Key points

• DMS moves database data in full-load or ongoing-change modes and provides current schema-conversion workflows.
• Schema assessment or conversion and the actual data-migration operation are separate steps.

Best-known use cases

• Migrate databases while minimizing source downtime.
• Capture ongoing database changes for analytics pipelines or replicas.
• Convert supported source schemas when moving between database engines.

What candidates often confuse it with

• DMS is database-focused migration and change capture; DataSync moves file data and Application Migration Service rehosts servers.

Key takeaway

Choose DMS for database migration or ongoing change capture, with schema conversion handled as its own boundary.

Relevant exam tasks

• D1.1 — Task 1.1: Perform data ingestion
• 1.1.1 — Read data from streaming sources (for example, Amazon Kinesis, Amazon Managed Streaming for Apache Kafka [Amazon MSK], Amazon DynamoDB Streams, AWS DMS, AWS Glue, Amazon Redshift).
• 1.1.2 — Read data from batch sources (for example, Amazon S3, AWS Glue, Amazon EMR, AWS DMS, Amazon Redshift, AWS Lambda, Amazon AppFlow).
• D2.4 — Task 2.4: Design data models and schema evolution
• 2.4.3 — Perform schema conversion (for example, by using AWS SCT and AWS DMS Schema Conversion).

Learn more

• DEA-C01 in-scope services
• DEA-C01 Domain 1: Data Ingestion and Transformation
• DEA-C01 Domain 2: Data Store Management