Quick Answer
The answer is a caching layer, such as Amazon ElastiCache for Redis or Memcached, along with connection pooling and write optimization strategies. This combination directly addresses low-latency database design for web application demands by reducing disk I/O and offloading the primary database, ensuring frequently accessed data is served from in-memory stores for both reads and writes. On the AWS Certified Database Specialty DBS-C01 exam, this concept tests your understanding of how to decouple read-heavy workloads from the database engine, often appearing in scenario-based questions where a high-traffic app suffers from slow response times. A common trap is to focus solely on scaling the database instance vertically, ignoring the architectural pattern of caching. Remember the memory tip: “Cache first, pool connections, write behind” — this sequence ensures you prioritize in-memory reads, manage concurrent connections efficiently, and defer writes to avoid bottlenecks.
This DBS-C01 practice question tests your understanding of workload-specific database design. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Which THREE factors should be considered when designing a database for a high-traffic web application that requires low-latency reads and writes?
Caching layer
Caching reduces database load and latency.
Partitioning strategy
Partitioning helps distribute load and improve performance.
Strict normalization
Why wrong: Normalization increases joins, potentially increasing latency.
Connection pooling
Connection pooling reduces overhead and improves response times.
Denormalization of data
Why wrong: Denormalization can improve read performance but may complicate writes.
Answer choices
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.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
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.
Related concept
Read the scenario before looking for a memorised answer.
Partitioning strategy
Why this is correct
Partitioning helps distribute load and improve performance.
Related concept
Read the scenario before looking for a memorised answer.
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.
Related concept
Read the scenario before looking for a memorised answer.
Denormalization of data
Why it's wrong here
Denormalization can improve read performance but may complicate writes.
Common exam traps
The trap here is that candidates may 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.
Detailed technical explanation
Partitioning (e.g., horizontal sharding or range-based partitioning) distributes data across multiple nodes, enabling parallel reads and writes to reduce contention. Connection pooling (e.g., using RDS Proxy or PgBouncer) reuses database connections to avoid the overhead of frequent TCP handshakes and authentication, which is critical under high concurrency. Both directly address latency by reducing per-request overhead.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
What to study next
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Workload-Specific Database Design — study guide chapter
Learn the concepts, then practise the questions
Workload-Specific Database Design practice questions
Targeted practice on this topic area only
All DBS-C01 questions
1,730 questions across all exam domains
AWS Certified Database Specialty DBS-C01 study guide
Full concept coverage aligned to exam objectives
DBS-C01 practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Practise DBS-C01 questions linked to Workload-Specific Database Design.
Practise DBS-C01 questions linked to Deployment and Migration.
Practise DBS-C01 questions linked to Management and Operations.
Practise DBS-C01 questions linked to Monitoring and Troubleshooting.
Practise DBS-C01 questions linked to Database Security.
Practise DBS-C01 questions linked to DBS-C01 fundamentals.
Practise DBS-C01 questions linked to DBS-C01 scenario.
Practise DBS-C01 questions linked to DBS-C01 troubleshooting.
Practice this exam
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Workload-Specific Database Design — This question tests Workload-Specific Database Design — Read the scenario before looking for a memorised answer..
The correct answer is: 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.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jun 24, 2026
This DBS-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DBS-C01 exam.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.