Storage

Table of Contents

• Azure Disks
• Azure Blob Containers
• Azure File Shares
• Azure Queues
• Azure Tables
• Azure Data Box
• Azure Data Lake Storage

Azure Disks

• Purpose: Persistent storage for Azure VMs.
• Key Capabilities:
  • Managed or unmanaged disk options.
  • Different performance tiers (Standard HDD, Standard SSD, Premium SSD, Ultra Disk).
• Typical Use Cases:
  • VM operating system and data disks.
  • High-performance storage for I/O-intensive workloads.

Azure Blob Containers

• Purpose: Object storage solution for unstructured data.
• Key Capabilities:
  • Hot, Cool, and Archive tiers for cost optimization.
  • Scalable, cost-effective data storage for images, videos, backups.
• Typical Use Cases:
  • Data lake storage for analytics.
  • Media content delivery.
  • Backup and disaster recovery.

Azure File Shares

• Purpose: Fully managed file share service using the SMB or NFS protocol.
• Key Capabilities:
  • Shared file access across multiple VMs or on-premises.
  • Integration with Active Directory for access control.
• Typical Use Cases:
  • Lift-and-shift legacy applications that use file shares.
  • Centralized file storage and collaboration.

Azure Queues

• Purpose: Messaging service for decoupling and scaling application components.
• Key Capabilities:
  • Simple, asynchronous message queue.
  • Durable storage of messages.
• Typical Use Cases:
  • Microservices communication.
  • Asynchronous task processing.

Azure Tables

• Purpose: NoSQL key-value store for high-volume data.
• Key Capabilities:
  • Schemaless design.
  • Scalable and cost-effective for large datasets.
• Typical Use Cases:
  • IoT data ingestion.
  • Storing user profiles or session data.

Azure Data Box

• Purpose: Physical devices to securely transfer large amounts of data to Azure.
• Key Capabilities:
  • Various device sizes and types.
  • Encryption in transit and at rest.
• Typical Use Cases:
  • One-time data migration or bulk data import.
  • Offline data transfer when network bandwidth is limited.

Azure Data Lake Storage

• Purpose: Hyperscale repository for big data analytics workloads.
• Key Capabilities:
  • High-performance, hierarchical file system for analytics.
  • Integration with Azure analytics services (Databricks, Synapse).
• Typical Use Cases:
  • Data lake for enterprise analytics pipelines.
  • Big data processing and machine learning.