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

Question 1

A company is building a real-time leaderboard for a gaming application. The leaderboard must update scores within seconds and support queries for top players and individual ranks. Which database design is most appropriate?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Amazon DynamoDB with a global secondary index on score. Amazon DynamoDB with a global secondary index (GSI) on score is the most appropriate design because it supports real-time updates and low-latency queries for both top players (via query on the GSI with ScanIndexForward=false and Limit) and individual ranks (via efficient key lookups). DynamoDB's fully managed, serverless architecture ensures sub-second response times at any scale, which is critical for a gaming leaderboard that must update scores within seconds.

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Amazon S3 with Range GET requests

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Amazon ElastiCache for Redis with sorted sets

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Amazon RDS for PostgreSQL with ORDER BY and LIMIT

Question 2

A startup is building a mobile application that needs to store user profiles and preferences. The data is schema-less and will grow rapidly. The application requires single-digit millisecond latency for reads and writes. Which AWS database should they choose?

Accepted Answer

Amazon DynamoDB. Amazon DynamoDB is a fully managed NoSQL key-value and document database that delivers single-digit millisecond latency at any scale. It is schema-less, making it ideal for storing user profiles and preferences that have varying attributes, and it automatically scales to handle rapid growth without downtime or performance degradation.

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Amazon Aurora (MySQL compatible)

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Amazon Redshift

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Amazon RDS for SQL Server

Question 3

A company uses Amazon Aurora MySQL for its online transaction processing (OLTP) application. Recently, read traffic has increased significantly, causing performance issues. The company wants to offload read traffic with minimal application changes. Which solution should they implement?

Accepted Answer

Create one or more Aurora Replicas. Aurora Replicas are designed specifically to offload read traffic from the primary Aurora instance with minimal application changes. They connect to the same shared storage volume as the primary, so replication is nearly instantaneous and requires no additional storage overhead. The application can use the Aurora reader endpoint to distribute read queries across up to 15 low-latency replicas.

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Enable Multi-AZ deployment

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Migrate to Amazon DynamoDB

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Add an Amazon ElastiCache cluster in front of Aurora

Question 4

A financial services company needs a database to store transaction records with strong consistency and the ability to run complex analytical queries. The data volume is in the terabytes and is expected to grow. The company also needs point-in-time recovery. Which AWS database solution meets these requirements?

Accepted Answer

Amazon Redshift with automated snapshots. Amazon Redshift is correct because it is a fully managed, petabyte-scale data warehouse designed for complex analytical queries on large datasets, and it supports automated snapshots for point-in-time recovery within a configurable retention period. The service provides strong consistency for committed transactions and can handle terabytes of data with columnar storage and massively parallel processing, making it ideal for the financial services company's requirements.

Answer

Amazon RDS for MySQL with read replicas

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Amazon ElastiCache for Redis with AOF persistence

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Amazon DynamoDB with on-demand backup

Question 5

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. It uses user_id as the partition key and timestamp as the sort key for efficient per-user queries, while the Global Secondary Index (GSI) on timestamp allows the global feed to be sorted by timestamp without a costly scan. This design leverages DynamoDB's key-value and query capabilities to support both access patterns with low latency and minimal read capacity consumption.

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

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Amazon S3 with a metadata index in DynamoDB

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Amazon RDS for PostgreSQL with indexes on user_id and timestamp

Question 6

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 deployment for Amazon RDS for Oracle provides synchronous replication to a standby instance in a different Availability Zone, with automatic failover in the event of a database failure. This ensures high availability without manual intervention, meeting the requirement for automatic failover for a 500 GB Oracle database.

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Create a cross-Region read replica

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Migrate to Amazon DynamoDB Global Tables

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Take regular snapshots and restore in a different Availability Zone

Question 7

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. Query with ScanIndexForward=false and Limit=1 retrieves only the most recent item for a given partition key (sensor ID) by reading items in descending sort key (timestamp) order and stopping after one item. This is the most efficient pattern as it uses the primary key index directly, avoids scanning, and minimizes read capacity consumption.

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Use BatchGetItem with the sensor ID and multiple timestamps

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Use Scan with FilterExpression on sensor ID

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Use GetItem with the sensor ID and the current timestamp

Question 8

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. Amazon DynamoDB is a fully managed NoSQL database service that eliminates the need for server provisioning, patching, or maintenance. Unlike Amazon RDS for MySQL, where you are responsible for managing the underlying DB instance (including OS and database engine patches), DynamoDB abstracts all infrastructure management, allowing you to focus solely on data access patterns.

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Strong consistency by default

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Support for complex joins and transactions

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Built-in read replicas for scaling reads

Question 9

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. Amazon DynamoDB Global Tables use an eventually consistent model for cross-region replication. Applications must tolerate eventual consistency, as updates made in one region are propagated to other regions asynchronously, typically within one second or less. This design trade-off enables high availability and low-latency writes across multiple regions.

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Using a single write region to avoid conflicts

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Strongly consistent reads across regions

Question 10

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. Amazon Aurora Auto Scaling automatically adjusts the number of Aurora Replicas in response to changes in read workload demand, ensuring consistent read performance without manual intervention. This is ideal for read-heavy workloads where traffic patterns fluctuate, as it dynamically adds or removes replicas based on target metrics like CPU utilization or connections.

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Use Provisioned IOPS EBS volumes for the primary instance

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Enable Multi-AZ to create a standby for read traffic

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Migrate the read-heavy queries to Amazon DynamoDB

Question 11

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. Secondary indexes in MongoDB must be converted to the Amazon DocumentDB-compatible format. DocumentDB uses a different storage engine and indexing implementation than MongoDB, so indexes created in MongoDB are not automatically compatible. Converting secondary indexes ensures that the query patterns relying on those indexes continue to perform with low-latency reads after migration.

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Provision EBS-optimized instances with increased IOPS

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Use a larger instance type to avoid indexing issues

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Enable DynamoDB Accelerator (DAX) for caching

Question 12

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. Amazon Timestream is a purpose-built time-series database that efficiently handles high-frequency writes and recent-time queries (e.g., last hour) with automatic data tiering (in-memory store for recent data, magnetic store for historical). Its serverless architecture and built-in time-series functions (e.g., interpolation, smoothing) make it ideal for social media analytics workloads requiring low-latency queries on recent data.

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Amazon RDS with MySQL

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Amazon Neptune

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Amazon DynamoDB

Question 13

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). The query filters on user_id and orders by login_time, which is a classic case for a composite index. A B-Tree index on (user_id, login_time) allows MySQL to locate all rows for the given user_id via the index's leading column and then retrieve the rows in sorted order using the second column, avoiding a full table scan and a filesort operation. This directly addresses the root cause — the lack of an index to support both the WHERE and ORDER BY clauses efficiently.

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Implement an application-level cache using ElastiCache

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Partition the table by user_id

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Upgrade to a larger instance type with more memory

Question 14

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. Amazon RDS for PostgreSQL is the correct choice because it provides full ACID compliance through its support for PostgreSQL's MVCC (Multi-Version Concurrency Control) and WAL (Write-Ahead Logging), ensuring transactional integrity for financial transaction records. It also excels at complex JOIN queries for reporting, leveraging PostgreSQL's advanced query optimizer and support for foreign keys, indexes, and CTEs. The read-heavy workload with occasional batch inserts is well-suited to RDS for PostgreSQL, as it can scale read replicas and handle batch operations efficiently with proper indexing.

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Amazon DynamoDB

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Amazon Aurora Serverless

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Amazon Timestream

Question 15

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. Amazon DynamoDB is the most suitable choice because it is a fully managed NoSQL key-value and document database that delivers single-digit millisecond latency at any scale, making it ideal for storing player profiles and game state data for millions of concurrent users. It supports high throughput with auto-scaling, integrates seamlessly with REST APIs via AWS SDKs, and requires minimal operational overhead due to its serverless nature.

Answer

Amazon RDS for MySQL with read replicas

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Amazon Neptune

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Amazon ElastiCache for Redis