Amazon DBS-C01 Online Practice
Questions and Exam Preparation
DBS-C01 Exam Details
Exam Code
:DBS-C01
Exam Name
:AWS Certified Database - Specialty (DBS-C01)
Certification
:Amazon Certifications
Vendor
:Amazon
Total Questions
:321 Q&As
Last Updated
:May 30, 2026
Amazon DBS-C01 Online Questions &
Answers
Question 141:
A company hosts an on-premises Microsoft SQL Server Enterprise edition database with Transparent Data Encryption (TDE) enabled. The database is 20 TB in size and includes sparse tables. The company needs to migrate the database to Amazon RDS for SQL Server during a maintenance window that is scheduled for an upcoming weekend. Data-at- rest encryption must be enabled for the target DB instance.
Which combination of steps should the company take to migrate the database to AWS in the MOST operationally efficient manner? (Choose two.)
A. Use AWS Database Migration Service (AWS DMS) to migrate from the on-premises source database to the RDS for SQL Server target database. B. Disable TDE. Create a database backup without encryption. Copy the backup to Amazon S3. C. Restore the backup to the RDS for SQL Server DB instance. Enable TDE for the RDS for SQL Server DB instance. D. Set up an AWS Snowball Edge device. Copy the database backup to the device. Send the device to AWS. Restore the database from Amazon S3. E. Encrypt the data with client-side encryption before transferring the data to Amazon RDS.
B. Disable TDE. Create a database backup without encryption. Copy the backup to Amazon S3. C. Restore the backup to the RDS for SQL Server DB instance. Enable TDE for the RDS for SQL Server DB instance.
A company has a database monitoring solution that uses Amazon CloudWatch for its Amazon RDS for SQL Server environment. The cause of a recent spike in CPU utilization was not determined using the standard metrics that were collected. The CPU spike caused the application to perform poorly, impacting users. A Database Specialist needs to determine what caused the CPU spike.
Which combination of steps should be taken to provide more visibility into the processes and queries running during an increase in CPU load? (Choose two.)
A. Enable Amazon CloudWatch Events and view the incoming T-SQL statements causing the CPU to spike. B. Enable Enhanced Monitoring metrics to view CPU utilization at the RDS SQL Server DB instance level. C. Implement a caching layer to help with repeated queries on the RDS SQL Server DB instance. D. Use Amazon QuickSight to view the SQL statement being run. E. Enable Amazon RDS Performance Insights to view the database load and filter the load by waits, SQL statements, hosts, or users.
B. Enable Enhanced Monitoring metrics to view CPU utilization at the RDS SQL Server DB instance level. E. Enable Amazon RDS Performance Insights to view the database load and filter the load by waits, SQL statements, hosts, or users.
Explanation/Reference:
https://aws.amazon.com/premiumsupport/knowledge-center/rds-instance- high-cpu/ "Several factors can cause an increase in CPU utilization. For example, user- initiated heavy workloads, analytic queries, prolonged deadlocks and lock waits, multiple concurrent transactions, long-running transactions, or other processes that utilize CPU resources. First, you can identify the source of the CPU usage by: Using Enhanced Monitoring Using Performance Insights"
Question 143:
An ecommerce company has tasked a Database Specialist with creating a reporting dashboard that visualizes critical business metrics that will be pulled from the core production database running on Amazon Aurora. Data that is read by the dashboard should be available within 100 milliseconds of an update.
The Database Specialist needs to review the current configuration of the Aurora DB cluster and develop a cost-effective solution. The solution needs to accommodate the unpredictable read workload from the reporting dashboard without any impact on the write availability and performance of the DB cluster.
Which solution meets these requirements?
A. Turn on the serverless option in the DB cluster so it can automatically scale based on demand. B. Provision a clone of the existing DB cluster for the new Application team. C. Create a separate DB cluster for the new workload, refresh from the source DB cluster, and set up ongoing replication using AWS DMS change data capture (CDC). D. Add an automatic scaling policy to the DB cluster to add Aurora Replicas to the cluster based on CPU consumption.
A. Turn on the serverless option in the DB cluster so it can automatically scale based on demand.
Explanation/Reference:
Question 144:
An application reads and writes data to an Amazon RDS for MySQL DB instance. A new reporting dashboard needs read-only access to the database. When the application and reports are both under heavy load, the database experiences performance degradation. A database specialist needs to improve the database performance.
What should the database specialist do to meet these requirements?
A. Create a read replica of the DB instance. Configure the reports to connect to the replication instance endpoint. B. Create a read replica of the DB instance. Configure the application and reports to connect to the cluster endpoint. C. Enable Multi-AZ deployment. Configure the reports to connect to the standby replica. D. Enable Multi-AZ deployment. Configure the application and reports to connect to the cluster endpoint.
A. Create a read replica of the DB instance. Configure the reports to connect to the replication instance endpoint.
A database specialist is building a system that uses a static vendor dataset of postal codes and related territory information that is less than 1 GB in size. The dataset is loaded into the application's cache at start up. The company needs to store this data in a way that provides the lowest cost with a low application startup time.
Which approach will meet these requirements?
A. Use an Amazon RDS DB instance. Shut down the instance once the data has been read. B. Use Amazon Aurora Serverless. Allow the service to spin resources up and down, as needed. C. Use Amazon DynamoDB in on-demand capacity mode. D. Use Amazon S3 and load the data from flat files.
D. Use Amazon S3 and load the data from flat files.
Explanation/Reference:
https://www.sumologic.com/insight/s3-cost-optimization/ For example, for 1 GB file stored on S3 with 1 TB of storage provisioned, you are billed for 1 GB only. In a lot of other services such as Amazon EC2, Amazon Elastic Block Storage (Amazon EBS) and Amazon DynamoDB you pay for provisioned capacity. For example, in the case of Amazon EBS disk you pay for the size of 1 TB of disk even if you just save 1 GB file. This makes managing S3 cost easier than many other services including Amazon EBS and Amazon EC2. On S3 there is no risk of over-provisioning and no need to manage disk utilization.
Question 146:
A company is using Amazon Redshift. A database specialist needs to allow an existing Redshift cluster to access data from other Redshift clusters. Amazon RDS for PostgreSQL databases, and AWS Glue Data Catalog tables.
Which combination of steps will meet these requirements with the MOST operational efficiency? (Choose three.)
A. Take a snapshot of the required tables from the other Redshift clusters. Restore the snapshot into the existing Redshift cluster. B. Create external tables in the existing Redshift database to connect to the AWS Glue Data Catalog tables. C. Unload the RDS tables and the tables from the other Redshift clusters into Amazon S3. Run COPY commands to load the tables into the existing Redshift cluster. D. Use federated queries to access data in Amazon RDS. E. Use data sharing to access data from the other Redshift clusters. F. Use AWS Glue jobs to transfer the AWS Glue Data Catalog tables into Amazon S3. Create external tables in the existing Redshift database to access this data.
B. Create external tables in the existing Redshift database to connect to the AWS Glue Data Catalog tables. D. Use federated queries to access data in Amazon RDS. E. Use data sharing to access data from the other Redshift clusters.
Explanation/Reference:
Correct Answer: B, D, E from Amazon documents: To allow an existing Redshift cluster to access data from other Redshift clusters, Amazon RDS for PostgreSQL databases, and AWS Glue Data Catalog tables, the database specialist should use the following features123: Create external tables in the existing Redshift database to connect to the AWS Glue Data Catalog tables. This feature allows you to query data stored in Amazon S3 using the AWS Glue Data Catalog as the metadata store. You can create external tables in your Redshift database that reference the data catalog tables and use SQL to query the data in S3. This feature is operationally efficient because it does not require moving or copying the data from S3 to Redshift1. Use federated queries to access data in Amazon RDS. This feature allows you to query and join data from one or more Amazon RDS for PostgreSQL and Amazon Aurora PostgreSQL databases with data already in your Amazon Redshift cluster. You can use SQL to query the RDS databases directly from your Redshift cluster without having to load or unload any data. This feature is operationally efficient because it reduces data movement and storage costs, and simplifies data access and analysis2. Use data sharing to access data from the other Redshift clusters. This feature allows you to securely share live data across different Redshift clusters without the complexity and delays associated with data copies and data movement. You can share data within or across AWS accounts using a consumer-producer model. The producer cluster grants privileges on one or more schemas, called datashares, to the consumer clusters. The consumer clusters can then query the shared data in the producer cluster as if it were local tables. This feature is operationally efficient because it enables real-time and transactionally consistent data access, and eliminates data duplication and stale data issues3. Therefore, option B, D, and E are the correct steps to meet the requirements with the most operational efficiency. Option A is not efficient because it involves taking and restoring snapshots, which can be time-consuming and costly. Option C is not efficient because it involves unloading and loading data between S3 and Redshift, which can also incur additional time and cost. Option F is not necessary because it involves transferring the AWS Glue Data Catalog tables into S3, which can be avoided by using external tables to connect to the data catalog tables directly.
Question 147:
A business's mission-critical production workload is being operated on a 500 GB Amazon Aurora MySQL DB cluster. A database engineer must migrate the workload without causing data loss to a new Amazon Aurora Serverless MySQL DB cluster.
Which approach will result in the LEAST amount of downtime and the LEAST amount of application impact?
A. Modify the existing DB cluster and update the Aurora configuration to Serverless. B. Create a snapshot of the existing DB cluster and restore it to a new Aurora Serverless DB cluster. C. Create an Aurora Serverless replica from the existing DB cluster and promote it to primary when the replica lag is minimal. D. Replicate the data between the existing DB cluster and a new Aurora Serverless DB cluster by using AWS Database Migration Service (AWS DMS) with change data capture (CDC) enabled.
D. Replicate the data between the existing DB cluster and a new Aurora Serverless DB cluster by using AWS Database Migration Service (AWS DMS) with change data capture (CDC) enabled.
On a single Amazon RDS DB instance, a business hosts a MySQL database for its ecommerce application. Automatically saving application purchases to the database results in high-volume writes. Employees routinely create purchase reports for the company. The organization wants to boost database performance and minimize downtime associated with upgrade patching.
Which technique will satisfy these criteria with the LEAST amount of operational overhead?
A. Enable a Multi-AZ deployment of the RDS for MySQL DB instance, and enable Memcached in the MySQL option group. B. Enable a Multi-AZ deployment of the RDS for MySQL DB instance, and set up replication to a MySQL DB instance running on Amazon EC2. C. Enable a Multi-AZ deployment of the RDS for MySQL DB instance, and add a read replica. D. Add a read replica and promote it to an Amazon Aurora MySQL DB cluster master. Then enable Amazon Aurora Serverless.
C. Enable a Multi-AZ deployment of the RDS for MySQL DB instance, and add a read replica.
Explanation/Reference:
Question 149:
AWS CloudFormation stack including an Amazon RDS database instance was mistakenly removed, resulting in the loss of recent data. A Database Specialist must apply RDS parameters to the CloudFormation template in order to minimize the possibility of future inadvertent instance data loss.
Which settings will satisfy this criterion? (Select three.)
A. Set DeletionProtection to True B. Set MultiAZ to True C. Set TerminationProtection to True D. Set DeleteAutomatedBackups to False E. Set DeletionPolicy to Delete F. Set DeletionPolicy to Retain
A. Set DeletionProtection to True D. Set DeleteAutomatedBackups to False F. Set DeletionPolicy to Retain
Explanation/Reference:
A - https://aws.amazon.com/about-aws/whats-new/2018/09/amazon-rds- now-provides-database-deletion-protection/
D https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_WorkingWithAutomat edBackups.html
F - https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-attribute- deletionpolicy.html
Question 150:
A manufacturing company's website uses an Amazon Aurora PostgreSQL DB cluster.
Which configurations will result in the LEAST application downtime during a failover? (Choose three.)
A. Use the provided read and write Aurora endpoints to establish a connection to the Aurora DB cluster. B. Create an Amazon CloudWatch alert triggering a restore in another Availability Zone when the primary Aurora DB cluster is unreachable. C. Edit and enable Aurora DB cluster cache management in parameter groups. D. Set TCP keepalive parameters to a high value. E. Set JDBC connection string timeout variables to a low value. F. Set Java DNS caching timeouts to a high value.
A. Use the provided read and write Aurora endpoints to establish a connection to the Aurora DB cluster. B. Create an Amazon CloudWatch alert triggering a restore in another Availability Zone when the primary Aurora DB cluster is unreachable. C. Edit and enable Aurora DB cluster cache management in parameter groups.
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