DEA-C01 Data Ingestion and Transformation Practice Question

A company needs to ingest data from a relational database into Amazon S3 for analytics. The database is an Amazon RDS MySQL instance. Which AWS service should be used for a one-time historical data load?

⚠ Common exam trap

DEA-C01 often tests the distinction between DMS (database migration/ingestion) and Glue (ETL transformation), catching candidates who pick Glue for a straightforward one-time database-to-S3 load.

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

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AWS Database Migration Service (DMS)

AWS Database Migration Service (DMS) is designed for migrating data from relational databases like Amazon RDS MySQL into targets such as Amazon S3, supporting one-time full loads as well as ongoing replication. For a one-time historical data load, DMS can extract the existing data and land it in S3 efficiently. This makes DMS the correct service for the described scenario.

Answer analysis

Option-by-option breakdown

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

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AWS Database Migration Service (DMS)
Why this is correct
AWS DMS performs bulk migrations and can replicate existing table data from Amazon RDS MySQL into Amazon S3, making it suited to a one-time historical load. It reads source data directly without custom extraction code.
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AWS Glue ETL
Why it's wrong here
AWS Glue ETL is designed for ongoing, scheduled, or event-driven extract-transform-load jobs, not for a one-time bulk transfer from a relational database. The scenario requires a single historical load, which AWS Glue’s job scheduler and transformation engine are unnecessary overhead; the correct service, AWS Database Migration Service (DMS), performs a one-time full load without requiring Spark-based ETL infrastructure. Glue ETL is tempting because it can connect to JDBC sources like MySQL and write to S3, and it would be the correct choice if the requirement involved repeated incremental loads or complex data transformations during ingestion.
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Amazon Athena
Why it's wrong here
Athena queries data already in S3 using SQL; it cannot extract rows from an RDS MySQL instance into S3. It is tempting because Athena is the analytics query layer over S3, and would be correct for ad-hoc querying of the resulting dataset, not for the initial one-time load.
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Amazon Kinesis Data Firehose
Why it's wrong here
Firehose delivers streaming records to destinations; it cannot perform a bulk extract of existing MySQL table rows. It is tempting because Firehose writes to S3, and would be correct for continuous ingestion of real-time events, not a one-time historical load from a relational database.

Quick reference

AWS S3 Storage Class Comparison

Storage Class	Min Duration	Retrieval	Use Case
S3 Standard	None	Immediate	Frequently accessed data
S3 Standard-IA	30 days	Immediate	Infrequent access, rapid retrieval
S3 One Zone-IA	30 days	Immediate	Non-critical infrequent data
S3 Intelligent-Tiering	None	Immediate–hours	Unknown or changing access patterns
S3 Glacier Instant	90 days	Milliseconds	Archive with instant retrieval
S3 Glacier Flexible	90 days	Minutes–hours	Archive, flexible retrieval
S3 Glacier Deep Archive	180 days	Hours	Long-term compliance archive

Go deeper

DEA-C01 Data Ingestion and Transformation Practice Question

Why each option matters

Option-by-option breakdown

AWS S3 Storage Class Comparison

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