Data management - Performance Efficiency Pillar

Data management

The optimal data management solution for a particular system varies based on the kind of data type (block, file, or object), access patterns (random or sequential), required throughput, frequency of access (online, offline, archival), frequency of update (WORM, dynamic), and availability and durability constraints. Well-Architected workloads use purpose-built data stores which allow different features to improve performance.

This focus area shares guidance and best practices for optimizing data storage, movement and access patterns, and performance efficiency of data stores.