Cloud storage is the delivery of on-demand data storage services over the Internet, enabling organizations to store, manage, and access data without maintaining physical storage infrastructure. Cloud providers like AWS, Azure, and Google Cloud offer multiple storage types (object, block, file) optimized for different workloads, with pricing models based on storage capacity, access frequency, and data transfer. The key mental model: cloud storage is not one thing — it's a spectrum of storage services ranging from ultra-fast block storage for databases to ultra-cheap archival storage for compliance data, each with distinct performance characteristics, durability guarantees, and cost structures. In 2026, the spectrum now extends to AI-native storage (S3 Vectors, S3 Tables, GCS Rapid) purpose-built for vector embeddings, tabular analytics, and GPU-saturating training workloads. Understanding when to use object storage vs. block vs. file storage, how to apply lifecycle policies to automatically transition data between storage classes, and how to implement proper security and redundancy configurations are essential skills for optimizing both cost and performance in cloud environments.
What This Cheat Sheet Covers
This topic spans 23 focused tables and 181 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.
Table 1: Storage Types
The four fundamental storage models have distinct access patterns and cost structures. Choosing the wrong type for a workload is the most common cause of both performance problems and unnecessarily high cloud bills.
| Type | Example | Description |
|---|---|---|
aws s3 cp file.txt s3://bucket/key | • Stores data as discrete objects with metadata in a flat namespace, accessed via HTTP APIs • Ideal for unstructured data like images, videos, backups, and data lakes | |
aws ec2 create-volume --size 100 --volume-type gp3 | • Provides raw storage volumes attached to compute instances at the block level • Optimal for databases and transactional workloads requiring low latency and high IOPS |