Using faster, more expensive storage devices for hot data and slower, less expensive storage devices for cold data optimizes the performance of the queries that matter most while helping to reduce overall cost.
In this article
This paper presents a strategy for managing a multi-temperature data warehouse by storing data on different types of storage devices based on the temperature of the data. It provides guidelines and recommendations for each of the following tasks:
- Identifying and characterizing data into temperature tiers.
- Designing the database to accommodate multiple data temperatures.
- Moving data from one temperature tier to another.
- Using DB2® workload manager to allocate more resources to requests for hot data than to requests for cold data
- Planning a backup and recovery strategy when a data warehouse includes multiple data temperature tiers
The content of this paper applies to data warehouses based on version 10.1 or later of DB2 Database for Linux, UNIX, and Windows.
For additional best practices to help you implement multi-temperature data management with earlier versions of the DB2 software, refer to the best practice article "Multi-temperature data management" located in the Resources section.
|Article in PDF format||DB2V10_Multi-Temperature_0412.pdf||1663KB|
- Read the "Best Practices for multi-temperature data management" developerWorks article.
- Learn more about Best Practices for Physical Database Design.
- Learn more about "Best Practices for Workload Management".
- Learn more about the best practices for "Building a Recovery Strategy for an IBM Smart Analytics System Data Warehouse".
- Learn more about best practices for "DB2 for Linux, UNIX, and Windows".
- Follow developerWorks on Twitter.
- Watch developerWorks on-demand demos advanced functionality for experienced developers.
Get products and technologies
- Evaluate IBM products in the way that suits you best: Download a product trial, try a product online, use a product in a cloud environment, or spend a few hours in the SOA Sandbox learning how to implement Service Oriented Architecture efficiently.