AWS vs Azure Storage: A Technical Comparison for Cloud Architects

Choosing the wrong storage service is one of the fastest ways to tank your cloud infrastructure's performance and budget. Whether you're working with AWS or Azure, understanding the fundamental differences between object storage, block storage, and file systems isn't optional—it's critical.

AWS Storage Services: S3, EBS, and EFS

S3: Object Storage

S3 is designed for storing unstructured data accessible via HTTP/HTTPS APIs. It's not a filesystem and cannot be mounted as a traditional disk.

Use cases:

• Static assets (images, CSS, JavaScript)
• Application backups
• Data lakes and archives
• Content distribution

Key characteristics:

• Unlimited scalability
• HTTP-based access only
• Pay-per-use model with no capacity planning required
• Multiple storage classes for cost optimization

EBS: Block Storage

EBS provides block-level storage volumes that attach to EC2 instances. Critical limitation: one EBS volume can only attach to a single instance at a time (except for multi-attach enabled io1/io2 volumes in specific configurations).

Use cases:

• Boot volumes for EC2 instances
• Database storage requiring consistent IOPS
• Applications requiring low-latency block storage

Key characteristics:

• Single instance attachment (standard configuration)
• Provisioned IOPS for guaranteed performance
• Snapshot capability for backups
• AZ-specific (not cross-AZ by default)

EFS: Network File System

EFS provides a fully managed NFS that can be mounted concurrently by multiple EC2 instances across multiple Availability Zones.

Use cases:

• Shared application data between instances
• Content management systems
• Development environments
• Home directories

Key characteristics:

• Concurrent multi-instance access
• Automatic scaling based on usage
• POSIX-compliant filesystem
• Higher latency than EBS but shared access capability

Cost Optimization: S3 Storage Classes

S3 storage costs can spiral out of control if you're not using the appropriate storage class. Here's the breakdown:

S3 Standard

• Cost: ~$0.023/GB per month
• Use case: Frequently accessed data
• Access pattern: Multiple times per month

S3 Intelligent-Tiering

• Cost: Automatic movement between tiers based on access patterns
• Use case: Unpredictable access patterns
• Trade-off: Small monitoring fee but automatic optimization

S3 Glacier Instant Retrieval

• Cost: ~75% cheaper than Standard
• Use case: Data accessed quarterly
• Retrieval: Milliseconds

S3 Glacier Flexible Retrieval / Deep Archive

• Cost: Up to 90% cheaper than Standard
• Use case: Long-term archives, compliance data
• Retrieval: Minutes to hours

Cost optimization strategy: Analyze your access patterns. Data that hasn't been accessed in 90+ days is a prime candidate for Glacier tiers. Implement lifecycle policies to automatically transition objects based on age and access patterns.

Azure Storage Services: Blob, File, and Disk

Azure's storage model mirrors AWS but with different naming conventions and slight architectural differences.

Blob Storage (equivalent to S3)

• Hot tier: Frequently accessed data
• Cool tier: Infrequently accessed, 30-day minimum
• Archive tier: Rarely accessed, 180-day minimum
• HTTP-based access with REST APIs
• Ideal for unstructured data at scale

File Storage (similar to EFS)

• SMB protocol support (also NFS)
• Mount as network drive on Windows/Linux
• Suitable for lift-and-shift migrations
• Premium tier available for performance-sensitive workloads

Disk Storage (equivalent to EBS)

• Managed disks for Azure VMs
• Standard HDD, Standard SSD, Premium SSD, Ultra Disk tiers
• Integrated snapshots and replication
• VM-specific attachment

Common Pitfalls and Solutions

Mistake #1: Using block storage for shared file access

Problem: Attempting to mount EBS/Disk across multiple instances
Solution: Use EFS/File Storage for multi-instance scenarios

Mistake #2: Storing everything in premium tiers

Problem: Paying for high-performance storage for cold data
Solution: Implement lifecycle policies and use appropriate storage classes

Mistake #3: Using object storage for high-frequency small file operations

Problem: Poor performance and high costs for millions of small files
Solution: Use block/file storage for high-frequency operations; object storage for large-scale archival

Decision Matrix

Need shared filesystem across instances?
→ AWS: EFS | Azure: File Storage

Need block storage for single VM?
→ AWS: EBS | Azure: Disk Storage

Need scalable object storage?
→ AWS: S3 | Azure: Blob Storage

Need to optimize costs for infrequently accessed data?
→ AWS: S3 Glacier tiers | Azure: Blob Cool/Archive tiers

Conclusion

Storage service selection directly impacts performance, availability, and costs. The key is matching your access patterns and requirements to the appropriate service:

• Object storage for scalability and HTTP access
• Block storage for single-instance performance
• File storage for shared access across instances

Analyze your data access patterns, implement lifecycle policies, and choose the right storage tier. The difference between a well-architected storage strategy and a poorly planned one can mean thousands of dollars per month and significant performance implications.

Don't default to premium tiers for everything. Most data doesn't need millisecond access times—and you shouldn't pay for what you don't need.

Need help optimizing your cloud storage architecture? Let's discuss your storage strategy.