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Cloud service providers: Google Cloud Platform (GCP) vs. Microsoft Azure

Quick Verdict

Both Google Cloud Platform (GCP) and Microsoft Azure are strong contenders in the cloud computing market, each offering a wide array of services and features. GCP stands out with its custom machine types, high-performance networking, and detailed pricing information. Azure distinguishes itself with its hybrid cloud capabilities and cost management tools. The best choice depends on specific needs and priorities.

Key features – Side-by-Side

AttributeGoogle Cloud Platform (GCP)Microsoft Azure
Compute Engine Pricing and Options
Virtual Machine Scalability
Storage Options and Pricing
Database Services Offered
Networking Capabilities and Performance
AI and Machine Learning Services
Data Analytics Tools
Security Features and Compliance
Developer Tools and Support
Geographic Region Availability
Hybrid Cloud Capabilities
Cost Management and Optimization Tools

Overall Comparison

GCP Compute Engine: n1-standard-1 ~$0.10/hour (US). GCP Storage: Standard $0.020/GB, Nearline $0.010/GB, Coldline $0.004/GB, Archive $0.00099/GB (monthly). Azure LRS Archive Block Blob storage: starts at $0.00081 / GB per month (3 years reserved capacity). GCP Regions: 47. GCP Zones: 127. Azure VMSS supports up to 1,000 VM instances. GCP Spot VMs offer up to 91% discounts.

Pros and Cons

Google Cloud Platform (GCP)

Pros:
  • Custom machine types for tailored VMs
  • Significant discounts with Spot VMs and committed use contracts
  • Comprehensive suite of database services (SQL and NoSQL)
  • High-performance global networking via Google's private fiber network
  • Comprehensive AI/ML toolkit with Vertex AI and AutoML
  • Scalable data analytics tools like BigQuery and Dataflow
  • Robust security features and compliance certifications
  • Cost Management Suite for monitoring and optimizing costs
  • Global availability with multiple regions and zones
Cons:
  • No major disadvantages reported.

Microsoft Azure

Pros:
  • Wide range of computing options
  • Comprehensive suite of database services
  • Robust AI and machine learning services
  • Global presence with services available in numerous geographic regions
  • Tools to monitor, allocate, and optimize cloud spending
Cons:
  • No major disadvantages reported.

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