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Workload-Specific Database DesigneasyMultiple ChoiceObjective-mapped

DBS-C01 Workload-Specific Database Design Practice Question

A company is migrating an on-premises MongoDB database to AWS. The application uses MongoDB's aggregation pipeline for real-time analytics. Which AWS database service is most compatible and provides the least application changes?

⚠ Common exam trap

Many exam-takers assume DynamoDB's flexibility or Aurora's JSON support can easily replace MongoDB's aggregation pipeline, overlooking the fundamental differences in query language and data model that necessitate significant application rewrites.

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

Amazon DocumentDB (with MongoDB compatibility).

Amazon DocumentDB is designed to be MongoDB-compatible, supporting the MongoDB aggregation pipeline with minimal changes. This allows the company to migrate the existing MongoDB database and continue using the same aggregation pipeline for real-time analytics without rewriting application code, making it the most compatible option.

Answer analysis

Option-by-option breakdown

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

  • Amazon ElastiCache for Redis with RedisJSON module.

    Why it's wrong here

    Not a primary database; not MongoDB compatible.

  • Amazon DocumentDB (with MongoDB compatibility).

    Why this is correct

    DocumentDB is MongoDB-compatible and supports aggregation pipeline.

  • Amazon DynamoDB with DynamoDB Streams and Lambda for aggregation.

    Why it's wrong here

    Requires significant application changes; not MongoDB API compatible.

  • Amazon Aurora with JSON data type.

    Why it's wrong here

    Relational database, not compatible with MongoDB aggregation pipeline.

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