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Workload-Specific Database DesigneasyMultiple ChoiceObjective-mapped

DBS-C01 Workload-Specific Database Design Practice Question

A company is running a MySQL database on Amazon RDS and needs to store JSON documents that are frequently queried by fields within the JSON. The company wants to reduce development complexity and improve query performance. Which RDS MySQL feature should the database specialist recommend?

⚠ Common exam trap

Watch out — candidates often assume DynamoDB (Option A) is the only way to handle JSON efficiently, overlooking MySQL 8.0's native JSON support which avoids cross-service complexity while providing comparable query capabilities.

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

Use the JSON data type in MySQL 8.0 and utilize JSON path expressions in queries

MySQL 8.0's native JSON data type stores JSON documents in an optimized binary format, enabling efficient indexing and querying via JSON path expressions (e.g., `JSON_EXTRACT`, `->`, `->>`). This reduces development complexity by allowing direct SQL access to JSON fields without application-level parsing, and improves query performance through generated columns and virtual indexes.

Answer analysis

Option-by-option breakdown

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

  • Migrate the JSON data to Amazon DynamoDB and use DynamoDB's document model

    Why it's wrong here

    Migrating to DynamoDB would require application changes and may not be necessary if the data can be handled within RDS.

  • Use the JSON data type in MySQL 8.0 and utilize JSON path expressions in queries

    Why this is correct

    MySQL's JSON data type allows efficient storage and querying using JSON path expressions and indexes.

  • Store JSON documents in a VARCHAR(MAX) column and use LIKE operations for queries

    Why it's wrong here

    LIKE operations on VARCHAR columns are inefficient and do not support JSON path queries.

  • Store JSON documents as BLOBs and parse them in application code

    Why it's wrong here

    This approach puts parsing burden on the application and prevents database-level optimization.

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Last reviewed: Jun 11, 2026

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