DBS-C01 Workload-Specific Database Design Practice Question
Which THREE factors should be considered when designing a database for a high-traffic web application that requires low-latency reads and writes?
⚠ Common exam trap
Test-takers frequently confuse denormalization as a mandatory design choice for low-latency reads, when in fact it is a trade-off that can complicate writes and is not a core factor for both low-latency reads and writes in a high-traffic web application.
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
✓
Caching layer
A caching layer (e.g., Amazon ElastiCache for Redis or Memcached) reduces read latency by serving frequently accessed data from in-memory stores, offloading the primary database. For high-traffic web applications, this minimizes disk I/O and improves response times for both reads and writes when combined with write-through or write-behind strategies.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Caching layer
Why this is correct
Caching reduces database load and latency.
- ✓
Partitioning strategy
Why this is correct
Partitioning helps distribute load and improve performance.
- ✗
Strict normalization
Why it's wrong here
Normalization increases joins, potentially increasing latency.
- ✓
Connection pooling
Why this is correct
Connection pooling reduces overhead and improves response times.
- ✗
Denormalization of data
Why it's wrong here
Denormalization can improve read performance but may complicate writes.
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