Optimizations Differences: Autonomous Data Warehouse vs. Autonomous Transaction Processing

Autonomous Data Warehouse vs. Autonomous Transaction Processing

Question

Which two optimizations are different between Autonomous Data Warehouse and Autonomous Transaction Processing? (Choose two.)

Answers

Explanations

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A. B. C. D. E.

BC.

Autonomous Data Warehouse (ADW) and Autonomous Transaction Processing (ATP) are two different services provided by Oracle Autonomous Database Cloud. Although both ADW and ATP use the same Oracle Database technology and are managed autonomously, there are differences between them in terms of their optimizations.

The two optimizations that are different between ADW and ATP are:

B. Index Storage: In Autonomous Data Warehouse, the index storage is optimized for star queries with a column store index. This type of index is specifically designed to improve the performance of complex queries that involve joins and aggregations in large data sets typically found in data warehousing scenarios. In contrast, Autonomous Transaction Processing uses a row store index, which is more suitable for OLTP (Online Transaction Processing) workloads with frequent small transactions that require low latency.

E. Undo Management: Autonomous Transaction Processing includes a feature called "Flashback Query," which enables users to query data as it existed at a specific point in time. This requires the database to keep a history of changes made to the data, which is stored in an area called the undo tablespace. In contrast, Autonomous Data Warehouse does not provide this feature and therefore does not require as much undo space.

A. Backup Retention, Data Organization, and Memory Usage are not optimizations that differ between ADW and ATP:

  • Backup Retention: Both ADW and ATP provide automated backup and recovery, with a default retention period of 60 days for backups. This means that backups are retained for up to 60 days before being automatically deleted, unless the user specifies a different retention period.

  • Data Organization: Both ADW and ATP support various data organization schemes, including partitioning, compression, and clustering, to optimize the performance and storage efficiency of the database.

  • Memory Usage: Both ADW and ATP automatically manage the allocation and deallocation of memory resources, using a feature called "Auto Memory Management" to ensure that the database has sufficient memory for optimal performance.