concept

Data Tiering

Data tiering is a storage management strategy that organizes data into different tiers based on attributes like access frequency, performance requirements, and cost. It involves automatically moving data between high-performance, high-cost tiers (e.g., SSDs) and lower-performance, lower-cost tiers (e.g., HDDs or cloud storage) to optimize resource usage and reduce expenses. This concept is widely applied in data centers, cloud computing, and big data systems to balance performance and cost-effectiveness.

Also known as: Storage Tiering, Data Lifecycle Management, Hot-Cold Data Management, Tiered Storage, Hierarchical Storage Management
🧊Why learn Data Tiering?

Developers should learn data tiering when building or managing systems with large datasets, such as data lakes, enterprise applications, or cloud-based services, to improve efficiency and cut storage costs. It is particularly useful in scenarios with varying data access patterns, like hot data requiring fast retrieval and cold data needing archival, ensuring optimal performance without overspending on high-end storage for all data.

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