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

Question 1

A company runs a PostgreSQL database on Amazon RDS for a CRM application. The database is 500 GB and experiences high read traffic. The company wants to improve read scalability and reduce latency. Which TWO actions should the company take? (Choose two.)

Accepted Answer

Implement Amazon ElastiCache for Redis to cache common queries.. Option A is correct because Amazon ElastiCache for Redis can cache the results of frequently executed read queries, offloading read traffic from the RDS PostgreSQL instance and reducing latency for repeated queries. This is especially effective for read-heavy workloads where the same data is requested many times, as Redis provides sub-millisecond response times and reduces the load on the database.

Answer

Store large objects in Amazon S3 and reference them.

Answer

Enable Multi-AZ for automatic failover.

Answer

Migrate data to Amazon DynamoDB with Global Tables.

Question 2

A company runs a critical e-commerce platform on Amazon Aurora MySQL. The database is 2 TB and experiences a sudden spike in write latency during flash sales. The application uses auto-generated UUIDs as primary keys. The CPU utilization on the writer instance is 80%, and the read replicas show low utilization. Write latency has increased from 5 ms to 200 ms. The company needs to reduce write latency with minimal application changes. Which course of action is MOST effective?

Accepted Answer

Change the primary key to an auto-increment BIGINT and recreate indexes.. B is correct because UUID primary keys cause random writes that fragment the B-tree index, leading to frequent page splits and high write latency. Changing to an auto-increment BIGINT allows sequential writes, which fill index pages contiguously and reduce the write amplification that drives latency from 5 ms to 200 ms. This requires no application logic changes beyond the schema migration, making it the most effective minimal-change solution.

Answer

Implement sharding across multiple Aurora clusters.

Answer

Add more read replicas and redirect write-heavy queries to replicas.

Answer

Upgrade the writer instance to a larger instance type with more IOPS.

Question 3

A company is building a real-time chat application that requires storing messages with a maximum of 10,000 characters per message. The application needs sub-millisecond latency for reads and writes. The data must be durable and replicated across three Availability Zones. The development team wants to minimize operational overhead. Which AWS database service is most appropriate?

Accepted Answer

Amazon DynamoDB with DAX. Amazon DynamoDB with DAX is the most appropriate choice because it provides single-digit millisecond latency for reads and writes, supports up to 400 KB per item (easily accommodating 10,000 characters), and offers built-in replication across three Availability Zones for durability. DAX (DynamoDB Accelerator) further reduces read latency to sub-millisecond by serving as an in-memory cache, while DynamoDB itself handles write durability and replication automatically, minimizing operational overhead.

Answer

Amazon ElastiCache for Redis with replication

Answer

Amazon RDS for PostgreSQL with Multi-AZ

Answer

Amazon Aurora MySQL with Multi-AZ

Question 4

A company uses Amazon RDS for SQL Server with a 4 TB database for a financial reporting application. The database performs nightly batch updates that take 6 hours. The company needs to reduce the batch update time to under 2 hours. The current instance is db.r5.8xlarge with 64 vCPUs and 512 GB memory. The batch process is I/O-bound with high write throughput. Which change will MOST effectively reduce the batch update time?

Accepted Answer

Switch to Provisioned IOPS (io2) with 80,000 IOPS.. The batch process is I/O-bound with high write throughput, so the bottleneck is disk I/O, not compute or memory. Switching to Provisioned IOPS (io2) with 80,000 IOPS provides a predictable, high-performance storage tier that can sustain the required write throughput, directly reducing the batch update time from 6 hours to under 2 hours. RDS for SQL Server on io2 volumes delivers consistent low-latency I/O, which is critical for write-heavy workloads.

Answer

Upgrade to db.r5.16xlarge with 128 vCPUs.

Answer

Increase the instance memory to 1024 GB.

Answer

Enable Multi-AZ deployment.

Question 5

A company is running a MySQL database on Amazon RDS for a web application. The application experiences read-heavy traffic, and the company wants to improve read performance without changing the application code. Which design should the database specialist recommend?

Accepted Answer

Create one or more read replicas of the RDS DB instance.. Option B is correct because Amazon RDS read replicas allow you to offload read traffic from the primary DB instance without any application code changes. The application simply connects to the read replica endpoint(s) for SELECT queries, while writes continue to the primary instance. This directly addresses the read-heavy workload by distributing read requests across multiple copies of the database.

Answer

Implement an Amazon ElastiCache Redis cluster in front of the database.

Answer

Increase the instance size of the RDS DB instance.

Answer

Enable DynamoDB Accelerator (DAX) for the RDS instance.

Question 6

A company is designing a database for a global e-commerce platform that requires low-latency reads and writes across multiple AWS Regions. The database must support strongly consistent reads and provide automatic failover. Which AWS service should the company use?

Accepted Answer

Amazon DynamoDB global tables. Amazon DynamoDB global tables provide a fully managed, multi-Region, multi-active database solution that delivers low-latency reads and writes across AWS Regions. It supports strongly consistent reads when using the same-Region endpoint and offers automatic failover by allowing any Region to handle writes independently, ensuring high availability without manual intervention.

Answer

Amazon ElastiCache for Redis global datastore

Answer

Amazon S3 with cross-region replication

Answer

Amazon Aurora Global Database

Question 7

A company is migrating a PostgreSQL database to Amazon Aurora PostgreSQL. The current database has complex queries that join multiple tables and performs well. After migration, the same queries are slower on Aurora. What is the most likely cause?

Accepted Answer

The DB instance class does not have enough memory for the buffer cache.. Option A is correct because after migrating to Aurora PostgreSQL, the same complex queries are slower, which often indicates that the buffer cache is too small to hold the working set of data. Aurora uses a distributed storage system where the buffer cache is managed by the DB instance's memory; if the instance class lacks sufficient memory, frequently accessed data pages must be read from storage more often, increasing I/O latency. This is a common performance bottleneck when migrating from on-premises PostgreSQL, where the buffer cache might have been larger or the working set fit entirely in memory.

Answer

Aurora PostgreSQL does not support complex joins; the queries must be rewritten.

Answer

Aurora PostgreSQL does not support indexes on joined columns.

Answer

The default DB parameter group is optimized for write-heavy workloads, not read-heavy.

Question 8

A company uses Amazon DynamoDB for a gaming application that stores player data. The application frequently accesses items by the player's user ID. However, the company also needs to query players by their subscription tier (Gold, Silver, Bronze) and registration date. Which design should the database specialist recommend for this access pattern?

Accepted Answer

Create a Global Secondary Index (GSI) on subscription tier and registration date.. A Global Secondary Index (GSI) on subscription tier and registration date is the correct choice because it allows efficient querying on non-primary key attributes without affecting the base table's primary key structure. DynamoDB GSIs support eventually consistent reads and can be created on any table, enabling the required access pattern of querying players by subscription tier and registration date while maintaining the primary access pattern by user ID.

Answer

Export the data to Amazon Elasticsearch Service for querying.

Answer

Create a Local Secondary Index (LSI) on subscription tier and registration date.

Answer

Enable DynamoDB Streams and process the stream to populate a separate table.

Question 9

A company is running a MongoDB-compatible database on Amazon DocumentDB. The application performs frequent updates to a small subset of fields in documents. The company notices that write latency is high. What should the database specialist recommend to reduce write latency?

Accepted Answer

Review and remove unnecessary indexes on the collection.. Option A is correct because unnecessary indexes impose a write penalty on every insert, update, and delete operation. In Amazon DocumentDB, each write must update all indexes on the collection, so removing unused indexes reduces the per-document write overhead and directly lowers write latency for frequent updates to a small subset of fields.

Answer

Increase the instance size of the DocumentDB cluster.

Answer

Enable multi-master writes to distribute write load.

Answer

Change the storage type from standard to provisioned IOPS.

Question 10

A company has a critical application that uses Amazon RDS for MySQL with Multi-AZ deployment. During a recent failure, the automatic failover took 2 minutes, causing application timeout. The company needs to reduce failover time to under 30 seconds. Which solution should the database specialist recommend?

Accepted Answer

Migrate the database to Amazon Aurora MySQL.. Amazon Aurora MySQL is designed to reduce failover time significantly compared to standard RDS MySQL Multi-AZ. Aurora typically completes failover in under 30 seconds by using a shared distributed storage volume across multiple Availability Zones, allowing the primary instance to fail over to a read replica without the need to replay redo logs or perform crash recovery. This meets the requirement of reducing failover time to under 30 seconds.

Answer

Create a read replica and promote it during failover.

Answer

Increase the DB instance class to a larger size.

Answer

Implement Amazon RDS Proxy to handle connection draining.

Question 11

A company is designing a database for an IoT application that ingests millions of small sensor readings per second. The data is time-series and queries are mostly range scans over time. The company needs a cost-effective solution with high write throughput. Which AWS service should the database specialist recommend?

Accepted Answer

Amazon Timestream. Amazon Timestream is a purpose-built time-series database designed for IoT and operational applications that ingest millions of data points per second. It automatically manages storage tiers (in-memory and magnetic) to optimize cost, and its query engine is optimized for range scans over time, making it the most cost-effective and high-throughput choice for this workload.

Answer

Amazon Redshift with auto-ingest

Answer

Amazon RDS for PostgreSQL with pg_partman extension

Answer

Amazon DynamoDB with time-series data modeling

Question 12

A company is designing a database for an e-commerce platform that needs to store product catalog data. The data is highly relational with many-to-many relationships between products, categories, and suppliers. The platform requires ACID transactions and complex joins. Which TWO AWS database solutions are suitable for this workload? (Choose TWO.)

Accepted Answer

Amazon Aurora MySQL. Amazon Aurora MySQL is a fully ACID-compliant relational database that supports complex joins and many-to-many relationships through foreign keys and junction tables. It is optimized for high-throughput e-commerce workloads with features like auto-scaling storage and up to 15 low-latency read replicas, making it suitable for product catalog data that requires transactional consistency.

Answer

Amazon ElastiCache for Redis

Answer

Amazon Neptune

Answer

Amazon DynamoDB

Question 13

A company is moving a legacy on-premises Oracle database to AWS. The database has large tables with complex stored procedures and triggers. The company wants to minimize application changes. Which THREE AWS database services should the database specialist consider? (Choose THREE.)

Accepted Answer

Amazon RDS for Oracle. Amazon RDS for Oracle (Option C) is correct because it provides native Oracle compatibility, allowing the company to migrate the legacy Oracle database with minimal application changes. It supports large tables, complex stored procedures, and triggers without requiring code modifications, as it uses the same Oracle Database engine.

Answer

Amazon Redshift

Answer

Amazon DynamoDB

Question 14

A company is designing a database for a social media application that requires storing user profiles, posts, and follower relationships. The application needs low-latency queries for user timelines and social graph traversals. Which TWO AWS database services should the database specialist consider? (Choose TWO.)

Accepted Answer

Amazon Neptune. Amazon Neptune is a fully managed graph database service optimized for storing and querying highly connected data, such as social graphs. It supports property graph and RDF models, enabling low-latency traversals of follower relationships and user timelines using Gremlin or SPARQL queries.

Answer

Amazon Timestream

Answer

Amazon Redshift

Answer

Amazon RDS for MySQL

Question 15

Refer to the exhibit. A company uses this DynamoDB table to store user session data. The application frequently queries by user_id alone to get all sessions for a user. However, the query is slow. What is the most likely cause?

Accepted Answer

The table's partition key is session_id, not user_id, so querying by user_id requires a scan.. The table's primary key is session_id, not user_id. Querying by user_id without a secondary index forces DynamoDB to perform a full table scan, which reads every item and is significantly slower than a query operation. This is the most likely cause of the slow performance.

Answer

The table has no sort key on user_id.

Answer

The table has too many items, causing slow scans.

Answer

The provisioned read capacity is too low.