DBS-C01 Practice Test 26 — 15 Questions

Question 1

A startup is building a real-time analytics dashboard on AWS. The data arrives as time-series events from IoT devices at a rate of 10,000 writes per second. Each event is approximately 1 KB. The dashboard requires sub-second query latency for the last hour of data and must support ad-hoc analytical queries on historical data spanning months. The team needs to design a cost-effective database solution. Which combination of AWS services should be used?

Accepted Answer

Amazon DynamoDB with DynamoDB Accelerator (DAX) for real-time queries, and Amazon S3 with Amazon Athena for historical analytics.. Option A is correct because DynamoDB Accelerator (DAX) provides sub-second read latency for hot data, while Amazon S3 with Athena supports ad-hoc queries on historical data cost-effectively. Option B is wrong because Amazon Redshift is optimized for complex analytics but not for sub-second real-time queries. Option C is wrong because ElastiCache for Redis alone cannot handle the high write throughput and is not designed for analytics. Option D is wrong because Amazon RDS for PostgreSQL with read replicas is not designed for 10,000 writes per second and querying historical data would be expensive and slow.

Answer

Amazon ElastiCache for Redis for real-time queries, and Amazon OpenSearch Service for historical analytics.

Answer

Amazon Redshift for both real-time and historical queries, using auto-scaling and materialized views.

Answer

Amazon RDS for PostgreSQL with read replicas for real-time queries, and Amazon Redshift for historical analytics.

Question 2

A company is migrating an on-premises MongoDB database to Amazon DocumentDB. The current MongoDB workload uses aggregation pipelines with the $lookup stage and geospatial queries. The migration tool reports that some aggregation stages are not supported. Which THREE actions should the company take to address the incompatibilities?

Accepted Answer

Use $geoNear for geospatial queries as it is supported in DocumentDB.. Option A (rewrite $lookup as application-side joins) is correct because DocumentDB does not support $lookup. Option B (use $geoWithin operator) is correct because DocumentDB supports it. Option C (use $geoNear for geospatial) is correct because DocumentDB supports $geoNear. Option D is wrong because $graphLookup is not supported. Option E is wrong because storing pre-joined documents can be an alternative for $lookup but is not a direct action for unsupported stages.

Answer

Replace $lookup with $geoWithin for location-based queries.

Answer

Convert $graphLookup to use recursive queries in DocumentDB.

Question 3

A company needs to store session state for a web application that runs on Amazon EC2 instances behind an Application Load Balancer. The session data is small (less than 1 KB per user) and must be highly available with low latency. Which AWS database service is best for this use case?

Accepted Answer

Amazon ElastiCache for Redis. Amazon ElastiCache for Redis is ideal for storing session state because it is an in-memory key-value store with low latency and supports features like TTL and replication for high availability. Option B (DynamoDB) is wrong because it is not as fast for session state and is more expensive for small data. Option C (RDS) is wrong because it is a relational database with higher latency. Option D (S3) is wrong because it is object storage with higher latency.

Answer

Amazon S3

Answer

Amazon DynamoDB

Answer

Amazon RDS for MySQL

Question 4

A company runs a MongoDB-compatible workload on Amazon DocumentDB. They notice that many read requests are returning stale data even though reads are directed to the primary instance. What is the MOST likely cause?

Accepted Answer

The application is using a read preference that allows secondary reads.. DocumentDB uses a distributed storage volume with six copies across three Availability Zones. Reads from the primary are strongly consistent by default. However, if the application uses read preferences that allow secondary reads (e.g., 'secondaryPreferred'), then reads may go to replicas which are eventually consistent. The question implies reads are directed to primary, but if the application uses 'secondaryPreferred' and the primary is unavailable, reads may go to secondary. Alternatively, if the application uses a read preference that does not require primary, stale reads can occur. Option D addresses the most common cause: read preference set to allow secondary reads.

Answer

The application's session is pinned to a secondary replica despite requesting the primary.

Answer

The primary instance is experiencing high CPU utilization, causing delayed writes.

Answer

The storage volume is using the default eventually consistent configuration for primary reads.

Question 5

A company is designing a database for a social media analytics platform that requires: 1) storing relationships between users, posts, and interests; 2) running complex graph queries like 'find all friends of friends who like topic X'; 3) high availability with multi-region replication. Which TWO AWS services should they consider? (Choose TWO.)

Accepted Answer

Amazon Neptune. Option B (Neptune) is correct for graph queries. Option D (Global Database for Aurora) provides multi-region replication for relational data, but for graph queries Neptune is primary. Since Neptune does not natively support multi-region replication, the platform might use Aurora for metadata and Neptune for graph, but the question expects two services. Alternatively, DynamoDB Global Tables for key-value and Neptune for graph. However, given options, B and D are the best combined for graph and replication. Option A (DynamoDB) is not graph. Option C (Redshift) is analytics. Option E (ElastiCache) is caching.

Answer

Amazon Redshift

Answer

Amazon DynamoDB with Global Tables

Answer

Amazon ElastiCache for Redis

Question 6

A company is migrating an on-premises MySQL database to Amazon RDS for MySQL. They need to validate that the schema is compatible. Which AWS service should they use?

Accepted Answer

AWS Schema Conversion Tool (SCT). AWS SCT can assess and convert schemas for compatibility. AWS DMS is for data migration. Amazon Inspector is for security. AWS Trusted Advisor is for best practices.

Answer

Amazon Inspector

Answer

AWS Database Migration Service (DMS)

Answer

AWS Trusted Advisor

Question 7

A company is migrating an on-premises Oracle OLTP database to Amazon Aurora PostgreSQL. The database has a complex schema with stored procedures, triggers, and sequences. During the migration, the team notices that the conversion tool reports several incompatibilities. Which strategy should the team use to handle the database schema changes with minimal downtime?

Accepted Answer

Use AWS Database Migration Service (DMS) with the AWS Schema Conversion Tool (SCT) to convert the schema and migrate data, then handle remaining incompatibilities during a cutover window.. Option B is correct because AWS DMS can handle ongoing replication after initial load, and the AWS Schema Conversion Tool (SCT) can convert schema. Option A is wrong because converting manually is error-prone and time-consuming. Option C is wrong because Babelfish is for SQL Server, not Oracle. Option D is wrong because writing a custom script is not recommended given available tools.

Answer

Deploy Amazon RDS for PostgreSQL with Babelfish to run Oracle PL/SQL code natively.

Answer

Use pg_dump and pg_restore to migrate the schema, and then test and fix any errors.

Answer

Manually rewrite all stored procedures and triggers to PostgreSQL syntax before migration.

Question 8

A company is selecting a database for a time-series application that collects sensor data from thousands of devices. The data is written at a high velocity (millions of data points per second). The application needs to query recent data (last hour) with sub-second latency and perform long-term analysis on months of data. Which TWO AWS database services best meet these requirements?

Accepted Answer

Amazon Timestream for both real-time and historical queries.. Option A (Timestream) is built for time-series data with fast queries. Option D (DynamoDB with TTL) can handle high write throughput and automatically expire old data to S3 for analysis. Option B is wrong because Redshift is not designed for sub-second real-time queries. Option C is wrong because ElastiCache is primarily a cache. Option E is wrong because QLDB is for ledger data.

Answer

Amazon ElastiCache for Redis with Time Series module.

Answer

Amazon Redshift for real-time queries and historical analysis.

Answer

Amazon Quantum Ledger Database (QLDB) for immutable time-series records.

Question 9

A company is designing a database for a global e-commerce platform that requires low-latency reads and writes from multiple AWS regions. The data must be strongly consistent within a region but can be eventually consistent across regions. Which TWO services should the company consider?

Accepted Answer

Amazon DynamoDB Global Tables. DynamoDB Global Tables provides multi-region replication with eventual consistency across regions and strong consistency within a region. Aurora Global Database also provides low-latency reads across regions and can be configured for cross-region replication. Option C (Redshift) is wrong because it is not designed for multi-region active-active workloads. Option D (ElastiCache Global Datastore) is wrong because it is for Redis and provides cross-region replication but with eventual consistency and is not a primary database. Option E (RDS Cross-Region Read Replicas) is wrong because they are read-only and do not support writes from multiple regions.

Answer

Amazon ElastiCache for Redis Global Datastore

Answer

Amazon RDS Cross-Region Read Replicas

Answer

Amazon Redshift

Question 10

A company runs a critical PostgreSQL database on Amazon RDS Multi-AZ. They need to perform a major version upgrade (e.g., from 12 to 13) with minimal downtime. Which approach should they take?

Accepted Answer

Create a read replica of the DB instance, perform the major version upgrade on the replica, then promote the replica to a new primary and update the connection string.. RDS supports major version upgrades, but they require a brief downtime while the upgrade is applied. The recommended approach to minimize downtime is to create a read replica, upgrade the replica, promote it to a standalone instance, and then switch over. This way, the upgrade happens on the replica while the primary continues to serve traffic. Option A describes this correctly. Option B is the standard upgrade but incurs downtime. Option C is not supported (can't upgrade Multi-AZ without downtime). Option D suggests modifying the DB instance to Single-AZ, upgrading, then converting back to Multi-AZ, which also incurs downtime.

Answer

Take a snapshot, restore as a new instance with the upgraded engine version, and redirect traffic.

Answer

Initiate a major version upgrade directly on the Multi-AZ instance; the upgrade will be applied during the next maintenance window with minimal downtime.

Answer

Modify the DB instance to disable Multi-AZ, perform the upgrade, then re-enable Multi-AZ.

Question 11

A company is building a real-time leaderboard for an online game using Amazon DynamoDB. The leaderboard must update scores within seconds and support queries for top 100 players. Which TWO design patterns should be used? (Choose TWO.)

Accepted Answer

Use DynamoDB Streams to trigger a Lambda function that updates a separate leaderboard table.. Option A (DynamoDB Streams + Lambda) enables real-time updates. Option D (DAX) provides low-latency read caching for the leaderboard. Option B (GSI) could help but not for real-time top-N. Option C (ElastiCache) is an alternative but not DynamoDB-native. Option E (Sort key on score) is a good design but not a separate pattern; it's part of table design.

Answer

Create a global secondary index on the score attribute for efficient range queries.

Answer

Store the leaderboard in Amazon ElastiCache for Redis for low-latency reads.

Answer

Set the sort key to the score attribute for natural ordering.

Question 12

A company uses Amazon DynamoDB to store application logs. The logs have a TTL of 7 days. The operations team needs to run ad-hoc analytical queries on logs older than 7 days, which are automatically deleted by TTL. Which solution should the team implement to retain and analyze old logs?

Accepted Answer

Use DynamoDB Streams to export logs to Amazon S3 and query with Amazon Athena.. Option D is correct because DynamoDB Streams captures old images before TTL deletion, and Lambda can write them to S3 for analysis with Athena. Option A is wrong because DynamoDB cannot be queried by Athena directly. Option B is wrong because disabling TTL would increase costs. Option C is wrong because exporting to S3 is not automatic via streams.

Answer

Disable TTL and use a scheduled Lambda function to archive logs to Amazon S3.

Answer

Increase the TTL to 30 days and query the logs directly in DynamoDB.

Answer

Use AWS Glue to crawl DynamoDB tables and create a data catalog for Athena queries.

Question 13

A financial services company needs to store trade data with strong consistency, high durability, and the ability to run complex SQL queries on the data. The data volume is 10 TB and grows by 1 GB per day. Queries must return results in less than 5 seconds. Which database solution best meets these requirements?

Accepted Answer

Amazon Aurora. Amazon Aurora is a MySQL/PostgreSQL-compatible relational database that provides strong consistency, high durability (6 copies across 3 AZs), and supports complex SQL queries. Option B (DynamoDB) is wrong because it does not natively support complex SQL queries (though PartiQL exists, it's not as powerful). Option C (Redshift) is wrong because it is optimized for data warehousing and may have higher latency for single-row operations. Option D (DocumentDB) is wrong because it is MongoDB-compatible and not as strong on complex SQL joins.

Answer

Amazon DynamoDB

Answer

Amazon DocumentDB

Answer

Amazon Redshift

Question 14

A startup is building a mobile app backend using Amazon DynamoDB. They anticipate unpredictable traffic spikes. Which DynamoDB feature should they use to handle the spikes without manual intervention?

Accepted Answer

Enable DynamoDB Auto Scaling for read and write capacity.. DynamoDB Auto Scaling adjusts provisioned throughput based on actual traffic, using CloudWatch alarms. This handles spikes automatically. On-Demand capacity mode is another option that handles spikes automatically but can be more expensive for predictable workloads. However, the question asks for a feature to handle unpredictable spikes. Auto Scaling is the traditional approach. On-Demand is also valid but the question may expect Auto Scaling as the classic answer. But to be precise, On-Demand is designed for unpredictable traffic. However, the options: A: Auto Scaling, B: DAX, C: Global Tables, D: TTL. Auto Scaling is the most direct answer.

Answer

Use DynamoDB Accelerator (DAX) as a cache layer.

Answer

Set up a TTL (Time to Live) to automatically expire old items.

Answer

Implement DynamoDB Global Tables for multi-region replication.

Question 15

A startup is building a mobile app backend with user profiles and social features. They need a database that can handle flexible schemas, high read throughput for user profiles, and strong consistency for friend requests. Which database service should they choose?

Accepted Answer

Amazon DynamoDB. Option C is correct because Amazon DynamoDB offers flexible schema, high throughput, and optional strong consistency. Option A (RDS MySQL) is relational with fixed schema. Option B (Neptune) is graph-dedicated. Option D (DocumentDB) is MongoDB-compatible but not as optimized for consistent low-latency reads across a wide range of access patterns.

Answer

Amazon RDS for MySQL

Answer

Amazon Neptune

Answer

Amazon DocumentDB