DBS-C01 Practice Test 3 — 30 Questions

Question 1

A company is deploying a globally distributed application with users in the US, Europe, and Asia. The application requires sub-10ms read latency for user profiles stored in Amazon DynamoDB. Writes are less frequent. Which configuration meets the latency requirement while minimizing write conflicts?

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

Accepted Answer

Use DynamoDB global tables to replicate data to Regions close to users.. DynamoDB global tables provide multi-region, multi-active replication with eventual consistency, enabling sub-10ms reads from local replicas while writes are replicated asynchronously. This minimizes write conflicts because DynamoDB uses last-writer-wins (LWW) conflict resolution, which is acceptable for user profiles where writes are infrequent and conflicts are rare.

Answer

Deploy Amazon RDS for MySQL with Multi-AZ and cross-Region read replicas.

Answer

Use Amazon ElastiCache for Redis Global Datastore with DynamoDB as backing store.

Answer

Deploy a single DynamoDB table in us-east-1 with DAX caches in each region.

Question 2

A company is designing a database for an IoT application that ingests millions of sensor readings per second. Each reading includes device ID, timestamp, and measurement. The workload requires time-series analytics and data retention for 90 days. Which AWS database solution is MOST appropriate?

Accepted Answer

Amazon Timestream. Amazon Timestream is a purpose-built time-series database designed for IoT and operational applications that ingest millions of sensor readings per second. It automatically manages data retention policies (e.g., 90 days) by storing recent data in memory and historical data in a cost-optimized store, and it supports time-series analytics with built-in functions like interpolation and smoothing.

Answer

Amazon Redshift with auto-copy from S3

Answer

Amazon ElastiCache for Redis with time-series module

Answer

Amazon DynamoDB with TTL

Question 3

A financial services company is migrating an on-premises Oracle database to Amazon RDS for Oracle. The database has a high volume of write transactions and requires minimal downtime during migration. Which AWS service or feature should be used to replicate data continuously to the target RDS instance during the migration?

Accepted Answer

AWS Database Migration Service (AWS DMS) with ongoing replication. AWS Database Migration Service (AWS DMS) with ongoing replication (change data capture, CDC) is the correct choice because it continuously captures and applies changes from the source Oracle database to the target Amazon RDS for Oracle instance, enabling near-zero downtime during migration. This is achieved by using Oracle's redo logs to stream transactions in real time, which meets the high write volume and minimal downtime requirements.

Answer

Amazon RDS Read Replica

Answer

Amazon RDS Multi-AZ deployment

Answer

AWS Schema Conversion Tool (AWS SCT)

Question 4

A company is migrating a large Oracle data warehouse to AWS. The warehouse contains 50 TB of data and runs complex analytical queries. The solution must support concurrency of up to 100 users and provide high performance for queries. Which THREE design decisions should the company make? (Choose three.)

Accepted Answer

Use distribution keys based on frequently joined columns. Distribution keys based on frequently joined columns ensure that related data is co-located on the same compute nodes, minimizing data movement across the network during joins. This is critical for complex analytical queries on large datasets in Amazon Redshift, as it reduces shuffle overhead and improves query performance.

Answer

Use Amazon RDS for Oracle with Multi-AZ

Answer

Use Amazon DynamoDB with global tables

Question 5

A company is designing a database for an e-commerce platform that requires high availability and automatic failover with minimal downtime. The application performs both OLTP and read-heavy analytics. Which AWS database service should be used?

Accepted Answer

Amazon Aurora. Amazon Aurora is the correct choice because it combines the high availability and automatic failover of a relational database with the performance needed for both OLTP and read-heavy analytics. Aurora provides six-way replication across three Availability Zones, automatic failover in under 30 seconds, and supports up to 15 low-latency read replicas that can offload analytics queries without impacting write performance.

Answer

Amazon DynamoDB

Answer

Amazon RDS for MySQL

Answer

Amazon Redshift

Question 6

A company is migrating a 10 TB Oracle data warehouse to Amazon Redshift. The migration must minimize data transfer costs and ensure data integrity. Which TWO steps should the company take?

Accepted Answer

Use AWS Schema Conversion Tool (SCT) to convert the Oracle schema to Redshift. The AWS Schema Conversion Tool (SCT) is specifically designed to convert Oracle database schemas to Amazon Redshift-compatible schemas, handling data type mappings, stored procedures, and other schema objects. This step is critical for a successful migration as it ensures the target schema is optimized for Redshift's columnar storage and MPP architecture, reducing manual rework and potential data integrity issues.

Answer

Use AWS DMS to replicate data directly over the internet

Answer

Use Amazon Kinesis Data Streams to stream data to Redshift

Answer

Use Amazon Redshift Spectrum to query data in S3 after loading

Question 7

A company is designing a database for a social media application that requires low-latency access to user profiles and support for complex graph queries. Which AWS database service is most suitable for this workload?

Accepted Answer

Amazon Neptune. Amazon Neptune is a fully managed graph database service optimized for storing and querying highly connected data. It supports both property graph (Apache TinkerPop/Gremlin) and RDF (SPARQL) models, making it the ideal choice for social media applications that require low-latency traversal of complex relationships, such as friend-of-friend recommendations or influence paths.

Answer

Amazon DynamoDB

Answer

Amazon ElastiCache for Redis

Answer

Amazon RDS for MySQL

Question 8

Match each AWS monitoring tool to its capability for databases.

Accepted Answer

Amazon CloudWatch: Monitors AWS resources and applications, provides metrics and logs. Correct matches: CloudWatch monitors metrics and logs, Performance Insights analyzes database load, Enhanced Monitoring provides OS-level metrics, and CloudTrail records API activity. Common confusions include mixing Enhanced Monitoring with CloudWatch and Performance Insights with CloudTrail.

Answer

Amazon CloudWatch: Provides OS-level metrics for RDS instances

Answer

Amazon RDS Performance Insights: Records API calls for database actions

Question 9

A company is using Amazon RDS for PostgreSQL for its transactional database. The application generates reports that query millions of rows, causing high CPU on the primary instance. The reports are not time-sensitive. What is the MOST cost-effective way to offload the reporting queries without affecting write performance?

Accepted Answer

Create an Amazon RDS Read Replica and direct reporting queries to the replica.. Creating an Amazon RDS Read Replica offloads reporting queries to a separate read-only instance, preventing CPU contention on the primary. Since the reports are not time-sensitive, the replica can handle the large queries without impacting write performance, and it is cost-effective because you only pay for the replica's compute and storage.

Answer

Use Amazon ElastiCache to cache report results.

Answer

Enable Multi-AZ to distribute reads to the standby instance.

Answer

Migrate reporting to Amazon Redshift.

Question 10

A developer sees the above key schema for the ProductCatalog table. Which query will be most efficient for retrieving a single item?

Accepted Answer

GetItem with ProductId = '123' and Category = 'Books'. The ProductCatalog table's primary key is a composite key of Category (partition key) and ProductId (sort key). A GetItem operation with both the partition key and sort key provides the most efficient direct access to a single item, as it uses the primary key to retrieve the item with exactly one read operation, without any filtering or scanning.

Answer

Query with Category = 'Books'

Answer

GetItem with ProductId = '123'

Answer

Scan the table and filter by ProductId

Question 11

A company is using Amazon DynamoDB to store session data for a web application. The session data expires after 24 hours. Which DynamoDB feature should the company use to automatically delete expired items?

Accepted Answer

DynamoDB Time to Live (TTL). DynamoDB Time to Live (TTL) is the correct choice because it provides a cost-effective, fully managed mechanism to automatically delete expired items based on a timestamp attribute in the table. TTL works by comparing the current time to the epoch time value stored in the designated TTL attribute; when the value is in the past, DynamoDB marks the item for deletion, typically within 48 hours. This eliminates the need for custom code or additional AWS services, directly addressing the requirement to remove session data after 24 hours.

Answer

A retention policy on the DynamoDB table

Answer

DynamoDB Streams

Answer

A scheduled AWS Lambda function that scans and deletes expired items

Question 12

Which TWO techniques can reduce read latency for frequently accessed data in Amazon DynamoDB? (Choose 2.)

Accepted Answer

Add Global Secondary Indexes (GSI) for common query patterns. Adding Global Secondary Indexes (GSI) allows you to pre-materialize alternative query patterns, enabling efficient lookups on non-key attributes without scanning the entire table. This reduces read latency for frequently accessed data by providing a pre-sorted and partitioned index that DynamoDB can query directly, avoiding expensive full-table scans.

Answer

Use strongly consistent reads

Answer

Increase write capacity units

Answer

Decrease read capacity units

Question 13

A company runs a critical Amazon DynamoDB table with on-demand capacity. The table experiences throttling errors (ProvisionedThroughputExceededException) during peak hours. The table has a global secondary index (GSI) with a different partition key. What is the MOST likely cause of the throttling?

Accepted Answer

The global secondary index is throttling due to uneven access patterns.. On-demand DynamoDB tables automatically scale capacity for the base table, but a GSI can throttle writes if its partition key creates hot partitions. The throttling on the base table occurs because the GSI write capacity is exceeded due to uneven access patterns. Options A, C, and D are incorrect because on-demand tables handle base table capacity scaling, hot partitions on the base table would cause throttling on the base table but the issue is with the GSI, and read capacity is not relevant given the write errors.

Answer

The base table's write capacity is insufficient for the workload.

Answer

The partition key design causes hot partitions in the base table.

Answer

The table's read capacity is too low for the read-heavy workload.

Question 14

A startup is building a mobile application that requires a database to store user preferences and session data. The data is accessed by user ID and requires single-digit millisecond latency. The workload is read-heavy with occasional writes. Which database service is MOST cost-effective?

Accepted Answer

Amazon DynamoDB with on-demand capacity. Amazon DynamoDB with on-demand capacity is the most cost-effective choice because it provides single-digit millisecond latency for key-value lookups by user ID, scales automatically to handle read-heavy workloads with occasional writes, and charges only for the reads and writes consumed, avoiding the cost of provisioning for peak capacity. The on-demand mode eliminates the need for capacity planning, making it ideal for unpredictable or variable traffic patterns typical of a startup's mobile application.

Answer

Amazon Aurora Serverless

Answer

Amazon ElastiCache for Memcached

Answer

Amazon RDS for MySQL with provisioned IOPS

Question 15

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 16

A company is migrating an on-premises Oracle database to Amazon Aurora PostgreSQL. The database contains a large table that is partitioned by date. The company wants to minimize downtime during migration and ensure compatibility. Which TWO actions should the company take?

Accepted Answer

Use AWS Database Migration Service (DMS) with ongoing replication to migrate the data.. AWS DMS with ongoing replication (change data capture) allows continuous synchronization from the source Oracle database to the target Aurora PostgreSQL, minimizing downtime by keeping the target nearly up-to-date until the final cutover. This approach supports large partitioned tables and reduces the migration window compared to a full load only.

Answer

Migrate the database using a full load only and accept downtime.

Answer

Use AWS Schema Conversion Tool (SCT) to convert the schema automatically without any manual adjustments.

Answer

Replace the Oracle database with Amazon RDS for MySQL.

Question 17

A company is designing a database for a global e-commerce platform that requires sub-millisecond read latencies from multiple AWS regions. The data is mostly read, with occasional writes. Which database solution meets these requirements?

Accepted Answer

Amazon DynamoDB with Global Tables.. Amazon DynamoDB with Global Tables is the correct choice because it provides a fully managed, multi-Region, multi-master database that replicates data across AWS Regions with sub-second latency, enabling sub-millisecond read latencies for a globally distributed, mostly-read workload. The occasional writes are handled efficiently by the multi-master design, which automatically resolves conflicts using last-writer-wins semantics, ensuring strong eventual consistency.

Answer

Amazon ElastiCache for Redis with global datastore.

Answer

Amazon Aurora MySQL with Aurora Global Database.

Answer

Amazon RDS for MySQL with Multi-AZ and read replicas.

Question 18

A company is using Amazon RDS for Oracle with a very large database (10 TB). They need to migrate to Amazon Aurora PostgreSQL with minimal downtime. The source database is heavily used with constant writes. Which migration strategy is most appropriate?

Accepted Answer

Use AWS Database Migration Service (DMS) with ongoing replication to migrate from Oracle to Aurora PostgreSQL.. AWS DMS with ongoing replication (change data capture) is the most appropriate strategy for migrating a heavily written 10 TB Oracle database to Aurora PostgreSQL with minimal downtime. DMS can perform a full load of the existing data and then continuously replicate changes from Oracle's redo logs to Aurora PostgreSQL, allowing the source to remain fully operational until a brief cutover window. This approach minimizes downtime compared to offline export/import methods and is natively supported by AWS.

Answer

Export the Oracle database using expdp and import into Aurora PostgreSQL using pg_restore.

Answer

Create a read replica of the RDS Oracle instance and promote it to an Aurora PostgreSQL instance.

Answer

Use Oracle GoldenGate to replicate data to an Aurora PostgreSQL instance.

Question 19

A financial services company needs to enforce row-level security on a MySQL database hosted on Amazon RDS. They want to restrict access so that each application user can only see their own data. Which approach should they take?

Accepted Answer

Use a MySQL proxy that injects session context variables and enable row-level security in the application queries. MySQL does not natively support row-level security (RLS) like PostgreSQL or SQL Server. Instead, you can implement RLS by using a MySQL proxy (e.g., ProxySQL, Amazon RDS Proxy) that injects session context variables (e.g., user_id) at connection time. Application queries then reference these variables in WHERE clauses (e.g., WHERE user_id = @@session.user_id), effectively restricting each user to their own data without modifying the underlying schema.

Answer

Place each user's data in a separate database and use VPC endpoints to isolate access

Answer

Create separate database views for each user

Answer

Use IAM database authentication and define fine-grained access policies

Question 20

A company is designing a database for a global IoT application that ingests millions of events per second. Each event includes a device ID, timestamp, and sensor readings. The requirement is to store data for historical analysis and to support queries that aggregate data by device ID over time ranges. The team needs a cost-effective solution that can scale write throughput. Which database design is most appropriate?

Accepted Answer

Use Amazon DynamoDB with a table keyed by device ID (partition) and timestamp (sort).. Amazon DynamoDB with a composite primary key of device ID (partition key) and timestamp (sort key) is ideal for this IoT workload because it provides scalable write throughput to handle millions of events per second, while the sort key enables efficient time-range queries and aggregation by device ID. DynamoDB's fully managed, serverless architecture ensures cost-effectiveness by automatically scaling capacity and charging only for consumed resources, making it suitable for high-velocity time-series data.

Answer

Use Amazon RDS for MySQL with Multi-AZ and auto-scaling storage.

Answer

Use Amazon Redshift with a schema optimized for time-series data.

Answer

Use Amazon ElastiCache for Redis with persistence enabled.