- A
Use Amazon RDS for PostgreSQL with read replicas and materialized views refreshed every minute
Why wrong: Materialized views would not provide real-time updates and read replicas add replication lag.
- B
Use Amazon ElastiCache for Redis as a primary data store with sorted sets per user
Why wrong: Redis is not designed for durable primary storage; data loss risk is high.
- C
Use a single DynamoDB table with a global secondary index on user_id and timestamp
Why wrong: Without fan-out, querying posts from 5,000 followed users would require multiple queries and client-side merging, exceeding latency goals.
- D
Use Amazon DynamoDB with a fan-out on write pattern, storing each user's feed in a separate partition
Fan-out on write ensures feeds are pre-computed for fast reads, meeting latency and throughput requirements.
DynamoDB Fan-Out on Write Pattern — Social Media Feed Design
This DBS-C01 practice question tests your understanding of workload-specific database design. Examine the command output carefully: the correct answer depends on what the output actually shows, not on general recall alone. 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 social media startup is designing a database for user activity feeds. Each user follows up to 5,000 other users. The feed must show the latest 100 posts from followed users with latency under 200ms. Reads are 10x writes. Which database design best meets these requirements?
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 DynamoDB with a fan-out on write pattern, storing each user's feed in a separate partition
Option D is correct because the fan-out on write pattern with DynamoDB ensures each user's feed is pre-computed and stored in a separate partition, allowing reads to fetch the latest 100 posts with sub-200ms latency by querying a single item collection. This pattern optimizes for the 10:1 read-to-write ratio by shifting work to writes, which are less frequent, and avoids expensive joins or scans at read time.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 Amazon RDS for PostgreSQL with read replicas and materialized views refreshed every minute
Why it's wrong here
Materialized views would not provide real-time updates and read replicas add replication lag.
- ✗
Use Amazon ElastiCache for Redis as a primary data store with sorted sets per user
Why it's wrong here
Redis is not designed for durable primary storage; data loss risk is high.
- ✗
Use a single DynamoDB table with a global secondary index on user_id and timestamp
Why it's wrong here
Without fan-out, querying posts from 5,000 followed users would require multiple queries and client-side merging, exceeding latency goals.
- ✓
Use Amazon DynamoDB with a fan-out on write pattern, storing each user's feed in a separate partition
Why this is correct
Fan-out on write ensures feeds are pre-computed for fast reads, meeting latency and throughput requirements.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often choose Option C (GSI on user_id and timestamp) thinking it enables efficient querying, but they overlook the need to query across multiple followed users and merge results, which DynamoDB cannot do without application-level sorting and pagination, violating the 200ms latency SLA.
Detailed technical explanation
How to think about this question
The fan-out on write pattern leverages DynamoDB's ability to write to multiple item collections in a single transaction using the TransactWriteItems API, ensuring atomic updates to each follower's feed partition. This pattern is analogous to Apache Kafka's log compaction but optimized for DynamoDB's key-value model, where each user's feed partition uses a sort key of timestamp to enable efficient retrieval of the latest 100 posts via a Query with Limit and ScanIndexForward=false. In practice, this design requires careful management of write capacity units (WCUs) to handle spikes from celebrity users with millions of followers, often combined with a buffer like Amazon SQS to throttle writes.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
What to study next
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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 — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use Amazon DynamoDB with a fan-out on write pattern, storing each user's feed in a separate partition — Option D is correct because the fan-out on write pattern with DynamoDB ensures each user's feed is pre-computed and stored in a separate partition, allowing reads to fetch the latest 100 posts with sub-200ms latency by querying a single item collection. This pattern optimizes for the 10:1 read-to-write ratio by shifting work to writes, which are less frequent, and avoids expensive joins or scans at read time.
What should I do if I get this DBS-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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