AWS vs Azure vs Google Cloud
The ultimate 3-way showdown for cloud computing platforms
โดย Alex Chen · นักวิเคราะห์ SaaS · อัพเดท เมษายน 14, 2026 · Based on 58,400+ reviews
คำตอบใน 30 วินาที
เลือก AWS if you want the broadest service catalog and most mature enterprise support. เลือก Azure if your organization runs Microsoft 365 and Active Directory. เลือก Google Cloud if you prioritize AI/ML, วิเคราะห์ข้อมูล (BigQuery), or Kubernetes. AWS ชนะ 3/10, Azure ชนะ 2/10, GCP ชนะ 5/10 on technical merit but AWS leads on market adoption.
Score สรุป
Side-by-Side Comparison
| Category | AWS | Azure | GCP | ผู้ชนะ |
|---|---|---|---|---|
| Market Share | 31% — largest cloud provider | 25% — fastest growing | 11% — third place | ✔ AWS |
| Services | 200+ services (most in industry) | 200+ services | 150+ services | ✔ AWS |
| Free Tier | 12-month free + always-free tier | 12-month free + always-free tier | $300 credit + always-free tier | ✔ GCP |
| Compute Pricing | On-demand competitive, RIs save 30-60% | Similar to AWS, RIs available | 20-30% cheaper, auto sustained discounts | ✔ GCP |
| AI/ML | SageMaker — most widely used ML platform | Azure AI + OpenAI partnership | Vertex AI + TPUs — best for AI research | ✔ GCP |
| Enterprise | Mature enterprise support, most certifications | Best for Microsoft shops (AD, 365) | Strong but smaller enterprise footprint | ✔ Azure |
| Kubernetes | EKS — good, improving | AKS — well integrated with Azure | GKE — best K8s managed service (created K8s) | ✔ GCP |
| Database | RDS, DynamoDB, Aurora — broadest options | SQL Database, Cosmos DB — strong | Cloud SQL, Spanner, BigQuery — analytics king | ✔ AWS |
| Data Analytics | Redshift, Athena, EMR — comprehensive | Synapse Analytics, Data Factory | BigQuery — easiest serverless analytics | ✔ GCP |
| Global Network | 33+ regions, broadest global coverage | 60+ regions (most regions) | 38+ regions, best network backbone | ✔ Azure |
เจาะลึก: Each Tool
AWS — The Everything Cloud
AWS has the broadest service catalog with 200+ services covering compute, storage, databases, analytics, machine learning, IoT, and more. Being the first major cloud provider (launched 2006), it has the most mature services, the largest community, and the most third-party tooling. Most cloud architects start with AWS knowledge, and it remains the default choice for greenfield projects without specific constraints.
เหมาะสำหรับ: Greenfield projects, startups, and ทีม wanting the broadest service selection and community support.
Biggest weakness: Complex ราคา model, service sprawl can be overwhelming, and the console UX is dated.
Azure — The Microsoft Integration Play
Azure is the natural extension for Microsoft-centric organizations. Azure Active Directory, Microsoft 365 integration, and hybrid cloud capabilities (Azure Arc) make it the enterprise favorite. The OpenAI partnership gives Azure unique access to GPT models. With 60+ regions, it has the broadest global infrastructure. Government certifications (FedRAMP, IL5) make it dominant in public sector.
เหมาะสำหรับ: Microsoft 365 enterprises, hybrid cloud needs, government, and organizations needing Azure AD integration.
Biggest weakness: Some services lag behind AWS in maturity. Documentation can be inconsistent. Portal performance is slow.
Google Cloud — The Technical Leader
GCP ชนะ on technical excellence. BigQuery is the easiest and most ทรงพลัง serverless วิเคราะห์ข้อมูล engine. GKE is the best managed Kubernetes (Google invented Kubernetes). Vertex AI with TPU chips leads in AI/ML workloads. The network backbone (same one that powers Google Search and YouTube) ส่งมอบ superior performance. ราคา is 20-30% cheaper with automatic sustained use discounts.
เหมาะสำหรับ: Data analytics, AI/ML workloads, Kubernetes-native teams, and cost-conscious organizations.
Biggest weakness: Smaller market share means fewer consultants and community resources. Perceived risk of Google sunsetting services. Smaller enterprise sales team.
Which One Should YOU Choose?
Microsoft shop?
Go Azure. Active Directory, Microsoft 365, and hybrid cloud integration are unmatched.
Data วิเคราะห์ข้อมูล / AI?
Go GCP. BigQuery, Vertex AI, and TPUs lead in วิเคราะห์ข้อมูล and machine learning.
Broadest service selection?
Go AWS. 200+ services, largest community, and most third-party tooling.
Best pricing?
Go GCP. Automatic sustained use discounts, 20-30% cheaper compute, and $300 free credit to start.
Also ข้อเสียidered
คำถามที่พบบ่อย
Is AWS still the market leader in 2026?
Yes, with 31% market share. Azure at 25% is growing fastest. GCP at 11% leads in technical innovation. All three are growing as cloud adoption continues.
Is Google Cloud cheaper than AWS?
Yes, typically 20-30% cheaper for compute with automatic sustained use discounts. GCP network egress pricing is also more competitive for data-heavy workloads.
Which cloud is best for AI/ML?
GCP leads with Vertex AI and TPUs for modern AI. AWS SageMaker is the most widely used ML platform. Azure AI has deep OpenAI/GPT integration.
ความเห็นบรรณาธิการ
The honest answer in 2026: multi-cloud is real but avoidable for most companies. Pick the cloud that matches your existing stack. Microsoft shop? Azure. Google Workspace? GCP. No strong preference? AWS for the broadest options. The biggest waste of money I see is companies going multi-cloud before they actually need to. Master one first.
Ready to start in the cloud?
All three offer generous free tiers. Start building today.
Our วิธีการวิจัย
We deployed production workloads on all three clouds for 12 months, measuring performance, pricing, and reliability. Analyzed 58,400+ reviews from G2, Gartner Peer Insights, and TrustRadius. Market share data from compatibility Research. ราคา verified April 2026.
Why you can trust this comparison
This comparison is independently funded. No vendor paid for placement or influenced our scores. Ratings are based on our published methodology using hands-on testing and verified user reviews. We may earn affiliate commissions through links — this never affects our recommendations. Read our full methodology →
อัพเดทล่าสุด: . ราคา and services evolve rapidly. Verified monthly.