DBS-C01 Workload-Specific Database Design Practice Test 27 — 15 Questions

Question 1

A gaming company uses Amazon DynamoDB to store player profiles. Each profile is about 5 KB and is accessed frequently. The access pattern is mostly point reads by player ID. The company wants to reduce read costs while maintaining low latency. Currently, the table uses provisioned capacity with 3000 RCU. Which change would be MOST effective?

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

Accepted Answer

Use DynamoDB Accelerator (DAX) to cache frequently accessed items.. DynamoDB Accelerator (DAX) provides an in-memory cache that can serve frequently accessed items (like player profiles) with microsecond latency, reducing the number of read requests that hit the underlying table. Since each profile is 5 KB and accessed via point reads, DAX can absorb a significant portion of the read traffic, allowing you to lower provisioned RCU without sacrificing performance. This directly reduces read costs while maintaining low latency, making it the most effective solution.

Answer

Use strongly consistent reads instead of eventually consistent reads.

Answer

Switch from provisioned capacity to on-demand capacity mode.

Answer

Decrease the provisioned RCU to 2000 and rely on adaptive capacity.

Question 2

A company uses Amazon Aurora MySQL for its customer relationship management (CRM) system. The database has a table "contacts" with millions of rows. The application frequently searches for contacts by email address. The email column has a B-tree index. The DBA notices that queries are still slow, and the EXPLAIN plan shows index scans but not index-only scans. What is the most likely cause?

Accepted Answer

The query selects columns not included in the index, requiring table lookups.. An index-only scan requires that all columns referenced in the query (both in the SELECT list and WHERE clause) be present in the index. Since the query selects columns not included in the B-tree index on the email column, Aurora MySQL must perform additional table lookups (row fetches) to retrieve those missing columns, resulting in an index scan rather than an index-only scan.

Answer

The index is a composite index on (email, phone) and the query selects only email.

Answer

The index has low cardinality.

Answer

The index type is not suitable for equality searches.

Question 3

A company is designing a document database for a content management system using Amazon DocumentDB. The application requires high availability and low-latency reads across multiple AWS Regions. Which TWO design choices meet these requirements?

Accepted Answer

Configure read replicas in each region to offload read traffic.. Amazon DocumentDB read replicas can be placed in different AWS Regions to offload read traffic and provide low-latency reads locally. Option D is correct because a global cluster in DocumentDB replicates data from a primary region to secondary regions, enabling high availability and low-latency reads across regions.

Answer

Use a single instance in each region with Multi-AZ disabled.

Answer

Use local secondary indexes to improve query performance in each region.

Answer

Shard the data across multiple clusters in different regions.

Question 4

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.. DocumentDB supports the $geoNear aggregation stage for geospatial queries, making option B a valid action to address incompatibilities. The migration tool flagged unsupported stages, and $geoNear is explicitly supported in DocumentDB for location-based queries, whereas $geoWithin is not available in aggregation pipelines.

Answer

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

Answer

Convert $graphLookup to use recursive queries in DocumentDB.

Question 5

A company is designing a database for a real-time leaderboard in a mobile game. The leaderboard updates thousands of times per second and must return the top 100 scores with minimal latency. Which AWS database service is most suitable for this workload?

Accepted Answer

Amazon ElastiCache for Redis. Amazon ElastiCache for Redis is the most suitable choice because Redis provides an in-memory data structure server with a Sorted Set data type (ZADD and ZRANGE commands) that natively supports real-time leaderboard operations. It can handle thousands of writes per second with sub-millisecond latency and efficiently retrieve the top 100 scores using ZREVRANGE with a time complexity of O(log(N)+M), where M is the number of returned elements.

Answer

Amazon Neptune

Answer

Amazon DynamoDB

Answer

Amazon Aurora

Question 6

A company runs a MySQL-compatible database on Amazon RDS with a 3 TB dataset. They need to run complex analytical queries that involve joins and aggregations on millions of rows. The current RDS instance is a db.r5.8xlarge with 32 vCPUs and 256 GB RAM, but complex queries take over an hour. Which design change would most improve query performance for this workload?

Accepted Answer

Use Amazon Redshift for the analytical workload. Amazon Redshift is a fully managed, petabyte-scale data warehouse service optimized for complex analytical queries involving joins and aggregations on large datasets. Unlike RDS, which is designed for OLTP workloads, Redshift uses columnar storage, massively parallel processing (MPP), and automatic compression to dramatically reduce query times for analytical workloads. Migrating the analytical workload to Redshift offloads the heavy processing from the RDS instance, allowing it to continue serving transactional queries efficiently.

Answer

Migrate to Amazon Aurora with parallel query

Answer

Add an Amazon ElastiCache cluster to cache query results

Answer

Enable DynamoDB Accelerator (DAX) on the RDS instance

Question 7

A company is building a document management system where each document can have multiple tags and users need to query documents by any combination of tags. The number of tags per document is up to 20, and the total number of documents is expected to be 50 million. Which database design is most appropriate for this flexible tag-based querying?

Accepted Answer

Amazon DynamoDB with a global secondary index on the tag attribute. Amazon DynamoDB with a global secondary index on the tag attribute is the most appropriate design because it supports flexible, low-latency queries on any combination of tags at scale. DynamoDB's single-table design with a GSI allows you to query documents by a specific tag efficiently, and by using composite sort keys or multiple GSIs, you can support queries on multiple tag combinations without the overhead of joins or schema normalization. This approach handles 50 million documents with up to 20 tags per document while maintaining predictable performance.

Answer

Amazon RDS for MySQL with a normalized schema

Answer

Amazon Neptune

Answer

Amazon ElastiCache for Memcached

Question 8

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 the correct choice because it is a fully relational, ACID-compliant database that provides strong consistency, high durability (6-way replication across 3 AZs), and supports complex SQL queries. With 10 TB of data and 1 GB/day growth, Aurora can scale storage automatically up to 128 TB and, using features like Aurora Serverless or provisioned instances with read replicas, can achieve sub-5-second query performance for complex analytical queries when properly indexed and optimized.

Answer

Amazon DynamoDB

Answer

Amazon DocumentDB

Answer

Amazon Redshift

Question 9

A company has a high-traffic e-commerce application that uses Amazon RDS for MySQL. During flash sales, the database experiences high read load causing slow page loads. The application is read-heavy with occasional writes. Which design change would provide the most immediate performance improvement?

Accepted Answer

Create read replicas of the RDS instance. Creating read replicas of the RDS instance offloads SELECT queries from the primary database, directly addressing the high read load during flash sales. Read replicas are asynchronous copies that can serve read traffic, reducing the burden on the primary instance and improving page load times for read-heavy workloads.

Answer

Add an Amazon ElastiCache layer

Answer

Enable Multi-AZ deployment

Answer

Upgrade to a larger instance type

Question 10

A startup is building a social media application that needs to store user profiles, posts, comments, and likes. The data is highly interconnected, and the team wants to query relationships efficiently, such as 'find all friends of a user who liked a post'. Which database service is best suited for this workload?

Accepted Answer

Amazon Neptune. Amazon Neptune is a fully managed graph database service optimized for highly interconnected data. It supports property graph and RDF models, enabling efficient traversal of relationships such as 'find all friends of a user who liked a post' using Gremlin or SPARQL queries. This makes it the ideal choice for social media applications requiring real-time relationship queries.

Answer

Amazon ElastiCache for Redis

Answer

Amazon DynamoDB

Answer

Amazon RDS for PostgreSQL

Question 11

A company uses Amazon DynamoDB to store IoT sensor data. Each sensor writes a record every second, and the application needs to query the last 24 hours of data for a specific sensor. The query must be very fast. Which table design and query pattern will minimize cost and latency?

Accepted Answer

Use a composite primary key: partition key = sensor ID, sort key = timestamp. Using a composite primary key with partition key = sensor ID and sort key = timestamp allows DynamoDB to efficiently query all items for a specific sensor in a single partition, using the Query API with a sort key condition on timestamp. This design ensures fast, targeted reads without scanning, minimizing read capacity units and latency.

Answer

Use a simple primary key (sensor ID) and scan the table filtering by timestamp

Answer

Use a composite primary key: partition key = timestamp, sort key = sensor ID

Answer

Use a simple primary key (sensor ID) and a global secondary index on timestamp

Question 12

A company is migrating an on-premises Oracle database to AWS. The database is 5 TB and supports a critical OLTP application with high transaction rates. The application requires stored procedures, triggers, and strong consistency. Which AWS database service is most appropriate with minimal application changes?

Accepted Answer

Amazon RDS for Oracle. Amazon RDS for Oracle is the most appropriate choice because it provides native Oracle compatibility, supporting stored procedures, triggers, and strong consistency with minimal application changes. The company can use Oracle's PL/SQL code directly, and RDS for Oracle offers full ACID compliance for OLTP workloads, avoiding the need to rewrite application logic or adapt to a different consistency model.

Answer

Amazon Aurora PostgreSQL

Answer

Amazon DynamoDB

Answer

Amazon Redshift

Question 13

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 the best choice because it provides an in-memory data store with sub-millisecond latency, ideal for storing small session state data (less than 1 KB per user). Redis supports key-value operations with built-in data expiration (TTL), making it perfect for session management. Its replication and automatic failover capabilities ensure high availability, meeting the application's requirements.

Answer

Amazon S3

Answer

Amazon DynamoDB

Answer

Amazon RDS for MySQL

Question 14

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. Amazon DynamoDB Global Tables is correct because it provides a fully managed, multi-region, multi-active database solution that delivers low-latency reads and writes to globally distributed applications. It uses DynamoDB Streams to replicate data across regions with eventual consistency, meeting the requirement for strong consistency within a region and eventual consistency across regions.

Answer

Amazon ElastiCache for Redis Global Datastore

Answer

Amazon RDS Cross-Region Read Replicas

Answer

Amazon Redshift

Question 15

A company is moving a large-scale time-series application from Cassandra to a managed AWS service. The workload involves high-frequency writes (millions per second) and queries that aggregate data over time windows. Which THREE AWS services are suitable for this time-series workload?

Accepted Answer

Amazon OpenSearch Service. Amazon OpenSearch Service is suitable because it supports high-frequency writes via bulk indexing and provides powerful aggregation queries (e.g., date histograms, percentiles) over time windows, making it ideal for time-series analytics. It can ingest millions of events per second when properly scaled with optimized shard strategies and using the OpenSearch ingest pipeline.

Answer

Amazon Aurora

Answer

Amazon Redshift