DBS-C01 Workload-Specific Database Design Practice Question
A company needs to store and query JSON documents that have varying attributes. The workload is read-heavy, and the team wants to use SQL-like queries. Which service is most appropriate?
⚠ Common exam trap
Test-takers frequently choose DynamoDB with PartiQL because it supports SQL-like queries and JSON, but they overlook that DocumentDB is specifically designed for document workloads with flexible schemas and richer query capabilities, while DynamoDB is optimized for key-value access patterns and requires careful design for varying attributes.
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 (with MongoDB compatibility) is the most appropriate service because it is purpose-built for storing and querying JSON documents with varying attributes, and it supports SQL-like queries via MongoDB's query language, which is familiar to developers. As a read-heavy workload, DocumentDB's architecture with distributed storage and read replicas provides high throughput and low latency for such patterns. The flexible schema of DocumentDB naturally handles documents with differing attributes without requiring schema migrations.
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 Neptune
Why it's wrong here
Neptune is a graph database, not suitable for document storage.
- ✓
Amazon DocumentDB (with MongoDB compatibility)
Why this is correct
DocumentDB is a document database that natively stores JSON and supports MongoDB queries.
- ✗
Amazon DynamoDB with PartiQL
Why it's wrong here
PartiQL supports SQL-like queries but DynamoDB is not optimized for document storage.
- ✗
Amazon RDS for MySQL with JSON data type
Why it's wrong here
Relational database with JSON type, but not as flexible as a document database.
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