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

Question 1

A company uses Amazon DynamoDB to store session data for a web application. The table has a partition key of 'SessionId'. The company wants to automatically expire sessions after 1 hour. Which feature should be used?

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

Accepted Answer

DynamoDB Time to Live (TTL). DynamoDB Time to Live (TTL) is the correct choice because it allows you to define a per-item timestamp attribute (e.g., 'expireAt') that automatically deletes items after a specified duration—in this case, 1 hour. TTL operates at no additional cost, requires no custom code, and handles expiration asynchronously in the background, making it ideal for session data management.

Answer

DynamoDB Global Tables

Answer

AWS Lambda function that scans the table every hour and deletes old items.

Answer

DynamoDB Streams

Question 2

A company runs an Oracle database on Amazon RDS. The database is used by multiple applications, and the company needs to capture all data modification language (DML) changes for auditing. Which solution should be used?

Accepted Answer

Use AWS DMS with change data capture (CDC) to stream changes to Amazon S3.. AWS DMS with change data capture (CDC) can continuously capture DML changes from an Oracle RDS instance and stream them to Amazon S3 in a format such as Parquet or CSV. This provides a durable, queryable audit trail of all data modifications without requiring additional Oracle licensing or impacting database performance. CloudTrail captures API-level events, not DML changes, and Oracle Flashback and Audit Vault are not fully supported or manageable on Amazon RDS.

Answer

Use AWS CloudTrail to capture database events.

Answer

Enable Oracle Flashback and store the flashback logs.

Answer

Install Oracle Audit Vault on the RDS instance.

Question 3

A company uses Amazon Aurora MySQL for a SaaS application. Each tenant has a separate database. The company wants to implement a centralized monitoring solution that collects performance metrics from all tenant databases. The solution should be cost-effective and require minimal overhead. Which approach should be used?

Accepted Answer

Use Amazon CloudWatch Agent to collect custom metrics from each Aurora instance and aggregate in CloudWatch.. Amazon CloudWatch Agent can be installed on each Aurora instance to collect custom performance metrics (e.g., from performance_schema) and publish them as CloudWatch custom metrics. This approach is cost-effective because it uses CloudWatch’s pay-per-metric model and eliminates the need for a separate aggregation database or continuous data movement. It also requires minimal overhead as the agent handles collection and aggregation natively, with no additional infrastructure to manage.

Answer

Use AWS DMS to continuously replicate metrics to a central RDS instance.

Answer

Consolidate all tenants into a single RDS MySQL instance and use separate schemas.

Answer

Run an AWS Lambda function that queries each database's performance_schema every minute and stores results in S3.

Question 4

A company needs to store JSON documents that are up to 10 KB in size. The documents are accessed by a primary key, and the company requires single-digit millisecond latency. Which database service should be used?

Accepted Answer

Amazon DynamoDB. Amazon DynamoDB is the correct choice because it is a fully managed NoSQL key-value and document database that delivers single-digit millisecond latency at any scale. It natively supports JSON documents up to 400 KB in size (well above the 10 KB requirement) and provides primary key access with consistent low-latency performance, making it ideal for this workload.

Answer

Amazon Neptune

Answer

Amazon S3

Answer

Amazon RDS for MySQL with JSON data type

Question 5

A company is migrating a large Oracle data warehouse to Amazon Redshift. The source database has many complex stored procedures, views, and joins. Which THREE actions should the company take during the migration?

Accepted Answer

Use the AWS Schema Conversion Tool (SCT) to convert stored procedures.. AWS Schema Conversion Tool (SCT) is the recommended tool for converting Oracle stored procedures, functions, and packages to Amazon Redshift's PL/pgSQL-compatible language. It automates the translation of complex procedural logic, reducing manual effort and errors during migration. Redshift does not support Oracle-specific PL/SQL constructs natively, so SCT handles syntax and semantic conversion.

Answer

Migrate triggers as they are in Redshift.

Answer

Recreate all indexes from Oracle in Redshift.

Question 6

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. 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.

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 7

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. Enabling DynamoDB Adaptive Capacity with on-demand capacity mode automatically scales write capacity to handle traffic spikes during flash sales without requiring manual provisioning. This eliminates throttling while preserving the existing table schema (partition key 'user_id' and sort key 'product_id'), so the read pattern of querying the entire cart by user_id remains unchanged.

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 8

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. Amazon Timestream is purpose-built for time-series data, offering automatic tiered storage (in-memory for recent data and magnetic for historical data) and optimized query performance for time-range aggregations. Its serverless architecture eliminates provisioning overhead, making it the most cost-effective and performant choice for append-only IoT sensor data with infrequent updates.

Answer

Amazon DynamoDB with time-series design pattern

Answer

Amazon Redshift

Answer

Amazon RDS for MySQL with partitioning by date

Question 9

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. Amazon Aurora PostgreSQL is the correct choice because it provides full ACID compliance across multiple rows, which is essential for trade settlement records where each trade must be processed exactly once. Aurora PostgreSQL is a relational database that supports multi-row transactions with strong consistency, and its write-intensive workload performance is enhanced by a distributed storage subsystem that offloads redo log processing, making it suitable for high-throughput write operations while maintaining moderate read performance.

Answer

Amazon DynamoDB with DynamoDB transactions

Answer

Amazon ElastiCache for Redis

Answer

Amazon Neptune

Question 10

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. Adding a random suffix to the partition key for hot players distributes the write traffic across multiple partitions, preventing any single partition from being overwhelmed. DynamoDB's on-demand capacity mode automatically scales to handle traffic spikes, but it cannot resolve a hot key issue where all writes target the same partition key. By diversifying the partition key, writes are spread across partitions, allowing DynamoDB to utilize its full throughput capacity.

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 11

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. A multi-tenant SaaS application requiring strict data isolation with complex relational joins demands separate databases per tenant. Amazon RDS provides full relational capabilities (ACID transactions, complex joins) and provisioning separate RDS instances ensures complete tenant isolation, preventing cross-tenant data leakage and allowing independent backup, scaling, and performance tuning for each tenant.

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 12

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'. A global secondary index (GSI) with partition key 'game_id' and sort key 'score' allows efficient retrieval of the top 10 players per game by querying a single partition (game_id) and using the sort key to order by score descending. This avoids the 1 MB read limit per partition and provides the necessary ordering without scanning the entire table.

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 13

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. Creating multiple GSIs with different partition keys allows the application to support various query patterns (e.g., by category, by status, or combined) without incurring the cost of scanning the base table. DynamoDB charges for read/write capacity and storage per GSI, so multiple GSIs are cost-effective only if each serves a distinct access pattern, and this design maximizes query flexibility by enabling efficient key-based lookups for changing workloads.

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 14

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. Amazon Neptune is a fully managed graph database service purpose-built for storing and traversing highly connected data. It supports both property graph (Gremlin, openCypher) and RDF (SPARQL) models, making it ideal for recommendation engines that require multi-edge traversals across user relationships.

Answer

Amazon DynamoDB with adjacency list design

Answer

Amazon DocumentDB (with MongoDB compatibility)

Answer

Amazon RDS for PostgreSQL with recursive CTEs

Question 15

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. Amazon Aurora Global Database uses storage-based replication with a typical latency of under 1 second, supporting cross-region disaster recovery with an RPO of less than 1 second and an RTO of less than 1 minute by promoting a secondary region to primary. Amazon DynamoDB Global Tables provide multi-region, fully replicated tables with strong consistency and automatic failover, achieving RPO of less than 1 second and RTO of less than 1 minute through active-active replication.

Answer

Amazon RDS Multi-AZ

Answer

Amazon Redshift with cross-region snapshot copy

Answer

Amazon ElastiCache for Redis with Global Datastore