DBS-C01 Workload-Specific Database Design Practice Question
A startup is building a social media analytics application that ingests high-velocity streaming data from multiple sources. The data consists of JSON objects with varying schemas. The application needs to store this data for real-time querying and later batch processing. Which AWS database solution is most cost-effective and scalable for this workload?
⚠ Common exam trap
Candidates often choose Amazon Redshift (Option D) because they associate streaming data with data warehousing, but Redshift is optimized for batch analytics on structured data, not for real-time ingestion and querying of schema-less JSON, making DynamoDB the correct choice for this specific workload.
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 DynamoDB with on-demand capacity.
Amazon DynamoDB with on-demand capacity is the most cost-effective and scalable solution for this workload because it is a fully managed NoSQL database that can handle high-velocity streaming data with varying JSON schemas without requiring schema definition or provisioning. Its on-demand capacity mode automatically scales to accommodate unpredictable traffic spikes, making it ideal for real-time querying and batch processing via features like DynamoDB Streams and integration with AWS Glue or EMR.
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 persistence enabled.
Why it's wrong here
ElastiCache is a cache, not a primary data store for durability.
- ✓
Amazon DynamoDB with on-demand capacity.
Why this is correct
DynamoDB handles high-velocity writes and varying schemas, and is cost-effective for unpredictable workloads.
- ✗
Amazon RDS for MySQL with multiple read replicas.
Why it's wrong here
Relational database requires fixed schema and is not optimal for varying schemas.
- ✗
Amazon Redshift with auto-ingest from Kinesis.
Why it's wrong here
Redshift is for analytics, not real-time ingestion with varying schemas.
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