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
:Jul 12, 2026
Amazon DBS-C01 Online Questions &
Answers
Question 281:
A database specialist needs to review and optimize an Amazon DynamoDB table that is experiencing performance issues. A thorough investigation by the database specialist reveals that the partition key is causing hot partitions, so a new partition key is created. The database specialist must effectively apply this new partition key to all existing and new data.
How can this solution be implemented?
A. Use Amazon EMR to export the data from the current DynamoDB table to Amazon S3. Then use Amazon EMR again to import the data from Amazon S3 into a new DynamoDB table with the new partition key. B. Use AWS DMS to copy the data from the current DynamoDB table to Amazon S3. Then import the DynamoDB table to create a new DynamoDB table with the new partition key. C. Use the AWS CLI to update the DynamoDB table and modify the partition key. D. Use the AWS CLI to back up the DynamoDB table. Then use the restore-table-from- backup command and modify the partition key.
A. Use Amazon EMR to export the data from the current DynamoDB table to Amazon S3. Then use Amazon EMR again to import the data from Amazon S3 into a new DynamoDB table with the new partition key.
A company maintains several databases using Amazon RDS for MySQL and PostgreSQL. Each RDS database generates log files with retention periods set to their default values. The company has now mandated that database logs be maintained for up to 90 days in a centralized repository to facilitate real-time and after- the-fact analyses.
What should a Database Specialist do to meet these requirements with minimal effort?
A. Create an AWS Lambda function to pull logs from the RDS databases and consolidate the log files in an Amazon S3 bucket. Set a lifecycle policy to expire the objects after 90 days. B. Modify the RDS databases to publish log to Amazon CloudWatch Logs. Change the log retention policy for each log group to expire the events after 90 days. C. Write a stored procedure in each RDS database to download the logs and consolidate the log files in an Amazon S3 bucket. Set a lifecycle policy to expire the objects after 90 days. D. Create an AWS Lambda function to download the logs from the RDS databases and publish the logs to Amazon CloudWatch Logs. Change the log retention policy for the log group to expire the events after 90 days.
B. Modify the RDS databases to publish log to Amazon CloudWatch Logs. Change the log retention policy for each log group to expire the events after 90 days.
A database specialist wants to ensure that an Amazon Aurora DB cluster is always automatically upgraded to the most recent minor version available. Noticing that there is a new minor version available, the database specialist has issues an AWS CLI command to enable automatic minor version updates. The command runs successfully, but checking the Aurora DB cluster indicates that no update to the Aurora version has been made.
What might account for this? (Choose two.)
A. The new minor version has not yet been designated as preferred and requires a manual upgrade. B. Configuring automatic upgrades using the AWS CLI is not supported. This must be enabled expressly using the AWS Management Console. C. Applying minor version upgrades requires sufficient free space. D. The AWS CLI command did not include an apply-immediately parameter. E. Aurora has detected a breaking change in the new minor version and has automatically rejected the upgrade.
A. The new minor version has not yet been designated as preferred and requires a manual upgrade. D. The AWS CLI command did not include an apply-immediately parameter.
Explanation/Reference:
"When Amazon RDS designates a minor engine version as the preferred minor engine version, each database that meets both of the following conditions is upgraded to the minor engine version automatically" https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_UpgradeDBInstance.Upgrading.html
Question 284:
A company is using an Amazon RDS for MySQL DB instance for its internal applications. A security audit shows that the DB instance is not encrypted at rest. The company's application team needs to encrypt the DB instance.
What should the team do to meet this requirement?
A. Stop the DB instance and modify it to enable encryption. Apply this setting immediately without waiting for the next scheduled RDS maintenance window. B. Stop the DB instance and create an encrypted snapshot. Restore the encrypted snapshot to a new encrypted DB instance. Delete the original DB instance, and update the applications to point to the new encrypted DB instance. C. Stop the DB instance and create a snapshot. Copy the snapshot into another encrypted snapshot. Restore the encrypted snapshot to a new encrypted DB instance. Delete the original DB instance, and update the applications to point to the new encrypted DB instance. D. Create an encrypted read replica of the DB instance. Promote the read replica to master. Delete the original DB instance, and update the applications to point to the new encrypted DB instance.
C. Stop the DB instance and create a snapshot. Copy the snapshot into another encrypted snapshot. Restore the encrypted snapshot to a new encrypted DB instance. Delete the original DB instance, and update the applications to point to the new encrypted DB instance.
Question 285:
A database specialist is designing the database for a software-as-a-service (SaaS) version of an employee information application. In the current architecture, the change history of employee records is stored in a single table in an Amazon RDS for Oracle database. Triggers on the employee table populate the history table with historical records.
This architecture has two major challenges. First, there is no way to guarantee that the records have not been changed in the history table. Second, queries on the history table are slow because of the large size of the table and the need to run the queries against a large subset of data in the table.
The database specialist must design a solution that prevents modification of the historical records. The solution also must maximize the speed of the queries.
Which solution will meet these requirements?
A. Migrate the current solution to an Amazon DynamoDB table. Use DynamoDB Streams to keep track of changes. Use DynamoDB Accelerator (DAX) to improve query performance. B. Write employee record history to Amazon Quantum Ledger Database (Amazon QLDB) for historical records and to an Amazon OpenSearch Service domain for queries. C. Use Amazon Aurora PostgreSQL to store employee record history in a single table. Use Aurora Auto Scaling to provision more capacity. D. Build a solution that uses an Amazon Redshift cluster for historical records. Query the Redshift cluster directly as needed.
B. Write employee record history to Amazon Quantum Ledger Database (Amazon QLDB) for historical records and to an Amazon OpenSearch Service domain for queries.
Explanation/Reference:
Correct Answer: B from Amazon documents: Amazon Quantum Ledger Database (Amazon QLDB) is a fully managed ledger database that provides a transparent, immutable, and cryptographically verifiable transaction log of all your application changes. Amazon QLDB tracks each and every application data change and maintains a complete and verifiable history of changes over time1. This makes it ideal for storing historical records that need to be tamper-proof and auditable. Amazon QLDB also supports PartiQL, a SQL-compatible query language that lets you query data using familiar SQL operators2. Amazon OpenSearch Service (successor to Amazon Elasticsearch Service) is a fully managed service that makes it easy to deploy, operate, and scale OpenSearch, an open source search and analytics engine. Amazon OpenSearch Service lets you store, search, and analyze large volumes of data quickly and at low cost3. You can use Amazon OpenSearch Service to index and query your employee record history data stored in Amazon QLDB using the QLDB Streams feature. This way, you can leverage the powerful search and analytics capabilities of OpenSearch Service to run fast and flexible queries on your historical data. Therefore, option B is the best solution that meets the requirements of preventing modification of the historical records and maximizing the speed of the queries. Option A is not suitable because DynamoDB is a key-value and document database that does not provide a ledger-like transaction log. Option C is not suitable because Aurora PostgreSQL is a relational database that does not guarantee immutability of the historical records. Option D is not suitable because Redshift is a data warehouse that is optimized for analytical queries on large datasets, not for storing and querying individual records.
Question 286:
A Database Specialist needs to define a database migration strategy to migrate an on- premises Oracle database to an Amazon Aurora MySQL DB cluster. The company requires near-zero downtime for the data migration. The solution must also be cost-effective.
Which approach should the Database Specialist take?
A. Dump all the tables from the Oracle database into an Amazon S3 bucket using datapump (expdp). Run data transformations in AWS Glue. Load the data from the S3 bucket to the Aurora DB cluster. B. Order an AWS Snowball appliance and copy the Oracle backup to the Snowball appliance. Once the Snowball data is delivered to Amazon S3, create a new Aurora DB cluster. Enable the S3 integration to migrate the data directly from Amazon S3 to Amazon RDS. C. Use the AWS Schema Conversion Tool (AWS SCT) to help rewrite database objects to MySQL during the schema migration. Use AWS DMS to perform the full load and change data capture (CDC) tasks. D. Use AWS Server Migration Service (AWS SMS) to import the Oracle virtual machine image as an Amazon EC2 instance. Use the Oracle Logical Dump utility to migrate the Oracle data from Amazon EC2 to an Aurora DB cluster.
C. Use the AWS Schema Conversion Tool (AWS SCT) to help rewrite database objects to MySQL during the schema migration. Use AWS DMS to perform the full load and change data capture (CDC) tasks.
A database specialist manages a critical Amazon RDS for MySQL DB instance for a company. The data stored daily could vary from .01% to 10% of the current database size. The database specialist needs to ensure that the DB instance storage grows as needed.
What is the MOST operationally efficient and cost-effective solution?
A. Configure RDS Storage Auto Scaling. B. Configure RDS instance Auto Scaling. C. Modify the DB instance allocated storage to meet the forecasted requirements. D. Monitor the Amazon CloudWatch FreeStorageSpace metric daily and add storage as required.
A. Configure RDS Storage Auto Scaling.
Explanation/Reference:
If your workload is unpredictable, you can enable storage autoscaling for an Amazon RDS DB instance. With storage autoscaling enabled, when Amazon RDS detects that you are running out of free database space it automatically scales up your storage. https://aws.amazon.com/about-aws/whats-new/2019/06/rds-storage-auto-scaling/ https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_PIOPS.StorageTypes. html#USER_PIOPS.Autoscaling
Question 288:
A company is writing a new survey application to be used with a weekly televised game show. The application will be available for 2 hours each week. The company expects to receive over 500,000 entries every week, with each survey asking 2-3 multiple choice questions of each user. A Database Specialist needs to select a platform that is highly scalable for a large number of concurrent writes to handle he anticipated volume.
Which AWS services should the Database Specialist consider? (Choose two.)
A. Amazon DynamoDB B. Amazon Redshift C. Amazon Neptune D. Amazon Elasticsearch Service E. Amazon ElastiCache
A company performs an audit on various data stores and discovers that an Amazon S3 bucket is storing a credit card number. The S3 bucket is the target of an AWS Database Migration Service (AWS DMS) continuous replication task that uses change data capture (CDC). The company determines that this field is not needed by anyone who uses the target data. The company has manually removed the existing credit card data from the S3 bucket.
What is the MOST operationally efficient way to prevent new credit card data from being written to the S3 bucket?
A. Add a transformation rule to the DMS task to ignore the column from the source data endpoint. B. Add a transformation rule to the DMS task to mask the column by using a simple SQL query. C. Configure the target S3 bucket to use server-side encryption with AWS KMS keys (SSE- KMS). D. Remove the credit card number column from the data source so that the DMS task does not need to be altered.
A. Add a transformation rule to the DMS task to ignore the column from the source data endpoint.
Question 290:
A business is operating an on-premises application that is divided into three tiers: web, application, and MySQL database. The database is predominantly accessed during business hours, with occasional bursts of activity throughout the day. As part of the company's shift to AWS, a database expert wants to increase the availability and minimize the cost of the MySQL database tier.
Which MySQL database choice satisfies these criteria?
A. Amazon RDS for MySQL with Multi-AZ B. Amazon Aurora Serverless MySQL cluster C. Amazon Aurora MySQL cluster D. Amazon RDS for MySQL with read replica
B. Amazon Aurora Serverless MySQL cluster
Explanation/Reference:
Amazon Aurora Serverless v1 is a simple, cost-effective option for infrequent, intermittent, or unpredictable workloads. https://aws.amazon.com/rds/aurora/serverless/
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