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DEA-C01 · Question #220

A company is using Amazon S3 to build a data lake. The company needs to replicate records from multiple source databases into Apache Parquet format. Most of the source databases are hosted on Amazon…

The correct answer is C. Use AWS Database Migration Service (AWS DMS) to replicate existing data and future changes. Amazon DMS can perform a one-time full load of each source (including the on-prem SQL Server) and then capture ongoing changes (CDC), delivering them directly to S3 in Apache Parquet format. Using a single DMS replication task per source minimizes infrastructure, operational…

Data Ingestion and Transformation

Question

A company is using Amazon S3 to build a data lake. The company needs to replicate records from multiple source databases into Apache Parquet format. Most of the source databases are hosted on Amazon RDS. However, one source database is an on-premises Microsoft SQL Server Enterprise instance. The company needs to implement a solution to replicate existing data from all source databases and all future changes to the target S3 data lake. Which solution will meet these requirements MOST cost-effectively?

Options

  • AUse one AWS Glue job to replicate existing data. Use a second AWS Glue job to replicate future
  • BUse AWS Database Migration Service (AWS DMS) to replicate existing data. Use AWS Glue jobs
  • CUse AWS Database Migration Service (AWS DMS) to replicate existing data and future changes.
  • DUse AWS Glue jobs to replicate existing data. Use Amazon Kinesis Data Streams to replicate

How the community answered

(39 responses)
  • A
    3% (1)
  • B
    13% (5)
  • C
    77% (30)
  • D
    8% (3)

Explanation

Amazon DMS can perform a one-time full load of each source (including the on-prem SQL Server) and then capture ongoing changes (CDC), delivering them directly to S3 in Apache Parquet format. Using a single DMS replication task per source minimizes infrastructure, operational overhead, and cost.

Topics

#AWS DMS#Change Data Capture#Data Ingestion#Hybrid Data Replication

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