DBS-C01 Workload-Specific Database Design Practice Test 19 — 15 Questions

Question 1

A company is designing a document management system using Amazon DocumentDB. Each document is up to 10 MB. The application needs to retrieve multiple documents by their IDs in a single request. The IDs are known at query time. Which query pattern is most efficient?

Accepted Answer

Use a find operation with the $in operator on the _id field.. Option B is correct because $in operator allows a single query to fetch multiple documents by ID. Option A is wrong because scanning is inefficient. Option C is wrong because parallel queries increase overhead. Option D is wrong because $or is less efficient than $in for the same field.

Answer

Use a find operation with the $or operator on the _id field.

Answer

Use a scan operation with a filter on the _id field.

Answer

Issue multiple get operations in parallel.

Question 2

A social media application stores user posts in a DynamoDB table with a partition key of user_id and a sort key of timestamp. The most frequent query is to retrieve the 10 most recent posts for a given user. Which secondary index design would optimize this query?

Accepted Answer

Create an LSI with user_id as the partition key and timestamp as the sort key.. Option B is correct because a local secondary index (LSI) with the same partition key but a different sort key allows efficient retrieval of recent posts per user. Option A is wrong because a global secondary index (GSI) would require additional provisioned throughput and is unnecessary. Option C is wrong because using the sort key directly without an index still requires a scan. Option D is wrong because Elasticsearch adds operational complexity and cost for this simple query pattern.

Answer

Create a GSI with user_id as the partition key and timestamp as the sort key.

Answer

Use DynamoDB Streams to populate an Amazon Elasticsearch cluster for search queries.

Answer

Query the base table using the sort key timestamp with a limit of 10.

Question 3

A company runs an OLTP workload on an RDS for MySQL instance. The database has a table with 50 million rows. The application frequently runs queries that join this table with a small lookup table (1000 rows) using a foreign key. The queries are slow. Which design change would most improve performance?

Accepted Answer

Add an index on the foreign key column in the large table.. Option D is correct because proper indexing on the join column eliminates full table scans. Option A is wrong because increasing instance size is a vertical scaling approach that may help but is not as effective as indexing. Option B is wrong because read replicas distribute read traffic but do not speed up individual queries. Option C is wrong because partitioning can help with data management but not necessarily join performance.

Answer

Partition the large table by the foreign key column.

Answer

Scale up the RDS instance to a larger size.

Answer

Create a read replica and direct all read queries to it.

Question 4

A startup wants to store session data for a web application. Each session is small (under 1 KB) and accessed frequently with low latency. The data can be ephemeral and does not require complex queries. Which AWS database service is most suitable?

Accepted Answer

Amazon ElastiCache for Redis. Option A is correct because Amazon ElastiCache for Redis provides in-memory storage with low latency, perfect for session data. Option B is wrong because RDS is relational and overkill for simple key-value session data. Option C is wrong because DynamoDB is also suitable but for this use case, ElastiCache is simpler and faster. Option D is wrong because Neptune is a graph database, not appropriate for session storage.

Answer

Amazon DynamoDB

Answer

Amazon RDS for PostgreSQL

Answer

Amazon Neptune

Question 5

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).. Option D is correct because DynamoDB with a partition key of device ID and sort key of timestamp allows high write throughput and efficient time-range queries. Option A is wrong because RDS with auto-scaling cannot handle millions of events per second. Option B is wrong because Redshift is optimized for analytics but not for high-velocity writes. Option C is wrong because ElastiCache is in-memory and too expensive for historical storage.

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.

Question 6

A company runs a financial application that requires ACID transactions on a relational database. The workload has a high volume of writes and reads, and the team wants to minimize operational overhead. Which AWS database service should they choose?

Accepted Answer

Amazon Aurora (MySQL-compatible). Option C is correct because Amazon Aurora provides MySQL/PostgreSQL compatibility with ACID transactions and higher throughput than standard RDS, reducing overhead. Option A is wrong because DynamoDB is NoSQL and does not support ACID across multiple items by default. Option B is wrong because ElastiCache is in-memory and not ACID-compliant. Option D is wrong because RDS for Oracle requires licensing and more operational overhead compared to Aurora.

Answer

Amazon RDS for Oracle

Answer

Amazon DynamoDB with transactions enabled

Answer

Amazon ElastiCache for Memcached

Question 7

A gaming company wants to store player profiles and game state. The data is accessed via a REST API and must be highly available with single-digit millisecond latency. The schema is simple and may evolve over time. Which database should they use?

Accepted Answer

Amazon DynamoDB. Option A is correct because DynamoDB is a fully managed NoSQL database with consistent single-digit millisecond latency and flexible schema. Option B is wrong because RDS is relational and adds latency for simple lookups. Option C is wrong because Redshift is for analytics. Option D is wrong because S3 is object storage, not designed for low-latency updates.

Answer

Amazon S3

Answer

Amazon RDS for PostgreSQL

Answer

Amazon Redshift

Question 8

A company has a multi-player game that uses DynamoDB to store game state. The access pattern is write-heavy, and the game state for each active game session is updated frequently. The team notices throttling on the table during peak hours. The table has a partition key of game_id and no sort key. What design change would best reduce throttling?

Accepted Answer

Use a composite key with a random suffix on the partition key.. Option D is correct because using a write sharding pattern with a suffix distributes writes across partitions, avoiding hot spots. Option A is wrong because increasing read capacity does not help write throttling. Option B is wrong because DynamoDB Accelerator (DAX) only caches reads. Option C is wrong because global tables replicate data, not reduce throttling.

Answer

Enable DynamoDB global tables.

Answer

Enable DynamoDB Accelerator (DAX) for the table.

Answer

Increase the provisioned read capacity units (RCU).

Question 9

A company is migrating an on-premises Oracle data warehouse to AWS. The warehouse contains 50 TB of data and runs complex queries that involve joins and aggregations. The team wants to minimize migration effort and cost while maintaining query performance. Which AWS service should they use?

Accepted Answer

Amazon Redshift. Option C is correct because Amazon Redshift is a fully managed petabyte-scale data warehouse optimized for complex queries. Option A is wrong because RDS is for OLTP, not OLAP. Option B is wrong because ElastiCache is in-memory caching, not a data warehouse. Option D is wrong because DynamoDB is NoSQL and not suited for complex joins.

Answer

Amazon RDS for Oracle

Answer

Amazon ElastiCache for Redis

Answer

Amazon DynamoDB

Question 10

A company needs to store and query JSON documents that have varying attributes. The workload is read-heavy, and the team wants to use SQL-like queries. Which service is most appropriate?

Accepted Answer

Amazon DocumentDB (with MongoDB compatibility). Option B is correct because Amazon DocumentDB (with MongoDB compatibility) stores JSON documents natively and supports MongoDB-like queries. Option A is wrong because DynamoDB is key-value, not optimized for rich JSON queries. Option C is wrong because RDS requires a fixed schema. Option D is wrong because Neptune is a graph database.

Answer

Amazon Neptune

Answer

Amazon DynamoDB with PartiQL

Answer

Amazon RDS for MySQL with JSON data type

Question 11

Which TWO factors should you consider when choosing between Amazon RDS and Amazon DynamoDB for a new application?

Accepted Answer

RDS requires a predefined schema, while DynamoDB is schema-less.. Option B is correct because DynamoDB uses a NoSQL model, while RDS uses relational. Option E is correct because DynamoDB supports flexible schema, while RDS requires fixed schema. Option A is wrong because both support encryption. Option C is wrong because both support VPC. Option D is wrong because both support multi-AZ deployments (RDS Multi-AZ, DynamoDB global tables).

Answer

DynamoDB can only be accessed from within a VPC, while RDS can be public.

Answer

Only RDS supports Multi-AZ deployments for high availability.

Answer

Both services support encryption at rest and in transit.

Question 12

Which THREE design patterns are commonly used to optimize DynamoDB performance for write-heavy workloads?

Accepted Answer

Using DynamoDB adaptive capacity to handle unbalanced access patterns.. Option A is correct because write sharding distributes writes evenly. Option C is correct because batching reduces API calls. Option E is correct because adaptive capacity helps handle uneven access patterns. Option B is wrong because global tables are for multi-region replication, not write optimization. Option D is wrong because sparse indexes are for read optimization.

Answer

Using sparse indexes on rarely accessed attributes.

Answer

Using global tables to distribute writes across regions.

Question 13

Which TWO of the following are advantages of using Amazon Aurora over standard RDS for MySQL?

Accepted Answer

Aurora can deliver up to 5x the throughput of standard MySQL on the same hardware.. Option C is correct because Amazon Aurora uses a distributed, SSD-backed storage subsystem that separates compute from storage, enabling it to deliver up to 5x the throughput of standard MySQL running on the same hardware. This performance gain comes from the Aurora storage engine's ability to reduce I/O operations and parallelize writes across multiple storage nodes.

Answer

Aurora automatically fails over to a read replica in case of primary failure.

Answer

Aurora is compatible with PostgreSQL, so you can migrate from SQL Server easily.

Answer

Aurora supports up to 15 read replicas, while RDS for MySQL only supports 5.

Question 14

A company is designing a database for an e-commerce platform that stores product catalog data. The catalog has frequent reads and occasional writes. The data is highly relational but the team wants the lowest possible latency for read queries. Which database service should they choose?

Accepted Answer

Amazon DynamoDB with DAX. DynamoDB Accelerator (DAX) is an in-memory cache for DynamoDB that provides microsecond read latency. While DynamoDB itself is NoSQL, DAX is used to speed up reads. RDS with read replicas can improve read performance but not to microsecond level. ElastiCache could be used but requires more application logic. DocumentDB is a document database not optimized for microsecond reads.

Answer

Amazon DocumentDB

Answer

Amazon RDS for PostgreSQL with read replicas

Answer

Amazon ElastiCache for Redis

Question 15

A financial services company runs a core banking application on Amazon RDS for MySQL. They need to maintain a full audit trail of all changes to customer account balances for regulatory compliance. The audit trail must be immutable and queryable for up to 7 years. Which solution meets these requirements with minimal impact on the source database?

Accepted Answer

Migrate to Amazon Aurora MySQL and enable database activity streams, streaming to Amazon Kinesis Data Streams and then to Amazon S3. Amazon Aurora MySQL with database activity streams captures a near real-time feed of database activity and can be streamed to Amazon Kinesis Data Streams for analysis. This provides an immutable audit log. Option A uses binary logs which are not immutable and have limited retention. Option B is not immutable. Option D uses DynamoDB Streams but the source is RDS MySQL, not DynamoDB.

Answer

Use Amazon RDS Performance Insights to capture SQL queries and store them in Amazon S3

Answer

Use Amazon DynamoDB Streams with a Lambda function to capture changes from the MySQL database

Answer

Enable binary logging on the RDS instance and stream the binlog to Amazon S3 using AWS Database Migration Service (DMS)