- A
Migrate to Amazon Aurora with parallel query
Why wrong: Aurora is optimized for OLTP, not heavy analytical queries.
- B
Add an Amazon ElastiCache cluster to cache query results
Why wrong: Caching does not help for ad-hoc complex queries.
- C
Enable DynamoDB Accelerator (DAX) on the RDS instance
Why wrong: DAX is only for DynamoDB, not RDS.
- D
Use Amazon Redshift for the analytical workload
Redshift is a columnar data warehouse ideal for complex analytics.
Quick Answer
The answer is to use Amazon Redshift for the analytical workload. Redshift is a columnar data warehouse specifically designed for complex joins and aggregations on massive datasets, processing queries in seconds rather than hours by scanning only relevant columns and using massively parallel processing. On the AWS Certified Database Specialty DBS-C01 exam, this scenario tests your ability to distinguish between transactional and analytical storage engines—a common trap is assuming a larger RDS instance or moving to Aurora will fix analytical slowness, but both remain row-based and optimized for OLTP, not OLAP. Remember the key distinction: row-based for transactions, columnar for analytics. For a memory tip, think “Redshift for reporting, RDS for recording.”
DBS-C01 Workload-Specific Database Design Practice Question
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.
A company runs a MySQL-compatible database on Amazon RDS with a 3 TB dataset. They need to run complex analytical queries that involve joins and aggregations on millions of rows. The current RDS instance is a db.r5.8xlarge with 32 vCPUs and 256 GB RAM, but complex queries take over an hour. Which design change would most improve query performance for this 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
Use Amazon Redshift for the analytical workload
Using Amazon Redshift, a columnar data warehouse, would dramatically improve analytical query performance because it is optimized for complex joins and aggregations. Option A (Aurora) is wrong because it is still row-based and not optimized for analytical workloads. Option B (ElastiCache) is wrong because it is an in-memory cache not designed for complex analytical queries. Option D (DynamoDB Accelerator) is wrong because it is a cache for DynamoDB, not for relational databases.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Migrate to Amazon Aurora with parallel query
Why it's wrong here
Aurora is optimized for OLTP, not heavy analytical queries.
- ✗
Add an Amazon ElastiCache cluster to cache query results
Why it's wrong here
Caching does not help for ad-hoc complex queries.
- ✗
Enable DynamoDB Accelerator (DAX) on the RDS instance
Why it's wrong here
DAX is only for DynamoDB, not RDS.
- ✓
Use Amazon Redshift for the analytical workload
Why this is correct
Redshift is a columnar data warehouse ideal for complex analytics.
Related concept
Static NAT maps one inside address to one outside address.
Common exam traps
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
- Static NAT maps one inside address to one outside address.
- PAT allows many inside hosts to share one public address using ports.
- Inside local and inside global describe the private and translated addresses.
- NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
- Identify inside and outside interfaces first.
- Check whether the scenario needs static NAT, dynamic NAT or PAT.
- Do not confuse NAT matching ACLs with normal packet-filtering intent.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DBS-C01 NAT questions on configuration and troubleshooting.
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Workload-Specific Database Design — study guide chapter
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Workload-Specific Database Design practice questions
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FAQ
Questions learners often ask
What does this DBS-C01 question test?
Workload-Specific Database Design — This question tests Workload-Specific Database Design — Static NAT maps one inside address to one outside address..
What is the correct answer to this question?
The correct answer is: Use Amazon Redshift for the analytical workload — Using Amazon Redshift, a columnar data warehouse, would dramatically improve analytical query performance because it is optimized for complex joins and aggregations. Option A (Aurora) is wrong because it is still row-based and not optimized for analytical workloads. Option B (ElastiCache) is wrong because it is an in-memory cache not designed for complex analytical queries. Option D (DynamoDB Accelerator) is wrong because it is a cache for DynamoDB, not for relational databases.
What should I do if I get this DBS-C01 question wrong?
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DBS-C01 NAT questions on configuration and troubleshooting.
What is the key concept behind this question?
Static NAT maps one inside address to one outside address.
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Last reviewed: Jun 20, 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.
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