DBS-C01 Workload-Specific Database Design Practice Test 22 — 15 Questions

Question 1

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?

Accepted Answer

Use Amazon DynamoDB with a fan-out on write pattern, storing each user's feed in a separate partition. Option B is correct because DynamoDB with a fan-out on write pattern pre-joins posts into per-user feed tables, enabling fast reads with low latency. Option A (RDS with read replicas) would struggle with the high write volume and join complexity. Option C (ElastiCache as primary store) loses durability. Option D (DynamoDB single table with GSI) would require expensive scans to filter followed users' posts.

Answer

Use Amazon RDS for PostgreSQL with read replicas and materialized views refreshed every minute

Answer

Use Amazon ElastiCache for Redis as a primary data store with sorted sets per user

Answer

Use a single DynamoDB table with a global secondary index on user_id and timestamp

Question 2

An e-commerce platform uses Amazon DynamoDB for a shopping cart table with partition key 'user_id' and sort key 'product_id'. The table experiences throttled write requests during flash sales. The access pattern includes reading the entire cart at checkout. Which design change would improve write performance without changing the read pattern?

Accepted Answer

Enable DynamoDB Adaptive Capacity and ensure the table uses on-demand capacity mode. Option C is correct because DynamoDB adaptive capacity automatically adjusts partitions based on traffic patterns, mitigating hot keys. Option A (increase WCU) doesn't solve hot key issue. Option B (DAX) improves read, not write. Option D (remove sort key) would break the data model.

Answer

Enable DynamoDB Accelerator (DAX) to cache writes

Answer

Increase the provisioned write capacity units (WCU) to a higher value

Answer

Change the table design to use only partition key 'user_id' and remove the sort key

Question 3

A company wants to store and analyze time-series sensor data from millions of IoT devices. The data is append-only and rarely updated. Queries aggregate data over time ranges. Which AWS database service is most cost-effective and performant for this workload?

Accepted Answer

Amazon Timestream. Option A is correct because Timestream is purpose-built for time-series data, offering automatic tiering and optimized aggregation queries. Option B (DynamoDB) can handle time-series but requires careful design and is less cost-effective for large-scale. Option C (RDS) is relational and not optimized for time-series. Option D (Redshift) is for analytical workloads but is heavier and more expensive for IoT sensor data.

Answer

Amazon DynamoDB with time-series design pattern

Answer

Amazon Redshift

Answer

Amazon RDS for MySQL with partitioning by date

Question 4

A financial services company needs a database for trade settlement records. Each trade must be processed exactly once and the database must ensure ACID compliance across multiple rows. The workload is write-intensive with moderate reads. Which AWS database service should they choose?

Accepted Answer

Amazon Aurora PostgreSQL. Option B is correct because Aurora is ACID-compliant, supports complex transactions, and provides high availability. Option A (DynamoDB) is not fully ACID (only single-item transactions are atomic). Option C (Neptune) is a graph database. Option D (ElastiCache) is not durable and not ACID.

Answer

Amazon DynamoDB with DynamoDB transactions

Answer

Amazon ElastiCache for Redis

Answer

Amazon Neptune

Question 5

A gaming company uses Amazon DynamoDB to store player profiles. The table has partition key 'player_id' and sort key 'game_id'. During a new game launch, write traffic to a subset of players (influencers) spikes, causing throttling. The table uses on-demand capacity. Which solution resolves the hot key issue?

Accepted Answer

Add a random suffix to the partition key for the hot players to distribute writes. Option C is correct because adding a suffix to the partition key for hot keys distributes writes across multiple partitions. Option A (increase read capacity) doesn't help writes. Option B (DAX) is for reads. Option D (change to provisioned) doesn't solve hot key; adaptive capacity works in both modes.

Answer

Increase the maximum read capacity units in the on-demand settings

Answer

Switch to provisioned capacity mode and increase write capacity units

Answer

Enable DynamoDB Accelerator (DAX) to cache writes

Question 6

A startup is building a multi-tenant SaaS application where each tenant's data must be isolated. The data model is relational with complex joins. Which database deployment model is most appropriate?

Accepted Answer

Provision a separate Amazon RDS instance for each tenant. Option B is correct because a separate RDS instance per tenant provides strong isolation. Option A (single table with tenant_id) risks noisy neighbors. Option C (DynamoDB single table) is not relational. Option D (Redshift) is for analytics, not OLTP.

Answer

Use a single Amazon DynamoDB table with a tenant_id partition key

Answer

Use a single Amazon Redshift cluster with tenant_id distribution key

Answer

Use a single Amazon RDS database with a tenant_id column on every table

Question 7

A company uses Amazon DynamoDB for a high-traffic leaderboard application that updates scores in real-time. The table has partition key 'game_id' and sort key 'player_id'. Queries retrieve top 10 players by score for each game. Which secondary index design is most efficient?

Accepted Answer

Create a global secondary index (GSI) with partition key 'game_id' and sort key 'score'. Option C is correct because a GSI with game_id as partition key and score as sort key allows efficient top-N queries using ScanIndexForward=false. Option A (GSI with player_id) doesn't sort by score. Option B (LSI) cannot use a different partition key. Option D (no index) would require full table scan.

Answer

Create a global secondary index (GSI) with partition key 'game_id' and sort key 'player_id'

Answer

Create a local secondary index (LSI) with sort key 'score'

Answer

Do not create any index; use the base table with a scan

Question 8

A media company stores video metadata in Amazon DynamoDB. The table has partition key 'video_id' and sort key 'upload_date'. The application frequently queries videos by 'category' and 'status'. The access pattern changes over time. Which design minimizes cost and maximizes query flexibility?

Accepted Answer

Create multiple GSIs with different partition keys to support various query patterns. Option D is correct because DynamoDB supports multiple GSIs per table, allowing different access patterns. Option A (single GSI) is less flexible. Option B (stream to Elasticsearch) adds complexity and cost. Option C (single table design) may not fit all patterns.

Answer

Create a single GSI with partition key 'category' and sort key 'status'

Answer

Use DynamoDB Streams to replicate data to Amazon Elasticsearch Service

Answer

Redesign to a single DynamoDB table that aggregates all attributes into the partition key

Question 9

A company needs to store and query a graph of relationships between users for a recommendation engine. The queries involve traversing multiple edges. Which AWS database service is most suitable?

Accepted Answer

Amazon Neptune. Option B is correct because Neptune is a fully managed graph database designed for highly connected data. Option A (RDS) requires complex joins. Option C (DynamoDB) can model graphs but requires multiple queries. Option D (DocumentDB) is for documents.

Answer

Amazon DynamoDB with adjacency list design

Answer

Amazon DocumentDB (with MongoDB compatibility)

Answer

Amazon RDS for PostgreSQL with recursive CTEs

Question 10

A company is designing a database for a global e-commerce platform with strong consistency requirements. The database must support cross-region disaster recovery with RPO < 1 second and RTO < 1 minute. Which TWO AWS database services meet these requirements?

Accepted Answer

Amazon Aurora Global Database. Option A (Aurora Global Database) provides cross-region replication with typical RPO of 1 second and RTO of 1 minute. Option D (DynamoDB Global Tables) offers multi-region replication with eventual consistency but also supports strongly consistent reads in each region; however, for global tables, RPO is typically < 1 second and failover can be automated within seconds. Option B (RDS Multi-AZ) is single-region. Option C (Redshift) is not designed for OLTP. Option E (ElastiCache) is in-memory and not durable.

Answer

Amazon RDS Multi-AZ

Answer

Amazon Redshift with cross-region snapshot copy

Answer

Amazon ElastiCache for Redis with Global Datastore

Question 11

A company runs a MySQL-compatible database on Amazon RDS for a mission-critical application. The database experiences high write latency due to frequent index updates. The team wants to redesign the database to reduce write amplification and improve insert performance. Which TWO design changes could help?

Accepted Answer

Use batch INSERT statements instead of single-row inserts. Option A (removing unused indexes) directly reduces write amplification. Option C (batch inserts) reduces per-row overhead. Option B (increasing instance size) may not address root cause. Option D (changing to InnoDB) is already MySQL's default engine; switching to MyISAM is not recommended. Option E (normalizing) might increase joins but not necessarily reduce write amplification.

Answer

Switch the storage engine from InnoDB to MyISAM

Answer

Upgrade to a larger RDS instance class

Answer

Normalize the database schema to reduce data redundancy

Question 12

A company is migrating an on-premises MongoDB workload to Amazon DocumentDB. The workload includes aggregation pipelines with $lookup and $group operations. The team wants to ensure minimal performance impact. Which THREE steps should they take?

Accepted Answer

Create appropriate indexes on fields used in $lookup and $group. Option A (enable TLS) is security, not performance. Option B (create indexes) is critical for $lookup and $group. Option C (increase instance size) helps compute-intensive operations. Option D (disable journaling) is not recommended for durability. Option E (use parallel scans) can speed up aggregations.

Answer

Disable journaling to reduce I/O overhead

Answer

Enable TLS for all connections

Question 13

Refer to the exhibit. An application uses Cognito identity pools to authenticate users and dynamodb:LeadingKeys condition to restrict access to items where the partition key matches the user's sub. Some users report that they can see items belonging to other users. What is the most likely cause?

Accepted Answer

The ForAllValues:StringEquals should be ForAnyValue:StringEquals. Option B is correct because ForAllValues:StringEquals allows the action if the condition value matches at least one of the request values, but if the request has multiple leading keys (e.g., batch operations), it may pass incorrectly. ForAllValues checks that every key in the request matches the condition; if no keys are present, it also passes. The correct condition should be ForAnyValue:StringEquals to ensure at least one key matches. Option A is wrong because the condition is set. Option C is wrong unless the condition is missing. Option D is wrong because the audience is not relevant to item-level access.

Answer

The IAM policy does not include a condition for the table

Answer

The Cognito identity pool is not configured correctly

Answer

The table ARN is incorrect

Question 14

Refer to the exhibit. A CloudFormation stack was deployed to create an RDS instance. The application team reports they cannot connect to the database using the endpoint provided. The security group allows inbound traffic on port 3306 from the application's security group. What is the most likely cause?

Accepted Answer

The database password is not provided in the stack outputs; the team may be using the wrong password. Option D is correct because the output shows the DBName and MasterUsername, but not the password. The password is usually stored in Secrets Manager or parameter store and not output. Option A: the endpoint appears correct. Option B: port 3306 is MySQL default, and the security group is allowed. Option C: Multi-AZ does not affect connectivity.

Answer

The RDS instance is in a Multi-AZ deployment and the endpoint is for the standby

Answer

The security group inbound rule is missing the port 3306

Answer

The RDS endpoint is incorrect; it should include the port number

Question 15

Refer to the exhibit. The exhibit shows CloudWatch metrics from an Amazon RDS for PostgreSQL instance. The application is experiencing slow query performance. Which is the most likely cause?

Accepted Answer

High storage latency due to provisioned IOPS being fully utilized or EBS volume contention. Option A is correct because ReadLatency of 2.5 ms is high for a database with 5000 provisioned IOPS; typically sub-millisecond is expected. WriteLatency of 5 ms is also high. Memory usage is 450 MB out of 16 GB, so memory is fine. Connections (100) are moderate. IOPS (5000 read, 2000 write) are within limits but latency is high, indicating potential throttling or contention. Option B: connections are not high. Option C: memory is not pressured. Option D: CPU is not mentioned; high latency is often storage-related.

Answer

High CPU utilization due to complex queries

Answer

Too many database connections causing context switching

Answer

Insufficient memory causing disk swaps