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.
Best practices
- PERF03-BP01 Use a purpose-built data store that best supports your data access and storage requirements
- PERF03-BP02 Evaluate available configuration options for data store
- PERF03-BP03 Collect and record data store performance metrics
- PERF03-BP04 Implement strategies to improve query performance in data store
- PERF03-BP05 Implement data access patterns that utilize caching