DBS-C01 Workload-Specific Database Design Practice Test 25 — 15 Questions

Question 1

A social media company stores user posts in a database. Each post has a unique ID, content, and timestamp. The application frequently queries posts by user ID and also needs to support a global feed sorted by timestamp. Which database design is most efficient?

Accepted Answer

Amazon DynamoDB with user_id as partition key and timestamp as sort key, plus a GSI on timestamp. Amazon DynamoDB with a composite primary key (partition key on user_id, sort key on timestamp) allows efficient querying of a user's posts, and a GSI on (timestamp) can support the global feed. Option A (RDS) may become slow with large datasets. Option C (single table scan) is inefficient. Option D (S3) is not suitable for real-time queries.

Answer

Amazon DynamoDB with a single table and scan operation for the global feed

Answer

Amazon S3 with a metadata index in DynamoDB

Answer

Amazon RDS for PostgreSQL with indexes on user_id and timestamp

Question 2

A company is running a critical application on Amazon RDS for Oracle. They need to ensure high availability with automatic failover in case of a database failure. The database size is 500 GB. Which solution should they implement?

Accepted Answer

Enable Multi-AZ deployment. Multi-AZ for RDS Oracle provides automatic failover to a standby in a different Availability Zone. Option B (read replicas) are for read scaling, not automatic failover. Option C (manual snapshot restore) is not automatic. Option D (DynamoDB) is a different database service.

Answer

Create a cross-Region read replica

Answer

Migrate to Amazon DynamoDB Global Tables

Answer

Take regular snapshots and restore in a different Availability Zone

Question 3

A company uses Amazon DynamoDB to store IoT sensor data. Each sensor sends data every second, and the application needs to query the latest reading from each sensor. The sensor ID is the partition key, and the timestamp is the sort key. The table has millions of sensors. Which query pattern is most efficient to get the latest reading for a specific sensor?

Accepted Answer

Use Query with KeyConditionExpression on sensor ID, ScanIndexForward=false, Limit=1. Using a Query with ScanIndexForward set to false and a limit of 1 returns the most recent item for a given partition key efficiently. Option A (GetItem) requires knowing the exact sort key. Option C (Scan) is inefficient. Option D (BatchGetItem) is for multiple items with known keys.

Answer

Use BatchGetItem with the sensor ID and multiple timestamps

Answer

Use Scan with FilterExpression on sensor ID

Answer

Use GetItem with the sensor ID and the current timestamp

Question 4

Which TWO of the following are advantages of using Amazon DynamoDB over Amazon RDS for MySQL for a workload that requires high scalability and low maintenance? (Select TWO.)

Accepted Answer

No need to manage database servers or patches. DynamoDB automatically scales throughput and storage, and it is fully managed with no server administration. Option C is true for RDS, not DynamoDB. Option D is false because DynamoDB supports both consistency models. Option E is true for RDS, not DynamoDB.

Answer

Strong consistency by default

Answer

Support for complex joins and transactions

Answer

Built-in read replicas for scaling reads

Question 5

Which THREE considerations are important when designing a database for a global, multi-Region application using Amazon DynamoDB Global Tables? (Select THREE.)

Accepted Answer

Application tolerance for eventually consistent reads. Global Tables replicate data across regions asynchronously, so conflict resolution (last writer wins) is important. Applications must handle eventually consistent reads. Write capacity must be provisioned in each region. Option D (strong consistency) is not guaranteed across regions. Option E (single write region) defeats the purpose of Global Tables.

Answer

Using a single write region to avoid conflicts

Answer

Strongly consistent reads across regions

Question 6

Which TWO strategies can improve query performance in Amazon Aurora MySQL for a read-heavy workload? (Select TWO.)

Accepted Answer

Enable Aurora Auto Scaling for read replicas. Aurora Replicas offload read traffic, and Auto Scaling adjusts the number of replicas based on load. Option C (Multi-AZ) is for failover, not read scaling. Option D (EBS optimization) is not applicable to Aurora (uses cluster volume). Option E (DynamoDB) is a different service.

Answer

Use Provisioned IOPS EBS volumes for the primary instance

Answer

Enable Multi-AZ to create a standby for read traffic

Answer

Migrate the read-heavy queries to Amazon DynamoDB

Question 7

A company is migrating an on-premises MongoDB database to Amazon DocumentDB. The application uses secondary indexes extensively and requires low-latency reads. Which database design consideration is MOST important for this workload?

Accepted Answer

Convert secondary indexes to the DocumentDB-compatible format. Option B is correct because Amazon DocumentDB does not support the same range of secondary indexes as MongoDB; converting indexes ensures performance. Option A is wrong because DocumentDB uses its own storage, not EBS. Option C is wrong because DynamoDB Accelerator is for DynamoDB, not DocumentDB. Option D is wrong because vertical scaling is often insufficient; proper indexing is key.

Answer

Provision EBS-optimized instances with increased IOPS

Answer

Use a larger instance type to avoid indexing issues

Answer

Enable DynamoDB Accelerator (DAX) for caching

Question 8

A startup is building a social media analytics platform that requires storing time-series data with frequent writes and queries for the last hour. Which AWS database service is BEST suited for this workload?

Accepted Answer

Amazon Timestream. Option C is correct because Timestream is purpose-built for time-series data and supports high-frequency writes and recent data queries. Option A is wrong because RDS is not optimized for time-series. Option B is wrong because DynamoDB can store timestamps but lacks time-series optimizations. Option D is wrong because Neptune is a graph database.

Answer

Amazon RDS with MySQL

Answer

Amazon Neptune

Answer

Amazon DynamoDB

Question 9

A company uses Amazon RDS for MySQL with Multi-AZ and read replicas. The database has a table storing user sessions with 50 million rows. The application team reports that queries using 'SELECT * FROM sessions WHERE user_id = ? ORDER BY login_time DESC LIMIT 10' are slow. The EXPLAIN plan shows a full table scan. Which design change would BEST improve query performance?

Accepted Answer

Create a composite index on (user_id, login_time). Option A is correct because a composite index on (user_id, login_time) allows the database to find rows by user and order by time without scanning. Option B is wrong because increasing instance size does not address the missing index. Option C is wrong because caching may help but does not fix the root cause. Option D is wrong because partitioning by user_id may help, but a composite index is more effective for this specific query.

Answer

Implement an application-level cache using ElastiCache

Answer

Partition the table by user_id

Answer

Upgrade to a larger instance type with more memory

Question 10

A financial services company needs a database to store transaction records with strict ACID compliance and the ability to run complex JOIN queries for reporting. The workload is read-heavy with occasional batch inserts. Which AWS database service should they choose?

Accepted Answer

Amazon RDS for PostgreSQL. Option A is correct because Amazon RDS for PostgreSQL is a relational database that provides ACID compliance and supports complex joins. Option B is wrong because DynamoDB is NoSQL and does not support complex joins. Option C is wrong because Aurora Serverless is good but may not be the best for complex joins; however, it is still relational. Option D is wrong because Timestream is for time-series.

Answer

Amazon DynamoDB

Answer

Amazon Aurora Serverless

Answer

Amazon Timestream

Question 11

A gaming company wants to store player profiles and game state data with low-latency access for millions of concurrent users. The data is accessed via a REST API and requires high scalability with minimal operational overhead. Which database service is MOST suitable?

Accepted Answer

Amazon DynamoDB. Option C is correct because DynamoDB is a fully managed NoSQL database that provides single-digit millisecond latency at any scale, ideal for gaming profiles. Option A is wrong because RDS is relational and may not scale as easily. Option B is wrong because ElastiCache is a cache, not a primary database. Option D is wrong because Neptune is for graph data.

Answer

Amazon RDS for MySQL with read replicas

Answer

Amazon Neptune

Answer

Amazon ElastiCache for Redis

Question 12

A company uses Amazon Aurora MySQL-Compatible Edition for its e-commerce platform. During flash sales, the database experiences high write contention on the 'orders' table, causing slow inserts and deadlocks. The development team wants to reduce contention without changing the application code. Which database design strategy is MOST effective?

Accepted Answer

Enable Aurora Multi-Master to allow multiple write nodes. Option D is correct because using Aurora Auto Scaling with a Multi-Master cluster allows multiple writers to handle writes concurrently, reducing contention. Option A is wrong because read replicas are for read scaling, not write. Option B is wrong because vertical scaling may help but does not address write contention. Option C is wrong because sharding requires application changes.

Answer

Implement manual sharding across multiple Aurora clusters

Answer

Add more read replicas to offload read traffic

Answer

Use a larger instance type with higher IOPS

Question 13

A healthcare application requires storing patient records that include structured data (e.g., name, age) and unstructured data (e.g., medical images). The application needs to query structured data with SQL and serve images via HTTPS. Which combination of AWS services provides the MOST efficient design?

Accepted Answer

Amazon RDS for PostgreSQL for structured data and Amazon S3 for images with Amazon CloudFront. Option B is correct: RDS stores structured data with SQL, S3 stores images, and CloudFront caches images for low-latency access. Option A is wrong because DynamoDB does not support SQL. Option C is wrong because EFS is a file system, not optimized for image serving. Option D is wrong because Redshift is a data warehouse, not suitable for transactional queries.

Answer

Amazon DynamoDB for structured data and Amazon S3 for images with DynamoDB Accelerator (DAX)

Answer

Amazon RDS for MySQL for structured data and Amazon EFS for images

Answer

Amazon Redshift for structured data and Amazon S3 for images

Question 14

A startup is building a real-time chat application that requires storing messages with high write throughput and low-latency reads. The data model is simple: each message has a conversation ID, timestamp, and content. Which database design is MOST appropriate?

Accepted Answer

Amazon DynamoDB with conversation_id as partition key and timestamp as sort key. Option C is correct because DynamoDB is a NoSQL database that can handle high write throughput and low-latency reads with a simple key-value model. Option A is wrong because RDS may struggle with high write throughput. Option B is wrong because Timestream is for time-series, not chat messages. Option D is wrong because Redshift is for analytics.

Answer

Amazon RDS for MySQL with a single table and indexes on conversation_id and timestamp

Answer

Amazon Timestream to store messages as time-series data

Answer

Amazon Redshift with columnar storage and compression

Question 15

A company is running an Oracle database on Amazon RDS. The database has a large table that is frequently accessed by multiple applications. The DBA notices that the table has a high number of index scans but the queries are still slow. Upon investigation, the buffer cache hit ratio is low. Which design change would BEST improve performance?

Accepted Answer

Increase the instance size to provide more memory. Option B is correct because increasing the instance size provides more memory for the buffer cache, improving cache hit ratio. Option A is wrong because read replicas do not help with buffer cache on the primary. Option C is wrong because converting to columnar is for analytical workloads. Option D is wrong because switching to DynamoDB would require application changes.

Answer

Convert the table to columnar storage using Amazon Redshift

Answer

Add a read replica to offload queries

Answer

Migrate the table to Amazon DynamoDB with DAX