Q14 — AWS SAA-C03 Ch.16

Question 14 of 100 | ← Chapter 16

Q1214. A company wants to move its on-premises Oracle database to an Amazon Aurora PostgreSQL DB cluster. The source database includes 500 GB of data,900 stored procedures and functions,and application source code with embedded SQL statements.The company understands there are some database code objects and custom features that may not be automatically converted and may need some manual intervention. Management would like to complete this migration as fast as possible with minimal downtime.Which tools and approach should be used to meet these requirements?

• A. Use AWS DMS to perform data migration and to automatically create all schemas with Aurora PostgreSQL.
• B. Use AWS DMS to perform data migration and use the AWS Schema Conversion Tool(AWS SCT) to automatically generate the converted code. ✓
• C. Use the AWS Schema Conversion Tool (AWS SCT) to automatically convert all types of Oracle schemas to PostgreSQL and migrate the data to Aurora
• D. Use the dump and pg_dump utilities for both data migration and schema conversion.

Correct Answer: B. Use AWS DMS to perform data migration and use the AWS Schema Conversion Tool(AWS SCT) to automatically generate the converted code.

Explanation

To meet the requirements of migrating an on-premises Oracle database to an Amazon Aurora PostgreSQL DB cluster quickly and with minimal downtime, the appropriate choice would be B. Use AWS DMS to perform data migration and use the AWS Schema Conversion Tool (AWS SCT) to automatically generate the converted code. Here's the detailed analysis:AWS Schema Conversion Tool (AWS SCT):Functionality: AWS SCT is a tool designed for database migration that helps users convert existing database schemas (including tables, views, stored procedures, etc.) from one database engine to another. It supports multiple source and target databases and can convert relational OLTP schemas or data warehouse schemas.Advantages: AWS SCT can scan application source code used for embedded SQL statements and convert them as part of the database schema conversion project. This helps reduce the manual effort required to modify application code. Additionally, AWS SCT can perform cloud-native code optimization by converting legacy Oracle functions to equivalent AWS services, aiding in the upgrade of applications alongside the database migration.Applicability: In this scenario, since the source database includes 900 stored procedures and functions, as well as embedded SQL statements in the application source code, using AWS SCT can automatically convert these code objects, minimizing the need for manual intervention.AWS Database Migration Service (AWS DMS):Functionality: AWS DMS is a serverless service that automates the entire database migration process, including data transfer, data transformation, and data validation. It supports multiple database types, including Oracle and PostgreSQL.Advantages: AWS DMS offers features such as data encryption, checksums during data transfer, and data integrity checks to ensure the integrity and security of data during migration. Additionally, AWS DMS supports continuous replication, meaning the source database remains available during migration, thus minimizing downtime.Applicability: In this case, since the source database contains 500GB of data, using AWS DMS can efficiently migrate this data while maintaining its integrity and security. Furthermore, the continuous replication feature of AWS DMS helps minimize downtime.By combining AWS SCT for schema and code conversion with AWS DMS for data migration, the company can achieve a fast and efficient migration from an on-premises Oracle database to an Amazon Aurora PostgreSQL DB cluster with minimal downtime.