SAA-C03 Design High-Performing Architectures Practice Question
A customer-facing application has a relational data model and needs frequent complex queries (joins and aggregations), but it also experiences a significant read-heavy workload. Which design choice best improves read performance while keeping relational features?
⚠ Common exam trap
A common mix-up: candidates assume NoSQL databases like DynamoDB can handle relational queries if they simply 'switch' the database, ignoring that DynamoDB lacks native support for joins and complex aggregations, which are core to the relational data model described in the question.
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
✓
Add read replicas to an RDS or Aurora cluster and keep the primary for writes.
Adding read replicas to an RDS or Aurora cluster offloads read traffic from the primary instance, improving read performance for complex queries (joins and aggregations) while preserving the relational data model. Aurora automatically scales read replicas and uses a shared storage volume, making this highly efficient for read-heavy workloads.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use DynamoDB with a single partition key and avoid indexes to keep writes simple.
Why it's wrong here
DynamoDB with a single partition key can only efficiently fetch items sharing exactly that key; any other query forces a full table scan, and deliberately avoiding secondary indexes makes filtering on other attributes even worse. While DynamoDB supports key-value and document patterns, it does not natively support SQL joins, aggregations, or flexible relational queries, so the application would require a complete data-model redesign and client-side join logic. This option directly conflicts with the stated requirement to preserve the relational data model and query patterns.
- ✓
Add read replicas to an RDS or Aurora cluster and keep the primary for writes.
Why this is correct
Read replicas offload read operations from the primary database instance, improving read throughput and reducing contention with writes. RDS/Aurora preserve relational capabilities like joins and SQL queries. This is a common and practical way to scale performance for read-heavy workloads without completely changing the data model.
- ✗
Store the data in S3 and query it directly from the application without a database.
Why it's wrong here
S3 is an object storage service, not a database; it provides no built-in query engine, indexing, or transaction semantics. Directly querying from the application would require downloading entire objects (e.g., CSV, JSON) and performing joins/filtering in memory, which causes high latency, scales poorly, and is operationally difficult to maintain. S3 Select only handles simple filtering over a single object and cannot do cross-object joins, aggregations, or enforce consistency, making it unacceptable for a low-latency, relational workload.
- ✗
Switch the database to DynamoDB but keep using the same relational SQL queries and joins.
Why it's wrong here
DynamoDB does not support SQL joins in the same way relational databases do. Moving to DynamoDB generally requires a query-pattern redesign with keys and indexes. Keeping the same query approach would not work as intended.
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