DBS-C01 Workload-Specific Database Design Practice Test 21 — 15 Questions

Question 1

A company needs to store and analyze JSON documents that contain nested fields. The data is used for real-time dashboards and ad-hoc queries. The team wants a fully managed solution that supports both key-value lookups and SQL-like queries. Which AWS service should they use?

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

Accepted Answer

Amazon DynamoDB. Amazon DynamoDB is correct because it is a fully managed NoSQL key-value and document database that supports single-digit millisecond latency for key-value lookups, and its PartiQL-compatible query language enables SQL-like queries on JSON documents with nested fields. DynamoDB also integrates with AWS services like Lambda and Kinesis for real-time dashboards, and its adaptive capacity handles ad-hoc query patterns without manual scaling.

Answer

Amazon Redshift

Answer

Amazon RDS for PostgreSQL with JSONB

Answer

Amazon DocumentDB

Question 2

A company uses Amazon DynamoDB for a session management store. The application writes and reads session data frequently. The team notices that write requests occasionally fail with ProvisionedThroughputExceededException. They want a cost-effective solution to handle these bursts. What should they do?

Accepted Answer

Enable DynamoDB Auto Scaling for the table. DynamoDB Auto Scaling dynamically adjusts the provisioned write capacity based on actual traffic patterns, handling bursts cost-effectively by scaling up during spikes and down during lulls. This avoids the fixed-cost overhead of a higher provisioned value (Option A) and directly addresses the ProvisionedThroughputExceededException by ensuring sufficient capacity during bursts.

Answer

Increase the provisioned write capacity to a higher fixed value

Answer

Use DynamoDB Accelerator (DAX) to cache writes

Answer

Implement an Amazon SQS queue to buffer writes

Question 3

A company has a MySQL database that stores user profile data. The database is 1 TB and growing. The team wants to archive inactive user profiles that haven't been accessed in over 1 year. The archived data must be queryable but at a slower performance tier. Which approach is most cost-effective?

Accepted Answer

Export inactive profiles to Amazon S3 and use S3 Intelligent-Tiering for storage. The most cost-effective because Amazon S3 with Intelligent-Tiering automatically moves data between access tiers (frequent, infrequent, and archive) based on usage, minimizing storage costs for rarely accessed data. Inactive profiles exported to S3 remain queryable via S3 Select or Athena, meeting the requirement for slower query performance at a fraction of the cost of maintaining a relational database instance.

Answer

Create an RDS read replica and delete inactive records from the primary

Answer

Move inactive profiles to Amazon Aurora Serverless and stop the cluster when not in use

Answer

Use Amazon DynamoDB with TTL to expire inactive profiles

Question 4

A company is designing a database for a global application that requires active-active replication across two AWS Regions. The database must support multi-master writes with conflict resolution. Which AWS database service should they use?

Accepted Answer

Amazon DynamoDB Global Tables. Amazon DynamoDB Global Tables provides fully managed, multi-Region, multi-master replication, enabling active-active writes across two AWS Regions with built-in conflict resolution using last-writer-wins (based on timestamp). This directly meets the requirement for multi-master writes and conflict resolution without custom code.

Answer

Amazon Aurora Global Database

Answer

Amazon Redshift

Answer

Amazon RDS for MySQL with Multi-AZ

Question 5

A company runs a critical Oracle database on Amazon RDS. The database has a large table that is frequently accessed by multiple applications. The team wants to implement caching to reduce the load on the database. The cached data must be strongly consistent with the database. Which caching strategy should they use?

Accepted Answer

Write-through cache using Amazon ElastiCache. The write-through cache strategy ensures that every write to the database also updates the cache synchronously, so the cached data is always strongly consistent with the database. This is critical for the Oracle RDS workload where multiple applications require immediate consistency. Amazon ElastiCache (Redis or Memcached) supports write-through by updating the cache on every write operation, preventing stale reads.

Answer

Eventual consistency with DynamoDB Accelerator (DAX)

Answer

Read-only cache with Amazon ElastiCache

Answer

Lazy loading with cache-aside pattern

Question 6

A company is building a real-time analytics dashboard for IoT sensor data. The data arrives as JSON and needs to be stored in a way that supports fast ingestion and complex queries. Which database service is best suited?

Accepted Answer

Amazon Timestream. Amazon Timestream is purpose-built for time-series data, offering fast ingestion of JSON sensor data and optimized storage for time-based queries. It automatically manages retention, compression, and tiering (memory and magnetic store), enabling complex analytical queries (e.g., window functions, interpolation) without manual tuning. This makes it ideal for real-time IoT analytics dashboards.

Answer

Amazon RDS for PostgreSQL

Answer

Amazon DynamoDB with TTL

Answer

Amazon Redshift

Question 7

A company needs to store and manage user sessions for a web application. The application runs on multiple EC2 instances, and sessions must be accessible from any instance. The team wants a fully managed, highly available, and low-latency solution. Which AWS service should they use?

Accepted Answer

Amazon ElastiCache for Redis. Amazon ElastiCache for Redis is the correct choice because it provides a fully managed, in-memory data store with sub-millisecond latency, making it ideal for storing user session data that must be accessed from any EC2 instance. Redis supports atomic operations and data structures (e.g., TTL-based key expiration) that are well-suited for session management, and its replication and Multi-AZ failover ensure high availability. This meets the requirement for a fully managed, highly available, and low-latency solution without the overhead of managing a database cluster.

Answer

Amazon RDS for MySQL

Answer

Amazon DynamoDB

Answer

Amazon S3

Question 8

A company wants to run a graph database for a social network application. The data model involves users, posts, comments, and likes, with many-to-many relationships. Which AWS database service is most appropriate?

Accepted Answer

Amazon Neptune. Amazon Neptune is purpose-built for highly connected data, supporting property graph and RDF models with SPARQL and Gremlin/TinkerPop query languages. For a social network with users, posts, comments, and likes forming many-to-many relationships, Neptune efficiently traverses these connections using graph traversal algorithms, avoiding the expensive JOINs or denormalization required by other database types.

Answer

Amazon RDS for PostgreSQL

Answer

Amazon DocumentDB

Answer

Amazon DynamoDB

Question 9

A company runs a reporting application that queries an Amazon RDS for PostgreSQL database. The queries are complex and take a long time to run, causing performance degradation on the primary instance. The team wants to improve query performance without affecting the transactional workload. Which solution should they use?

Accepted Answer

Create one or more read replicas and direct reporting queries to them. Amazon RDS read replicas allow you to offload read-heavy reporting queries from the primary PostgreSQL instance. By directing complex, long-running queries to one or more read replicas, you eliminate resource contention on the primary instance, preserving transactional workload performance. RDS for PostgreSQL supports up to 15 read replicas, which can be promoted to a primary instance if needed, and they use asynchronous replication to stay nearly current.

Answer

Increase the instance size of the primary database

Answer

Migrate to Amazon RDS for MySQL and use Multi-AZ

Answer

Use Amazon ElastiCache to cache the results of complex queries

Question 10

A company uses Amazon DynamoDB to store order data. The table has a primary key (OrderID) and a Global Secondary Index (GSI) on CustomerID. The application often queries for all orders of a customer sorted by order date. The GSI projects only the keys. The queries are slow. What should the team do to improve query performance? (Choose two.)

Accepted Answer

Modify the GSI to include OrderDate as a sort key. The queries are slow because the GSI projects only keys. When querying the GSI, DynamoDB must fetch the full items from the base table (a 'fetch' operation) for each key, which is inefficient. Option C (modifying the GSI to include OrderDate as a sort key) allows the GSI to sort results by order date natively, improving query performance. Option E (changing the GSI projection to include all attributes) avoids the extra fetch by storing all attributes in the GSI, eliminating the need to access the base table. Option A (DAX) caches results but doesn't solve the sorting or projection issue. Option B (increasing read capacity) doesn't address the inefficiency of key-only projection. Option D (using an LSI) is not possible because LSIs require the same partition key as the base table; CustomerID is different from OrderID, so an LSI cannot be used.

Answer

Enable DynamoDB Accelerator (DAX) for the table

Answer

Increase the read capacity of the GSI

Answer

Use a Local Secondary Index (LSI) instead of a GSI

Question 11

A company runs an e-commerce application on Amazon RDS for MySQL. The application experiences read-heavy traffic during flash sales. The development team wants to offload read traffic without changing the application code. Which solution should be used?

Accepted Answer

Create an RDS Read Replica and point read traffic to the replica endpoint.. Creating an RDS Read Replica allows read-heavy traffic to be offloaded from the primary RDS instance without any application code changes. The application simply needs to be configured to use the read replica's endpoint for SELECT queries, while writes continue to the primary instance. This directly addresses the requirement to offload read traffic without modifying the application code.

Answer

Implement an Amazon ElastiCache cluster and update the application to cache queries.

Answer

Configure Multi-AZ deployment for the RDS instance.

Answer

Use DynamoDB Accelerator (DAX) in front of the RDS instance.

Question 12

A financial services company uses Amazon DynamoDB to store transaction records. The table has a partition key of 'AccountId' and a sort key of 'TransactionDate'. The company needs to run analytical queries that aggregate transactions by account and month. Currently, queries are slow due to full table scans. Which design change will improve query performance most effectively?

Accepted Answer

Create a Global Secondary Index (GSI) with partition key AccountId and sort key Month.. Creating a Global Secondary Index (GSI) with partition key AccountId and sort key Month allows the analytical queries to efficiently retrieve aggregated data by account and month without scanning the entire base table. The GSI reorganizes data by month, enabling DynamoDB to use the sort key for range queries and avoid full table scans, which directly addresses the performance issue.

Answer

Add DynamoDB Accelerator (DAX) to the table.

Answer

Change the table's sort key from TransactionDate to Month.

Answer

Enable DynamoDB Streams and process the stream with AWS Lambda to pre-aggregate results.

Question 13

A company needs to migrate an on-premises PostgreSQL database to Amazon Aurora PostgreSQL. The database is 2 TB in size and has a 24/7 uptime requirement. Which AWS service should be used to perform the migration with minimal downtime?

Accepted Answer

AWS Database Migration Service (DMS). AWS Database Migration Service (DMS) is the correct choice because it supports ongoing replication from an on-premises PostgreSQL source to Amazon Aurora PostgreSQL, enabling a migration with minimal downtime. DMS can perform a full load of the 2 TB database and then continuously replicate changes using PostgreSQL's logical replication (via the pglogical extension or native slot-based replication) until the cutover, keeping the source available throughout the process.

Answer

AWS Schema Conversion Tool (SCT)

Answer

AWS S3

Answer

pg_dump and pg_restore

Question 14

A company uses Amazon RDS for MySQL with Multi-AZ. During a recent failover test, the database experienced a 5-minute write outage. The application can tolerate up to 1 minute of downtime. Which solution should be used to reduce the failover time?

Accepted Answer

Migrate to Amazon Aurora MySQL.. Amazon Aurora MySQL is designed to reduce failover time significantly compared to standard RDS for MySQL Multi-AZ. Aurora typically completes failover in under 60 seconds by using a shared distributed storage volume across multiple Availability Zones, eliminating the need to replay redo logs on the standby. This directly meets the application's requirement of tolerating up to 1 minute of downtime.

Answer

Use Amazon RDS Proxy between the application and the database.

Answer

Enable automatic failover on the Multi-AZ deployment.

Answer

Decrease the DNS TTL on the RDS endpoint.

Question 15

A company is designing a database for a social media application that stores user posts. Each post can have multiple tags. The workload requires low-latency queries to find all posts with a specific tag. Which database design is most suitable?

Accepted Answer

Amazon DynamoDB with a Global Secondary Index on the tag attribute.. Amazon DynamoDB with a Global Secondary Index (GSI) on the tag attribute is the most suitable design because it allows low-latency queries to find all posts with a specific tag without scanning the entire table. The GSI enables efficient querying by tag as a partition key, supporting the required access pattern with consistent single-digit millisecond performance at any scale.

Answer

Amazon ElastiCache for Memcached storing posts and tags as key-value pairs.

Answer

Amazon RDS for MySQL with a normalized schema and JOIN queries.

Answer

Amazon Neptune with a graph model for tags and posts.