DBS-C01 Practice Test 24 — 15 Questions

Question 1

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.. Option D is correct because if the index does not include all columns needed (like phone), the database must fetch rows from the table. Option A is wrong because composite indexes on email and phone would help if queries used both, but not for email-only. Option B is wrong because B-tree indexes are suitable for equality. Option C is wrong because cardinality is likely high enough.

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 2

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 sensor ID as partition key and timestamp as sort key allows efficient querying of latest data with a Query operation on the partition key and a sort key condition. Option B (GSI on timestamp) is wrong because it would be less efficient for querying a specific sensor. Option C (scan) is wrong because it is expensive and slow. Option D (LSI on timestamp) is wrong because the sort key can be used directly without an LSI.

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 3

A company is migrating an on-premises Oracle database to Amazon Aurora PostgreSQL. The database is 2 TB and has a daily change rate of 10%. They have a 1 Gbps network connection to AWS. They want to minimize downtime during the migration. Which migration approach should they use?

Accepted Answer

Use AWS Database Migration Service (DMS) with ongoing replication. AWS DMS can perform continuous replication from Oracle to Aurora PostgreSQL with minimal downtime. Option A is wrong because pg_dump/restore would require a long downtime for the initial load and catch-up. Option B is wrong because an Aurora read replica cannot be created from an external Oracle database. Option D is wrong because the Schema Conversion Tool (SCT) is for schema conversion, not data migration.

Answer

Use AWS Schema Conversion Tool (SCT) to convert schema, then import data

Answer

Use pg_dump to export the database and pg_restore to import

Answer

Create an Aurora read replica from the Oracle database

Question 4

A social media company stores user posts in a database. Each post has a unique ID, content, and timestamp. The application frequently queries posts by user ID and also needs to support a global feed sorted by timestamp. Which database design is most efficient?

Accepted Answer

Amazon DynamoDB with user_id as partition key and timestamp as sort key, plus a GSI on timestamp. Amazon DynamoDB with a composite primary key (partition key on user_id, sort key on timestamp) allows efficient querying of a user's posts, and a GSI on (timestamp) can support the global feed. Option A (RDS) may become slow with large datasets. Option C (single table scan) is inefficient. Option D (S3) is not suitable for real-time queries.

Answer

Amazon DynamoDB with a single table and scan operation for the global feed

Answer

Amazon S3 with a metadata index in DynamoDB

Answer

Amazon RDS for PostgreSQL with indexes on user_id and timestamp

Question 5

A gaming company wants to store player profiles and game state data with low-latency access for millions of concurrent users. The data is accessed via a REST API and requires high scalability with minimal operational overhead. Which database service is MOST suitable?

Accepted Answer

Amazon DynamoDB. Option C is correct because DynamoDB is a fully managed NoSQL database that provides single-digit millisecond latency at any scale, ideal for gaming profiles. Option A is wrong because RDS is relational and may not scale as easily. Option B is wrong because ElastiCache is a cache, not a primary database. Option D is wrong because Neptune is for graph data.

Answer

Amazon RDS for MySQL with read replicas

Answer

Amazon Neptune

Answer

Amazon ElastiCache for Redis

Question 6

A developer runs the command shown and gets the output. Which conclusion can be drawn about the database configuration?

Accepted Answer

The database is a read replica of another instance. Option B is correct: the ReadReplicaSourceDBInstanceIdentifier field shows that this instance is a read replica of 'mydb-read-replica', meaning it is not the primary. Option A is wrong because the MultiAZ field is true for this instance, but it is a replica. Option C is wrong because the replica is in Multi-AZ, but it is still a read replica. Option D is wrong because the engine is mysql.

Answer

The database is a Multi-AZ read replica

Answer

The database engine is Aurora MySQL

Answer

The database is a primary instance in a Multi-AZ deployment

Question 7

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.. Option A (global cluster) provides multi-region replication with low-latency reads. Option D (read replicas) enhances read capacity. Option B is wrong because one instance per region doesn't provide high availability. Option C is wrong because sharding is not native in DocumentDB. Option E is wrong because local secondary indexes don't help cross-region.

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 8

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 direct migration path with minimal changes because it is fully compatible with Oracle and supports stored procedures, triggers, and strong consistency. Option A (Aurora PostgreSQL) is wrong because it requires converting Oracle-specific features to PostgreSQL. Option C (DynamoDB) is wrong because it does not support stored procedures or triggers natively (except for DynamoDB Streams and Lambda). Option D (Redshift) is wrong because it is a data warehouse, not for OLTP.

Answer

Amazon Aurora PostgreSQL

Answer

Amazon DynamoDB

Answer

Amazon Redshift

Question 9

A company wants to migrate their on-premises Oracle database to Amazon RDS for Oracle. They have a complex data loading process that uses Oracle Data Pump. Which migration approach is MOST efficient and minimizes downtime?

Accepted Answer

Use AWS Database Migration Service (DMS) with ongoing replication from the source Oracle database.. AWS DMS can perform a one-time full load followed by ongoing replication using Oracle LogMiner or binary reader. This minimizes downtime because after the full load, DMS continuously applies changes from the source. Data Pump export/import requires downtime. SCT is used for schema conversion, not data movement. Backup and restore also requires downtime.

Answer

Use AWS Schema Conversion Tool (SCT) to convert the schema and then copy data files directly.

Answer

Take a physical backup of the on-premises database and restore to RDS.

Answer

Export data using Oracle Data Pump and import into RDS.

Question 10

Refer to the exhibit. A developer runs a DynamoDB query against a global secondary index. The index's partition key is 'status' and sort key is 'created_at'. There are many items with status 'PENDING' in the table. Why does the query return zero items?

Accepted Answer

The global secondary index is not yet backfilled with data from the base table.. The query uses the index's partition key 'status' but does not specify a sort key condition. The index's sort key is 'created_at'. The query should return items with status 'PENDING' sorted by 'created_at'. However, the response shows 0 items but consumed 0.5 capacity units, indicating the index exists but no items matched. This could happen if the index is not yet backfilled (if recently created) or if the index's partition key attribute is missing in the items. In DynamoDB, GSI items are only written if the attribute exists. If items have a 'status' attribute set to 'PENDING', they should appear. The most likely cause is that the index is not fully populated yet (if recently created) or the 'status' attribute is missing in the items. The query syntax looks correct. Option A (incorrect expression) is unlikely. Option B (missing sort key) is not required for query on partition key only. Option C (index not yet backfilled) is plausible. Option D (using table name instead of index name) is incorrect because the query specifies --index-name. So C is correct.

Answer

The query is incorrectly targeting the base table instead of the index.

Answer

The query must include a condition on the sort key to return results.

Answer

The key-condition-expression uses the wrong attribute name placeholder.

Question 11

A startup is building a mobile application that needs to store user profiles and preferences. The data is schema-less and will grow rapidly. The application requires single-digit millisecond latency for reads and writes. Which AWS database should they choose?

Accepted Answer

Amazon DynamoDB. Amazon DynamoDB is a fully managed NoSQL database designed for low-latency, schema-less data at any scale. Option A (Aurora) is relational and requires predefined schema. Option C (Redshift) is for analytics. Option D (RDS SQL Server) is relational and not optimized for rapid scaling of schema-less data.

Answer

Amazon Aurora (MySQL compatible)

Answer

Amazon Redshift

Answer

Amazon RDS for SQL Server

Question 12

Which TWO strategies can improve query performance in Amazon Aurora MySQL for a read-heavy workload? (Select TWO.)

Accepted Answer

Enable Aurora Auto Scaling for read replicas. Aurora Replicas offload read traffic, and Auto Scaling adjusts the number of replicas based on load. Option C (Multi-AZ) is for failover, not read scaling. Option D (EBS optimization) is not applicable to Aurora (uses cluster volume). Option E (DynamoDB) is a different service.

Answer

Use Provisioned IOPS EBS volumes for the primary instance

Answer

Enable Multi-AZ to create a standby for read traffic

Answer

Migrate the read-heavy queries to Amazon DynamoDB

Question 13

Which TWO factors should be considered when designing a database for an IoT workload that ingests millions of sensor readings per second? (Choose 2.)

Accepted Answer

Implement data retention and aggregation to reduce storage costs. Options A and C are correct: Time-series data is best stored in a time-series database like Timestream, and data retention policies are crucial to manage storage costs. Option B is wrong because strong consistency is not typically required for IoT. Option D is wrong because graph databases are for relationships. Option E is wrong because ACID compliance is usually unnecessary for sensor data.

Answer

Ensure strong consistency for all reads

Answer

Enforce ACID transactions for all writes

Answer

Use a graph database to model relationships between sensors

Question 14

An e-commerce platform uses Amazon RDS for PostgreSQL to store order data. The database has a table "orders" with 500 million rows. The application runs a report query that aggregates daily sales for the last 30 days. The query currently scans the entire table and takes 15 minutes to complete. The team needs to reduce the query time to under 30 seconds. Which solution is MOST cost-effective?

Accepted Answer

Create a materialized view that stores daily sales aggregates and refresh it nightly.. Option B is correct because a materialized view can pre-aggregate the daily sales, and refreshing it daily avoids scanning the full table. Option A is wrong because indexes on date columns help but still require scanning large portions. Option C is wrong because partitioning by month still requires scanning the partition. Option D is wrong because upgrading to a larger instance is costly and may not achieve sub-30 seconds.

Answer

Partition the table by month and query only the relevant partitions.

Answer

Add a composite index on the date column and the sales amount column.

Answer

Upgrade the RDS instance to a larger size with more vCPUs and memory.

Question 15

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 allows efficient querying by tag. To query multiple tags, application-side intersection is needed. Option A (RDS with multiple join tables) is wrong because it introduces complex joins and is less scalable. Option C (ElastiCache) is wrong because it is not a persistent database for primary storage. Option D (Neptune) is wrong because although graph databases can handle tags, they are not the most straightforward for simple tag queries.

Answer

Amazon RDS for MySQL with a normalized schema

Answer

Amazon Neptune

Answer

Amazon ElastiCache for Memcached