DynamoDB vs MongoDB vs Cassandra - Practice Questions

Challenge - 5 Problems

🧠 Conceptual

intermediate

Primary Data Model Differences

Which database uses a wide-column store model primarily designed for handling large volumes of data across many commodity servers?

A MongoDB

B Cassandra

C DynamoDB

D All three use the same data model

💡 Hint

Think about which database is known for its column family storage and scalability.

Cassandra uses a wide-column store model optimized for distributed data across many servers. DynamoDB is a key-value and document store, while MongoDB is a document store.

❓ query_result

intermediate

Query Consistency Behavior

If you perform a read operation immediately after a write in DynamoDB with default settings, what consistency guarantee do you get?

A Strong consistency, always returns the latest write

B Read operations are not supported in DynamoDB

C No consistency guarantees

D Eventual consistency, may return stale data

💡 Hint

Consider the default read consistency mode in DynamoDB.

DynamoDB's default read consistency is eventual consistency, which means reads may not immediately reflect the latest writes.

📝 Syntax

advanced

DynamoDB Query Syntax for Filtering

Which of the following DynamoDB query expressions correctly filters items where the attribute 'status' equals 'active'?

DynamoDB

Table.query(
  KeyConditionExpression=Key('userId').eq('123'),
  FilterExpression=???
)

A Attr('status').eq('active')

B Key('status').eq('active')

C Filter('status').equals('active')

D Attr('status').equals('active')

💡 Hint

Use the correct class for filtering non-key attributes in DynamoDB queries.

The Attr class is used for filtering on non-key attributes in DynamoDB queries. Key is for key attributes only.

❓ optimization

advanced

Optimizing Write Throughput in Cassandra

Which approach best improves write throughput in Cassandra when handling a high volume of writes?

A Use batch writes sparingly and avoid large partitions

B Increase the replication factor to 5

C Use a single partition key for all writes

D Disable commit log to speed up writes

💡 Hint

Think about partition size and batch write best practices in Cassandra.

Using batch writes carefully and avoiding large partitions helps maintain high write throughput. Increasing replication factor adds overhead, and disabling commit log risks data loss.

🔧 Debug

expert

Troubleshooting DynamoDB Query Errors

You run this DynamoDB query but get a ValidationException error:

Table.query(KeyConditionExpression=Key('userId').eq('123') & Attr('status').eq('active'))

What is the cause of the error?

A Missing quotes around '123' in the Key condition

B KeyConditionExpression requires a FilterExpression for non-key attributes

C Using & operator between Key and Attr expressions is invalid in KeyConditionExpression

D Attr cannot be used in FilterExpression

💡 Hint

Check how KeyConditionExpression and FilterExpression are used in DynamoDB queries.

KeyConditionExpression only supports conditions on key attributes. Combining it with Attr conditions using & causes a ValidationException. Non-key filters must go in FilterExpression.