Optimize your database storage for Oracle workloads on AWS, Part 1: Using ADO and ILM data compression policies
Database Blog
This blog post discusses techniques to optimize storage for Oracle database workloads on AWS using Oracle's built-in features like Heat Map, Automatic Data Optimization (ADO), and Information Lifecycle Management (ILM) policies. It covers two approaches:
Specifically, the article covers:
- Enabling Heat Map tracking and setting up a sample partitioned table
- Automatic data compression based on data access pattern using ADO segment-level and row-level compression policies
- How ADO leverages Heat Map data and ILM policies to automate compression of infrequently accessed data
- Examples demonstrating the compression policies and their impact on storage reduction
- Conclusion summarizing the benefits of using these Oracle features on AWS for optimizing database storage
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