Azure Blob Storage Overview
Azure Blob Storage is Microsoft's object storage solution for the cloud. It is optimized for storing massive amounts of unstructured data, such as text or binary data. Unstructured data is data that doesn't adhere to a particular data model or definition, such as images, videos, audio files, plain text files, documents, or any other type of binary data. You can also use Blob Storage to store data to be processed by a distributed processing framework or analyzed as a data warehouse.
Key Features
- Scalability: Designed to scale to exabytes of data.
- Durability and Availability: Offers multiple redundancy options to ensure your data is safe and accessible.
- Cost-Effectiveness: Various tiers (Hot, Cool, Archive) allow you to optimize costs based on access frequency.
- Security: Comprehensive security features including encryption at rest and in transit, access control, and network security.
- Versatility: Suitable for a wide range of use cases, from serving images and documents directly to a website, to storing files for distributed access, backup and restore, disaster recovery, and data analysis.
Core Components
Blob Storage organizes data using a hierarchical structure:
- Storage Account: A fundamental container for all Azure Storage services, including blobs, files, queues, and tables.
- Container: A logical grouping of blobs, similar to a directory in a file system. Containers must be named using lowercase letters and numbers.
- Blob: The fundamental unit of storage for unstructured data. There are three types of blobs:
- Block Blobs: Optimized for storing large amounts of unstructured data, such as image or video files, application executables, and documents.
- Append Blobs: Optimized for append operations, such as logging data from a virtual machine.
- Page Blobs: Optimized for random read and write operations, typically used for storing virtual hard disk (VHD) files for Azure virtual machines.
Common Use Cases
- Serving images or documents for direct website access.
- Storing files for backup, restore, disaster recovery, and archival.
- Storing data for streaming analysis by an on-premises or hosted service.
- Writing logs to be ingested by a cloud-hosted service or on-premises analytics service.
- Storing data for download by a client application.