Reasonable Multi-Cloud Strategy:

• Primary workloads on single platform (reduce complexity)
• Specific services on strongest platform (e.g., BigQuery on GCP)
• Disaster recovery on second cloud

Not Recommended Multi-Cloud Strategy:

• Spreading across multiple clouds without clear reasons
• Pretending multi-cloud for pricing negotiation

Seven Dimensions Summary Comparison

Comparison Dimension	AWS	Azure	GCP
Service Breadth	5/5	4/5	3/5
Enterprise Features	5/5	5/5	4/5
AI/ML	4/5	5/5 (GPT-4)	5/5 (Gemini, BigQuery ML)
Data Analytics	4/5	4/5	5/5
Kubernetes	4/5	4/5	5/5
Pricing	3/5	3/5	4/5
Taiwan Support	5/5 (has data center)	4/5	3/5
Learning Curve	3/5 (steeper)	4/5 (easy for MS users)	4/5 (intuitive interface)

FAQ

Q1: Is Highest Market Share Best?

Not necessarily. AWS's highest market share means most mature ecosystem, easiest to find talent, most documentation, but doesn't mean best for every scenario. Choice should be based on your specific needs.

Q2: Can I Switch Cloud Platforms Later?

Yes, but it's expensive. Cloud migration typically takes 6-18 months, with downtime risks and relearning costs. Evaluate carefully before choosing.

Q3: Which Cloud Certification is Most Valuable?

From job market perspective, AWS certification demand is highest, Azure second, GCP third. But this reflects market share, not technical superiority.

Q4: Which Should Startups Choose?

Depends on your tech stack and target market. If using Google technologies (Firebase, Kubernetes), GCP integration is best. If targeting B2B enterprise customers, AWS or Azure compliance certifications are more complete. GCP's free tier is most friendly for startups.

Q5: Which to Choose in the AI Era?

Depends on which model you want to use:

• Want Claude: Choose AWS
• Want GPT-4/ChatGPT: Choose Azure
• Want Gemini or value cost: Choose GCP

If still uncertain, AWS Bedrock's multi-model support offers most flexibility.

Q6: Are There Special Considerations for Taiwan Enterprises?

Yes. If there are data residency regulatory requirements (like financial industry), AWS Taiwan data center is currently the only choice. If already heavily using Microsoft products (Office 365, Teams), Azure integration will be smoother.

Next Steps

Choosing a cloud platform is a long-term decision. Recommendations:

1. Clearly List Requirements: Necessary features, budget, compliance requirements
2. Do PoC Testing: Use free tier to actually try out
3. Consult Professional Opinions: Find neutral cloud consultants to evaluate
4. Plan Migration Path: Don't rush into full migration

If you've decided to use AWS, you can start deep learning from the AWS Complete Guide.

Tell Us Your Needs, We Give You Neutral Advice

CloudInsight is an independent cloud consulting company with partnerships with all three major cloud platforms, with no preference for any. We'll recommend the most suitable platform and architecture based on your actual needs. Schedule a free consultation now, let professional consultants help you make the right choice.

Further Reading

• AWS Complete Guide: Comprehensive Learning Resources from Beginner to Advanced
• AWS EC2 Complete Tutorial: Instance Types, Pricing, Setup Steps
• AWS AI Services Complete Guide: Bedrock, SageMaker, AI Certification Introduction
• AWS Pricing Complete Guide: Pricing Models, Calculator Tutorial, Cost-Saving Tips
• AWS Taiwan Resources Complete Guide: Partners, Salaries, Events, Data Center Information

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Illustration: Seven Dimensions Comparison Radar Chart

Scene Description: Seven dimensions comparison radar chart. Seven axes for Service Breadth, Enterprise Features, AI/ML, Data Analytics, Kubernetes, Pricing, Taiwan Support. Three lines representing AWS (orange), Azure (blue), GCP (colorful), showing relative strength of each platform across dimensions.

Visual Focus:

• Main content clearly presented

Required Elements:

• Key elements as described

Chinese Text to Display: None

Color Tone: Professional, clear

Elements to Avoid: Abstract graphics, gears, glowing effects

Slug: cloud-service-comparison-matrix

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