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.

Practice

1. Which database is best known for automatic scaling and simple key-value access?

easy

A. Cassandra

B. DynamoDB

C. MongoDB

D. MySQL

Solution

1. Step 1: Understand DynamoDB's core feature

   DynamoDB is designed for simple key-value access and automatic scaling.

2. Step 2: Compare with other databases

   MongoDB focuses on flexible document storage, Cassandra on high availability for huge data.

3. Final Answer:

   DynamoDB -> Option B

4. Quick Check:

   Automatic scaling + key-value = DynamoDB [OK]

Hint: Automatic scaling with key-value means DynamoDB [OK]

Common Mistakes:

• Confusing MongoDB's flexible documents with key-value simplicity
• Thinking Cassandra automatically scales like DynamoDB
• Choosing MySQL which is relational, not key-value

2. Which of the following is the correct way to describe MongoDB's data model?

easy

A. Column-family store with automatic partitioning

B. Simple key-value pairs with fixed schema

C. Flexible document storage with rich queries

D. Relational tables with strict schema

Solution

1. Step 1: Identify MongoDB's data model

   MongoDB stores data as flexible JSON-like documents allowing rich queries.

2. Step 2: Eliminate other options

   Column-family store describes Cassandra, key-value with fixed schema fits DynamoDB less, relational tables fit SQL databases.

3. Final Answer:

   Flexible document storage with rich queries -> Option C

4. Quick Check:

   MongoDB = flexible documents + rich queries [OK]

Hint: MongoDB = flexible JSON documents + rich queries [OK]

Common Mistakes:

• Confusing MongoDB with Cassandra's column-family model
• Thinking MongoDB uses fixed schema like relational DB
• Mixing key-value with document storage

3. Given a large dataset requiring high availability and fast writes across multiple data centers, which database is most suitable?

medium

A. MongoDB

B. DynamoDB

C. SQLite

D. Cassandra

Solution

1. Step 1: Analyze requirements for high availability and multi-datacenter writes

   Cassandra is designed for huge data with high availability and multi-region replication.

2. Step 2: Compare other options

   MongoDB supports replication but less optimized for huge scale multi-datacenter writes; DynamoDB is scalable but less focused on multi-datacenter writes; SQLite is local and not distributed.

3. Final Answer:

   Cassandra -> Option D

4. Quick Check:

   High availability + multi-datacenter = Cassandra [OK]

Hint: Huge data + multi-region writes = Cassandra [OK]

Common Mistakes:

• Choosing DynamoDB for multi-datacenter writes
• Confusing SQLite as distributed database
• Assuming MongoDB handles huge multi-region writes best

4. You try to use MongoDB's flexible document queries on DynamoDB but get errors. What is the likely cause?

medium

A. DynamoDB does not support flexible document queries like MongoDB

B. DynamoDB requires SQL syntax for queries

C. MongoDB uses column-family data model incompatible with DynamoDB

D. DynamoDB only supports relational tables

Solution

1. Step 1: Understand query capabilities of DynamoDB

   DynamoDB supports key-value and simple queries but not rich flexible document queries like MongoDB.

2. Step 2: Eliminate incorrect causes

   DynamoDB does not use SQL syntax, is not column-family, and is not relational.

3. Final Answer:

   DynamoDB does not support flexible document queries like MongoDB -> Option A

4. Quick Check:

   DynamoDB lacks MongoDB's flexible queries [OK]

Hint: DynamoDB lacks MongoDB's rich document query support [OK]

Common Mistakes:

• Assuming DynamoDB uses SQL syntax
• Confusing data models between MongoDB and Cassandra
• Thinking DynamoDB supports relational tables

5. You need a database for an app that requires flexible JSON documents, automatic scaling, and global availability. Which approach best fits this need?

hard

A. Use DynamoDB with JSON support and global tables

B. Use MongoDB with sharding and replica sets only

C. Use Cassandra with column-family tables and no JSON support

D. Use SQLite with local JSON extensions

Solution

1. Step 1: Identify features needed

   The app needs flexible JSON documents, automatic scaling, and global availability.

2. Step 2: Match features to databases

   DynamoDB supports JSON documents, automatic scaling, and global tables for availability. MongoDB supports JSON but global availability requires extra setup and scaling is manual. Cassandra lacks native JSON support and SQLite is local only.

3. Final Answer:

   Use DynamoDB with JSON support and global tables -> Option A

4. Quick Check:

   JSON + auto scale + global = DynamoDB [OK]

Hint: DynamoDB global tables + JSON = best for scaling + availability [OK]

Common Mistakes:

• Choosing MongoDB without considering scaling complexity
• Ignoring Cassandra's lack of JSON support
• Selecting SQLite which is not distributed