Object storage manages data as discrete units called objects within a flat address space, removing the complexity of hierarchical file systems. Each object includes the raw data, extensible metadata, and a unique identifier. Applications interact with the storage using HTTP/HTTPS methods such as GET, PUT, and DELETE, typically via the S3-compatible API.
Unlike block storage, object storage is designed for unstructured data. It does not allow incremental updates; modifying a single byte requires replacing the entire object. This architecture enables massive horizontal scalability, allowing clusters to grow to exabyte scales by simply adding new storage nodes without performance degradation.
Use Cases
It is the primary choice for storing static web assets, database backups, long-term archives, and massive datasets for AI/ML training. It is optimized for high throughput and durability rather than low-latency random access, making it unsuitable for running operating systems or active databases.
Technical fact: Object storage systems often use WORM (Write Once, Read Many) models and eventual consistency. This ensures that data remains immutable and protected against accidental overwrites while maintaining high availability across multiple geographic regions.