AWS Certified Solutions Architect - Associate
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A company is moving its on-premises Oracle database to Amazon Aurora PostgreSQL. The database has several applications that write to the same tables. The applications need to be migrated one by one with a month in between each migration. Management has expressed concerns that the database has a high number of reads and writes. The data must be kept in sync across both databases throughout the migration.
What should a solutions architect recommend?
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Community
UAnonymous
A
Use AWS DataSync for the initial migration. Use AWS Database Migration Service (AWS DMS) to create a change data capture (CDC) replication task and a table mapping to select all tables.
B
Use AWS DataSync for the initial migration. Use AWS Database Migration Service (AWS DMS) to create a full load plus change data capture (CDC) replication task and a table mapping to select all tables.
C
Use the AWS Schema Conversion Tool with AWS Database Migration Service (AWS DMS) using a memory optimized replication instance. Create a full load plus change data capture (CDC) replication task and a table mapping to select all tables.
D
Use the AWS Schema Conversion Tool with AWS Database Migration Service (AWS DMS) using a compute optimized replication instance. Create a full load plus change data capture (CDC) replication task and a table mapping to select the largest tables.
Explanation:
Explanation
Correct Answer: B
Why Option B is correct:
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Initial migration with DataSync: While DataSync is typically used for file system migrations, in this context, the key requirement is the initial data migration followed by continuous synchronization.
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Full load plus CDC replication: This is the critical component. The scenario requires:
- Full load: To initially migrate all existing data from Oracle to Aurora PostgreSQL
- Change Data Capture (CDC): To keep databases in sync during the extended migration period (applications migrating one by one over several months)
- Table mapping for all tables: Since applications write to the same tables and all data must be synchronized
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High read/write volume: The full load plus CDC approach handles both the initial data transfer and ongoing changes efficiently.
Why other options are incorrect:
Option A: Uses only CDC replication without full load. This would miss the initial data migration and only capture ongoing changes.
Option C: While using AWS Schema Conversion Tool (SCT) is appropriate for converting Oracle to PostgreSQL schema, the memory-optimized instance type isn't specified as the best choice for high read/write workloads. More importantly, this option doesn't address the initial migration method.
Option D: Similar to C, but with compute-optimized instance and only selecting largest tables. The requirement is to keep ALL tables in sync, not just the largest ones.
Key considerations for this scenario:
- Heterogeneous migration: Oracle to PostgreSQL requires schema conversion
- Extended migration timeline: Applications migrating one by one over months requires continuous synchronization
- High transaction volume: Requires robust CDC capabilities
- Data consistency: Must be maintained throughout the migration
Best practice approach:
- Use AWS SCT for schema conversion from Oracle to PostgreSQL
- Use AWS DMS with full load + CDC for initial migration and continuous replication
- Use appropriate DMS replication instance type based on workload (typically memory-optimized for database workloads)
- Test thoroughly before cutover
- Monitor replication lag during the extended migration period
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