Storage

Blob Storage: Binary Large Object Management

Blob storage specializes in storing binary large objects—unstructured data like images, videos, documents, and backups. While often used interchangeably with object storage, blob storage typically refers to cloud provider implementations (like Azure Blob Storage) optimized for specific cloud ecosystems. Understanding blob storage capabilities enables leveraging cloud storage services effectively for diverse application needs.

Blob Types

Block Blobs are optimized for uploading large amounts of data efficiently. They consist of blocks that can be uploaded independently and in parallel, then committed as a complete blob. This makes them ideal for documents, media files, and general-purpose storage. Each block blob can store up to 190 TB.

Block Storage: High-Performance Persistent Storage

Block storage provides raw storage volumes that appear as hard drives to operating systems and applications. Unlike file or object storage, block storage operates at the block level, giving applications direct control over data organization. This makes block storage ideal for databases, virtual machines, and applications requiring low-latency, high-throughput storage with direct volume access.

Fundamental Concepts

Blocks are fixed-size chunks (typically 512 bytes to 1MB) into which the volume is divided. Applications read and write at block granularity, allowing precise control over I/O operations.

Data Lakes: Centralized Repository for All Data

Data lakes are centralized repositories that store vast amounts of structured and unstructured data at any scale. Unlike traditional databases that require defining schemas upfront, data lakes store raw data in its native format, deferring schema definition until the data is read (schema-on-read). This flexibility makes data lakes ideal for big data analytics, machine learning, and consolidating diverse data sources into a single platform.

Core Principles

Store Everything is fundamental to data lakes. Keep all data—operational logs, clickstreams, IoT sensors, transaction records—in original formats without filtering or transformation. Storage is cheap; valuable insights might come from data initially deemed unimportant.

Distributed File Systems: Shared Storage at Scale

Distributed file systems provide shared file storage across multiple servers, presenting a unified view of files to clients while distributing data across a cluster for scalability and fault tolerance. Unlike object storage’s flat namespace, distributed file systems maintain hierarchical directory structures and POSIX semantics, making them suitable for applications expecting traditional file system behavior at massive scale.

Key Characteristics

POSIX Compatibility means distributed file systems support standard file operations: open, read, write, seek, and close. Applications written for local file systems often work with distributed file systems without modification, simplifying migration and adoption.

Object Storage: Scalable Unstructured Data Storage

Object storage is a data storage architecture that manages data as objects rather than blocks or files. Each object contains data, metadata, and a unique identifier, making object storage ideal for large volumes of unstructured data like images, videos, backups, and logs. Cloud services like Amazon S3, Google Cloud Storage, and Azure Blob Storage have made object storage the de facto standard for cloud-based data storage.

Core Concepts

Objects are the fundamental storage units, consisting of the data itself (the object’s payload), metadata (key-value pairs describing the object), and a unique identifier (key) used to retrieve the object. Objects can range from bytes to terabytes in size.