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Data Store ManagementmediumMultiple ChoiceObjective-mapped

DEA-C01 Data Store Management Practice Question

A company is migrating its on-premises PostgreSQL database to Amazon RDS for PostgreSQL. The database is 5 TB in size and supports a critical application that requires less than 30 minutes of downtime. The company has a 1 Gbps network connection to AWS. The data engineering team plans to use AWS Database Migration Service (DMS) with change data capture (CDC) to keep the target in sync. During the full load phase, DMS is taking longer than expected, and the team is concerned about meeting the downtime window. Which action should the team take to speed up the full load?

⚠ Common exam trap

Test-takers frequently assume increasing target instance size (Option A) will speed up the full load, but they overlook that DMS's single-task architecture is the primary bottleneck, not the target's write capacity.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Create multiple DMS tasks to load different tables in parallel.

Creating multiple DMS tasks to load different tables in parallel (Option D) is the correct action because DMS performs full load sequentially within a single task. By splitting tables across multiple tasks, the team can parallelize the data transfer, utilizing the 1 Gbps network more efficiently and reducing the overall full load time to meet the 30-minute downtime window.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Increase the compute capacity of the target RDS instance.

    Why it's wrong here

    May not improve DMS throughput significantly.

  • Enable DMS validation to ensure data integrity.

    Why it's wrong here

    Validation adds overhead and slows migration.

  • Use AWS Snowball Edge to transfer the data offline.

    Why it's wrong here

    Offline transfer increases downtime.

  • Create multiple DMS tasks to load different tables in parallel.

    Why this is correct

    Parallel tasks increase throughput.

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