AWS vs Google Cloud Platform
AW
Amazon Web Services (AWS)
Comprehensive cloud platform offering 200+ services for compute, storage, databases, and infrastructure.
Enterprise organizations, multi-workload deployments, teams needing legacy integration (Oracle, SAP), and companies requiring maximum third-party vendor support
VS
GC
Google Cloud Platform (GCP)
Enterprise cloud infrastructure with AI/ML services, advanced analytics, and global reach.
Data-driven startups, companies building ML-first products, organizations needing advanced analytics, and teams requiring rapid development velocity without infrastructure complexity
Short Answer
AWS dominates market share at 32% with the broadest service catalog (200+ services), while Google Cloud excels in data analytics, machine learning, and offers 25-40% lower compute costs for comparable workloads. AWS suits enterprises needing extensive integrations; Google Cloud wins for AI/ML-first organizations.
Our Verdict
AI-assistedChoose AWS if you need the broadest ecosystem, most third-party integrations, and enterprise support with established processes. Choose Google Cloud if you're building data-intensive applications, require advanced ML capabilities, want 25-35% lower infrastructure costs, or prioritize developer simplicity in analytics workflows.
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Amazon Web Services (AWS)7.1
7.9Google Cloud Platform (GCP)
Choose Amazon Web Services (AWS) if
Enterprise organizations, multi-workload deployments, teams needing legacy integration (Oracle, SAP), and companies requiring maximum third-party vendor support
Choose Google Cloud Platform (GCP) if
Data-driven startups, companies building ML-first products, organizations needing advanced analytics, and teams requiring rapid development velocity without infrastructure complexity
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Key Differences at a Glance
🔹
Global Market Share: Amazon Web Services (AWS) wins (32% vs 11%)
🔹
Total Services Offered: Amazon Web Services (AWS) wins (200+ vs 100+)
🔹
Compute Pricing (per vCPU/hour): Google Cloud Platform (GCP) wins ($0.0298 (e2-medium on-demand) vs $0.0416 (t3.medium on-demand))
Key Facts & Figures
| Metric | Amazon Web Services (AWS) | Google Cloud Platform (GCP) | Diff |
|---|---|---|---|
| Standard Storage Cost($/GB/month) | $0.023 | — | — |
| Archival Storage Cost($/GB/month) | $0.004 | — | — |
| Global Data Centers(regions) | 33 regions | 40+ regions | -18% |
| Market Share 2026(%) | 32% | — | — |
| Global Market Share (2026)(%) | 32% | 11% | +191% |
| Total Available Services(services) | 200+ | 100+ | +100% |
| Global Availability Zones(zones) | 33 | 42 | -21% |
| Pricing Model Complexity(simplicity score) | 5/10 | 9/10 | -44% |
| ML/AI Service Innovation Rating(score) | 8/10 | 10/10 | -20% |
| Windows/Active Directory Integration(native score) | 4/10 | 3/10 | +33% |
| Supported Cloud Providers(count) | AWS only | — | — |
| Global Geographic Regions(regions) | 33 regions | — | — |
| Availability Zones (AWS regions)(zones) | 105+ zones | — | — |
| Available Services/Integrations(count) | 190+ native services | — | — |
| Time to Provision Standard EC2 Instance(seconds) | 30-45 (via Console/CLI) | — | — |
| Monthly Cost (1 vCPU, 1GB RAM, Standard Instance)(USD) | $9.50 (t3.micro on-demand) | — | — |
| Outbound Data Transfer Cost per GB(USD) | $0.0116 | — | — |
| Global Data Center Regions(regions) | 33 regions | 40+ | -18% |
| Global Market Share(%) | 32% of global cloud infrastructure (2024) | 11% | +191% |
| Service Count(services) | 200+ | 100+ | +100% |
| Compute Cost (e2-medium equivalent)(USD/hour) | $0.0416 | $0.0298 | +40% |
| Data Transfer Out Cost(USD/GB) | $0.02 | $0.12 | -83% |
| ML Training Setup Time(hours) | 8-12 hours (SageMaker) | 2-3 hours (Vertex AI) | +300% |
| BigQuery Query Latency(seconds) | 15-30 seconds (Athena, 1TB scan) | 2-5 seconds (BigQuery, 1TB scan) | +543% |
| Enterprise Support Annual Cost(USD) | $15,000 | $12,500 | +20% |
| Kubernetes Integration Complexity(manual steps) | 18-25 steps (EKS setup) | 3-4 steps (GKE) | +514% |
| Available Cloud Services/Products(count) | 200+ | — | — |
| Free Tier Duration(months) | 12 months + always-free services | — | — |
| Premium Support Response Time(hours) | 1 hour (Business Support) | — | — |
| Monthly Cost for 10TB Egress Data Transfer(USD) | $116 (after 1GB free) | — | — |
| Minimum Setup Time(minutes) | 120 minutes | — | — |
| Minimum Monthly Cost(USD) | $4.34 (t3.micro EC2 only) | — | — |
| Global Edge Locations(locations) | 280+ CloudFront locations | 100+ via Cloud CDN | +180% |
| Average Cold Start Latency(milliseconds) | 125ms (Lambda standard) | — | — |
| Setup Time to First Deploy(minutes) | 45-60 (configure VPC, IAM, EC2, security groups) | — | — |
| Built-in Database Support(count) | 8+ (RDS, DynamoDB, Aurora, ElastiCache, Neptune, DocumentDB, Keyspaces, Timestream) | — | — |
| SLA Uptime Guarantee(percentage) | 99.99% (us-east-1 region) | — | — |
| Concurrent Connections per Instance(requests/second) | 50,000+ (t3.large EC2) | — | — |
| Estimated Learning Time for New Developer(hours) | 80-100 hours | — | — |
| Supported Programming Languages for IaC(languages) | 3 languages (YAML, JSON, TypeScript/Python/Java via CDK) | — | — |
| Available Services/Resources(services) | 200+ AWS-specific services (largest portfolio in cloud) | — | — |
| Free Tier Cost(USD/month) | Free (1 year, then pay-as-you-go infrastructure costs) | — | — |
| AWS Regions/Availability Zones(regions) | 33+ geographic regions with 105+ availability zones | — | — |
| Certified Professionals(people) | 1M+ AWS Certified professionals | — | — |
| Global Data Center Locations(regions) | 42 regions, 134 zones | 42 regions, 134 zones | — |
| Uptime SLA(percent) | 99.9% (Cloud DNS) | 99.9% (Cloud DNS) | — |
| Cold Start Latency(ms) | 500-2000ms | 500-2000ms | — |
| Integrated Services(count) | 200+ services | 200+ services | — |
| Monthly Free Credits/Tier(USD) | $300 | $300 | — |
| Data Egress Cost(USD/GB) | $0.12/GB | $0.12/GB | — |
| BigQuery/Analytics Equivalent Cost(USD per TB scanned) | $6.25 | $6.25 | — |
| Compute Instance (2vCPU, 8GB RAM)(USD/month) | $65-$78 | $65-$78 | — |
| Oracle Database License Discount(% savings) | No discount | No discount | — |
| Active Developer Community(estimated active developers) | 7.6 million | 7.6 million | — |
| Autonomous Database Uptime SLA(% availability) | 99.95% | 99.95% | — |
| AI/ML Model Catalog(pre-built models) | 40+ models in Vertex AI | 40+ models in Vertex AI | — |
| Cheapest Virtual Machine (Hourly)(USD) | $0.04/hour ($29.20/month) | $0.04/hour ($29.20/month) | — |
| Managed Database Types(count) | 25+ (including Spanner, Firestore, Bigtable) | 25+ (including Spanner, Firestore, Bigtable) | — |
| Free Trial Credits(USD) | $300 (90 days) | $300 (90 days) | — |
| Typical App Deployment Time(minutes) | 30-45 minutes | 30-45 minutes | — |
| Monthly Starting Cost(USD) | $50-200 | $50-200 | — |
| Apache Spark Query Performance Boost(x faster vs open-source) | 1.5-2x (Dataproc optimization) | 1.5-2x (Dataproc optimization) | — |
| Available Services(count) | 200+ | 200+ | — |
| BigQuery/Equivalent Query Speed (1TB dataset)(seconds) | 8-12 sec (native BigQuery) | 8-12 sec (native BigQuery) | — |
| Organizations Using Platform(count (thousands)) | 4,000,000+ (GCP users across Alphabet ecosystem) | 4,000,000+ (GCP users across Alphabet ecosystem) | — |
| Average Deployment Time(weeks) | 300-900 seconds (App Engine) | 300-900 seconds (App Engine) | — |
| Free Tier Compute(vCPU hours/month) | 300 e2-micro hours (App Engine) | 300 e2-micro hours (App Engine) | — |
| Native Database Options(count) | 8 (SQL, Firestore, Spanner, BigQuery, Datastore, Memorystore, AlloyDB, DynamoDB) | 8 (SQL, Firestore, Spanner, BigQuery, Datastore, Memorystore, AlloyDB, DynamoDB) | — |
| Compute Price (vCPU/hour)(USD) | $0.04-0.48 depending on machine type | $0.04-0.48 depending on machine type | — |
| Regions Available(regions) | 35+ cloud regions worldwide | 35+ cloud regions worldwide | — |
| Setup Complexity (1-10 scale)(difficulty) | 8/10 (requires IAM, VPC, networking knowledge) | 8/10 (requires IAM, VPC, networking knowledge) | — |
| Entry-Level Compute Cost (Monthly)(USD) | $19.25/month (e2-micro) | $19.25/month (e2-micro) | — |
| AI/ML Service Count(services) | 150+ (BigQuery, Vertex AI, Vision, NLP, etc.) | 150+ (BigQuery, Vertex AI, Vision, NLP, etc.) | — |
| Free Trial Credit(USD) | $300 (90 days) | $300 (90 days) | — |
| Time to Deploy Hello World(minutes) | 15-20 minutes | 15-20 minutes | — |
| Enterprise Support Starting Price(USD/month) | $500/month | $500/month | — |
All figures sourced from publicly available data. Last updated Jun 2026.
Key Differences
Amazon Web Services (AWS)
Attribute
Google Cloud Platform (GCP)
32%🏆
Global Market Share
11%
200+🏆
Total Services Offered
100+
$0.0416 (t3.medium on-demand)
Compute Pricing (per vCPU/hour)
$0.0298 (e2-medium on-demand)🏆
$5.00 (Athena equivalent)
BigQuery Query Cost (per TB scanned)
$5.00
SageMaker (good, separate tools)
AI/ML Native Capabilities
Vertex AI (integrated, 3x faster setup)🏆
$0.02/GB (first 1GB free)🏆
Data Transfer Out Pricing
$0.12/GB (no free tier)
$15,000+ (Business Support minimum)
Enterprise Support Cost (annual)
$12,500+ (Enhanced Support minimum)🏆
Global Market Share
Amazon Web Services (AWS)
32%🏆
Google Cloud Platform (GCP)
11%
Total Services Offered
Amazon Web Services (AWS)
200+🏆
Google Cloud Platform (GCP)
100+
Compute Pricing (per vCPU/hour)
Amazon Web Services (AWS)
$0.0416 (t3.medium on-demand)
Google Cloud Platform (GCP)
$0.0298 (e2-medium on-demand)🏆
BigQuery Query Cost (per TB scanned)
Amazon Web Services (AWS)
$5.00 (Athena equivalent)
Google Cloud Platform (GCP)
$5.00
AI/ML Native Capabilities
Amazon Web Services (AWS)
SageMaker (good, separate tools)
Google Cloud Platform (GCP)
Vertex AI (integrated, 3x faster setup)🏆
Data Transfer Out Pricing
Amazon Web Services (AWS)
$0.02/GB (first 1GB free)🏆
Google Cloud Platform (GCP)
$0.12/GB (no free tier)
Enterprise Support Cost (annual)
Amazon Web Services (AWS)
$15,000+ (Business Support minimum)
Google Cloud Platform (GCP)
$12,500+ (Enhanced Support minimum)🏆
Full Comparison
| Attribute | Amazon Web Services (AWS) | Google Cloud Platform (GCP) |
|---|---|---|
| Standard Storage Cost($/GB/month) | $0.023 | — |
| Archival Storage Cost($/GB/month) | $0.004 | — |
| Pricing Model Complexity(simplicity score) | 5/10 | 9/10 |
| Base Software Cost(USD/month) | Pay-per-use only | — |
| Terraform Cloud Team Plan Cost(USD/month per user) | N/A | — |
Show 21 more attributesMonthly Cost (1 vCPU, 1GB RAM, Standard Instance)(USD) $9.50 (t3.micro on-demand) — Outbound Data Transfer Cost per GB(USD) $0.0116 — Compute Cost (e2-medium equivalent)(USD/hour) $0.0416 $0.0298 Data Transfer Out Cost(USD/GB) $0.02 $0.12 Free Tier Duration(months) 12 months + always-free services — Monthly Cost for 10TB Egress Data Transfer(USD) $116 (after 1GB free) — Minimum Monthly Cost(USD) $4.34 (t3.micro EC2 only) — Free Tier Cost(USD/month) Free (1 year, then pay-as-you-go infrastructure costs) — Monthly Free Credits/Tier(USD) $300 — Pro Plan Cost(USD/month) Variable (usage-based) — Data Egress Cost(USD/GB) $0.12/GB — BigQuery/Analytics Equivalent Cost(USD per TB scanned) $6.25 — Compute Instance (2vCPU, 8GB RAM)(USD/month) $65-$78 — Oracle Database License Discount(% savings) No discount — Cheapest Virtual Machine (Hourly)(USD) $0.04/hour ($29.20/month) — Free Trial Credits(USD) $300 (90 days) — Monthly Starting Cost(USD) $50-200 — Free Tier Compute(vCPU hours/month) 300 e2-micro hours (App Engine) — Compute Price (vCPU/hour)(USD) $0.04-0.48 depending on machine type — Entry-Level Compute Cost (Monthly)(USD) $19.25/month (e2-micro) — Free Trial Credit(USD) $300 (90 days) — | ||
| AI/ML Model Flexibility | Multiple models via Bedrock | — |
| Hybrid Cloud Support Maturity | AWS Outposts (limited) | — |
| Global Data Centers(regions) | 33 regions | 40+ regions |
| Global Availability Zones(zones) | 33 | 42 |
| Global Geographic Regions(regions) | 33 regions | — |
| Availability Zones (AWS regions)(zones) | 105+ zones | — |
Show 3 more attributesGlobal Data Center Regions(regions) 33 regions 40+ Global Data Center Locations(regions) 42 regions, 134 zones — Regions Available(regions) 35+ cloud regions worldwide — | ||
| Container Serverless Performance | Fargate (feature-rich) | — |
| Market Share 2026(%) | 32% | — |
| Global Market Share (2026)(%) | 32% | 11% |
| Total Available Services(services) | 200+ | 100+ |
| ML/AI Service Innovation Rating(score) | 8/10 | 10/10 |
| Hybrid Cloud Support Level(capability) | Moderate (Outposts) | Good (Anthos) |
| Windows/Active Directory Integration(native score) | 4/10 | 3/10 |
| Developer Community Size(developers) | Largest | Growing |
| GitHub Stars(stars) | N/A (not a single GitHub repo) | — |
| Container/Kubernetes Strength(native integration) | Strong (ECS/EKS) | Best (GKE native) |
| BigQuery-Grade Analytics(capability) | Via Athena/Redshift | Native (BigQuery) |
| Supported Cloud Providers(count) | AWS only | — |
| Available Services/Integrations(count) | 190+ native services | — |
| Time to Provision Standard EC2 Instance(seconds) | 30-45 (via Console/CLI) | — |
| Global Edge Locations(locations) | 280+ CloudFront locations | 100+ via Cloud CDN |
| Average Cold Start Latency(milliseconds) | 125ms (Lambda standard) | — |
| Cold Start Latency(ms) | 500-2000ms | — |
| Autonomous Database Uptime SLA(% availability) | 99.95% | — |
Show 2 more attributesApache Spark Query Performance Boost(x faster vs open-source) 1.5-2x (Dataproc optimization) — BigQuery/Equivalent Query Speed (1TB dataset)(seconds) 8-12 sec (native BigQuery) — | ||
| GitHub Integration for IaC(native support) | AWS CloudFormation requires manual GitHub setup | — |
| Kubernetes Container Orchestration | Supported (GKE) - industry standard with advanced networking | — |
| Global Market Share(%) | 32% of global cloud infrastructure (2024) | 11% |
| Organizations Using Platform(count (thousands)) | 4,000,000+ (GCP users across Alphabet ecosystem) | — |
| Service Count(services) | 200+ | 100+ |
| Available Cloud Services/Products(count) | 200+ | — |
| AI/ML Service Availability(availability) | SageMaker, Bedrock, Forecast, Lookout, Kendra | — |
| Built-in Database Support(count) | 8+ (RDS, DynamoDB, Aurora, ElastiCache, Neptune, DocumentDB, Keyspaces, Timestream) | — |
| Integrated Services(count) | 200+ services | — |
Show 6 more attributesManaged Database Types(count) 25+ (including Spanner, Firestore, Bigtable) — Native Database Options(count) 8 (SQL, Firestore, Spanner, BigQuery, Datastore, Memorystore, AlloyDB, DynamoDB) — ML/AI Services(count) Vertex AI, TensorFlow, Vision API, NLP API, AutoML (5+ major services) — AI/ML Service Count(services) 150+ (BigQuery, Vertex AI, Vision, NLP, etc.) — Kubernetes (Managed)(null) GKE (Enterprise-grade, full API support) — Database Options(types) 15+ (Cloud SQL, Firestore, Bigtable, Spanner, Memorystore) — | ||
| ML Training Setup Time(hours) | 8-12 hours (SageMaker) | 2-3 hours (Vertex AI) |
| Kubernetes Integration Complexity(manual steps) | 18-25 steps (EKS setup) | 3-4 steps (GKE) |
| Supported Programming Languages for IaC(languages) | 3 languages (YAML, JSON, TypeScript/Python/Java via CDK) | — |
| BigQuery Query Latency(seconds) | 15-30 seconds (Athena, 1TB scan) | 2-5 seconds (BigQuery, 1TB scan) |
| Enterprise Support Annual Cost(USD) | $15,000 | $12,500 |
| Premium Support Response Time(hours) | 1 hour (Business Support) | — |
| Enterprise Support Starting Price(USD/month) | $500/month | — |
| Minimum Setup Time(minutes) | 120 minutes | — |
| Setup Time to First Deploy(minutes) | 45-60 (configure VPC, IAM, EC2, security groups) | — |
| Estimated Learning Time for New Developer(hours) | 80-100 hours | — |
| SLA Uptime Guarantee(percentage) | 99.99% (us-east-1 region) | — |
| Uptime SLA(percent) | 99.9% (Cloud DNS) | — |
| Concurrent Connections per Instance(requests/second) | 50,000+ (t3.large EC2) | — |
| Multi-Cloud Support(cloud providers) | AWS only | GCP only |
| Available Services/Resources(services) | 200+ AWS-specific services (largest portfolio in cloud) | — |
| AWS Regions/Availability Zones(regions) | 33+ geographic regions with 105+ availability zones | — |
| Certified Professionals(people) | 1M+ AWS Certified professionals | — |
| DDoS Protection | Basic included; Advanced requires paid add-on | — |
| Active Developer Community(estimated active developers) | 7.6 million | — |
| AI/ML Model Catalog(pre-built models) | 40+ models in Vertex AI | — |
| Native ML Pipeline Integration(rating) | Vertex AI (robust, separate service) | — |
| Typical App Deployment Time(minutes) | 30-45 minutes | — |
| AI/ML Service Maturity | Advanced (Vertex AI, AutoML, BigQuery ML) | — |
| Available Services(count) | 200+ | — |
| Data Lakehouse ACID Support(capability) | BigLake (preview), requires external ACID solutions | — |
| Average Deployment Time(weeks) | 300-900 seconds (App Engine) | — |
| Setup Complexity (1-10 scale)(difficulty) | 8/10 (requires IAM, VPC, networking knowledge) | — |
| Time to Deploy Hello World(minutes) | 15-20 minutes | — |
Amazon Web Services (AWS)
Google Cloud Platform (GCP)
Standard Storage Cost($/GB/month)
$0.023
—
Archival Storage Cost($/GB/month)
$0.004
—
Pricing Model Complexity(simplicity score)
5/10
9/10
Base Software Cost(USD/month)
Pay-per-use only
—
Terraform Cloud Team Plan Cost(USD/month per user)
N/A
—
Show 21 more attributes
Monthly Cost (1 vCPU, 1GB RAM, Standard Instance)(USD)
$9.50 (t3.micro on-demand)
—
Outbound Data Transfer Cost per GB(USD)
$0.0116
—
Compute Cost (e2-medium equivalent)(USD/hour)
$0.0416
$0.0298
Data Transfer Out Cost(USD/GB)
$0.02
$0.12
Free Tier Duration(months)
12 months + always-free services
—
Monthly Cost for 10TB Egress Data Transfer(USD)
$116 (after 1GB free)
—
Minimum Monthly Cost(USD)
$4.34 (t3.micro EC2 only)
—
Free Tier Cost(USD/month)
Free (1 year, then pay-as-you-go infrastructure costs)
—
Monthly Free Credits/Tier(USD)
$300
—
Pro Plan Cost(USD/month)
Variable (usage-based)
—
Data Egress Cost(USD/GB)
$0.12/GB
—
BigQuery/Analytics Equivalent Cost(USD per TB scanned)
$6.25
—
Compute Instance (2vCPU, 8GB RAM)(USD/month)
$65-$78
—
Oracle Database License Discount(% savings)
No discount
—
Cheapest Virtual Machine (Hourly)(USD)
$0.04/hour ($29.20/month)
—
Free Trial Credits(USD)
$300 (90 days)
—
Monthly Starting Cost(USD)
$50-200
—
Free Tier Compute(vCPU hours/month)
300 e2-micro hours (App Engine)
—
Compute Price (vCPU/hour)(USD)
$0.04-0.48 depending on machine type
—
Entry-Level Compute Cost (Monthly)(USD)
$19.25/month (e2-micro)
—
Free Trial Credit(USD)
$300 (90 days)
—
AI/ML Model Flexibility
Multiple models via Bedrock
—
Hybrid Cloud Support Maturity
AWS Outposts (limited)
—
Global Data Centers(regions)
33 regions
40+ regions
Global Availability Zones(zones)
33
42
Global Geographic Regions(regions)
33 regions
—
Availability Zones (AWS regions)(zones)
105+ zones
—
Show 3 more attributes
Global Data Center Regions(regions)
33 regions
40+
Global Data Center Locations(regions)
42 regions, 134 zones
—
Regions Available(regions)
35+ cloud regions worldwide
—
Container Serverless Performance
Fargate (feature-rich)
—
Market Share 2026(%)
32%
—
Global Market Share (2026)(%)
32%
11%
Total Available Services(services)
200+
100+
ML/AI Service Innovation Rating(score)
8/10
10/10
Hybrid Cloud Support Level(capability)
Moderate (Outposts)
Good (Anthos)
Windows/Active Directory Integration(native score)
4/10
3/10
Developer Community Size(developers)
Largest
Growing
GitHub Stars(stars)
N/A (not a single GitHub repo)
—
Container/Kubernetes Strength(native integration)
Strong (ECS/EKS)
Best (GKE native)
BigQuery-Grade Analytics(capability)
Via Athena/Redshift
Native (BigQuery)
Supported Cloud Providers(count)
AWS only
—
Available Services/Integrations(count)
190+ native services
—
Time to Provision Standard EC2 Instance(seconds)
30-45 (via Console/CLI)
—
Global Edge Locations(locations)
280+ CloudFront locations
100+ via Cloud CDN
Average Cold Start Latency(milliseconds)
125ms (Lambda standard)
—
Cold Start Latency(ms)
500-2000ms
—
Autonomous Database Uptime SLA(% availability)
99.95%
—
Show 2 more attributes
Apache Spark Query Performance Boost(x faster vs open-source)
1.5-2x (Dataproc optimization)
—
BigQuery/Equivalent Query Speed (1TB dataset)(seconds)
8-12 sec (native BigQuery)
—
GitHub Integration for IaC(native support)
AWS CloudFormation requires manual GitHub setup
—
Kubernetes Container Orchestration
Supported (GKE) - industry standard with advanced networking
—
Global Market Share(%)
32% of global cloud infrastructure (2024)
11%
Organizations Using Platform(count (thousands))
4,000,000+ (GCP users across Alphabet ecosystem)
—
Service Count(services)
200+
100+
Available Cloud Services/Products(count)
200+
—
AI/ML Service Availability(availability)
SageMaker, Bedrock, Forecast, Lookout, Kendra
—
Built-in Database Support(count)
8+ (RDS, DynamoDB, Aurora, ElastiCache, Neptune, DocumentDB, Keyspaces, Timestream)
—
Integrated Services(count)
200+ services
—
Show 6 more attributes
Managed Database Types(count)
25+ (including Spanner, Firestore, Bigtable)
—
Native Database Options(count)
8 (SQL, Firestore, Spanner, BigQuery, Datastore, Memorystore, AlloyDB, DynamoDB)
—
ML/AI Services(count)
Vertex AI, TensorFlow, Vision API, NLP API, AutoML (5+ major services)
—
AI/ML Service Count(services)
150+ (BigQuery, Vertex AI, Vision, NLP, etc.)
—
Kubernetes (Managed)(null)
GKE (Enterprise-grade, full API support)
—
Database Options(types)
15+ (Cloud SQL, Firestore, Bigtable, Spanner, Memorystore)
—
ML Training Setup Time(hours)
8-12 hours (SageMaker)
2-3 hours (Vertex AI)
Kubernetes Integration Complexity(manual steps)
18-25 steps (EKS setup)
3-4 steps (GKE)
Supported Programming Languages for IaC(languages)
3 languages (YAML, JSON, TypeScript/Python/Java via CDK)
—
BigQuery Query Latency(seconds)
15-30 seconds (Athena, 1TB scan)
2-5 seconds (BigQuery, 1TB scan)
Enterprise Support Annual Cost(USD)
$15,000
$12,500
Premium Support Response Time(hours)
1 hour (Business Support)
—
Enterprise Support Starting Price(USD/month)
$500/month
—
Minimum Setup Time(minutes)
120 minutes
—
Setup Time to First Deploy(minutes)
45-60 (configure VPC, IAM, EC2, security groups)
—
Estimated Learning Time for New Developer(hours)
80-100 hours
—
SLA Uptime Guarantee(percentage)
99.99% (us-east-1 region)
—
Uptime SLA(percent)
99.9% (Cloud DNS)
—
Concurrent Connections per Instance(requests/second)
50,000+ (t3.large EC2)
—
Multi-Cloud Support(cloud providers)
AWS only
GCP only
Available Services/Resources(services)
200+ AWS-specific services (largest portfolio in cloud)
—
AWS Regions/Availability Zones(regions)
33+ geographic regions with 105+ availability zones
—
Certified Professionals(people)
1M+ AWS Certified professionals
—
DDoS Protection
Basic included; Advanced requires paid add-on
—
Active Developer Community(estimated active developers)
7.6 million
—
AI/ML Model Catalog(pre-built models)
40+ models in Vertex AI
—
Native ML Pipeline Integration(rating)
Vertex AI (robust, separate service)
—
Typical App Deployment Time(minutes)
30-45 minutes
—
AI/ML Service Maturity
Advanced (Vertex AI, AutoML, BigQuery ML)
—
Available Services(count)
200+
—
Data Lakehouse ACID Support(capability)
BigLake (preview), requires external ACID solutions
—
Average Deployment Time(weeks)
300-900 seconds (App Engine)
—
Setup Complexity (1-10 scale)(difficulty)
8/10 (requires IAM, VPC, networking knowledge)
—
Time to Deploy Hello World(minutes)
15-20 minutes
—
Visual Comparison
Side-by-side comparison of numeric attributes
Pros & Cons
Amazon Web Services (AWS)
5 pros3 cons
Pros
- 200+ services with deepest breadth in database (DynamoDB, RDS, Aurora), networking, and containerization (ECS, EKS)
- Strongest marketplace ecosystem with 2,000+ third-party integrations
- Lowest data egress costs ($0.02/GB vs $0.12/GB on GCP)
- Most mature auto-scaling with predictive scaling capabilities
- 32% market share means largest talent pool and community support
Cons
- 25-35% higher compute costs than Google Cloud for equivalent workloads
- Complex pricing model with 150+ SKUs makes cost prediction difficult
- SageMaker ML tools require more manual configuration than Vertex AI
Google Cloud Platform (GCP)
5 pros3 cons
Pros
- 25-40% lower compute pricing ($0.0298/vCPU-hour vs AWS $0.0416)
- Vertex AI provides industry-leading ML operations with AutoML and unified feature store
- BigQuery (native columnar data warehouse) handles 1M+ queries/day with sub-second latency
- Simplest Kubernetes integration (GKE) with automatic cluster scaling included
- Superior data analytics stack (DataFlow, Looker, Analytics Hub)
Cons
- Only 11% market share with smaller third-party ecosystem (fewer pre-built connectors)
- Data egress costs 6x higher ($0.12/GB vs AWS $0.02/GB), locking users in
- Smaller enterprise customer base means fewer reference architectures and case studies
Frequently Asked Questions
Google Cloud is 25-40% cheaper on compute instances ($0.0298/vCPU-hour vs AWS $0.0416), but AWS has 6x lower data egress costs ($0.02/GB vs $0.12/GB). For data-heavy workloads with minimal egress, GCP wins; for multi-region deployments, AWS wins. Break-even typically occurs at 500GB+/month of data transfer.
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Last updated: June 21, 2026AI generated