Kafka vs RabbitMQ vs Redis Pub/Sub - Practice Questions

Challenge - 5 Problems

🧠 Conceptual

intermediate

Primary Use Case Differences

Which of the following best describes the primary use case difference between Kafka, RabbitMQ, and Redis Pub/Sub?

A Kafka is used for web hosting, RabbitMQ for file storage, Redis Pub/Sub for image processing.

B Kafka is mainly for caching, RabbitMQ for database storage, Redis Pub/Sub for batch processing.

C Kafka is designed for high-throughput event streaming, RabbitMQ for complex routing and message queuing, Redis Pub/Sub for lightweight real-time messaging without persistence.

D Kafka is a relational database, RabbitMQ is a web server, Redis Pub/Sub is a programming language.

💡 Hint

Think about what each system is optimized to do in messaging and data handling.

Kafka is optimized for streaming large volumes of data with durability. RabbitMQ excels at complex routing and guaranteed delivery. Redis Pub/Sub is fast but does not store messages.

❓ Predict Output

intermediate

Message Persistence Behavior

Given the following scenario, which system will retain messages if the consumer is offline and reconnects later?

Kafka

Scenario: A producer sends messages continuously. The consumer disconnects for 10 minutes and then reconnects.

A Kafka will retain messages and deliver them when the consumer reconnects.

B RabbitMQ will not retain messages if the consumer is offline.

C Redis Pub/Sub will retain messages and deliver them when the consumer reconnects.

D None of the systems retain messages for offline consumers.

💡 Hint

Consider which systems support message durability and replay.

Kafka stores messages on disk and allows consumers to read from any offset, so messages are retained. Redis Pub/Sub does not store messages, so offline consumers miss messages. RabbitMQ can retain messages if configured with durable queues, but by default messages may be lost if the consumer is offline.

🔧 Debug

advanced

Unexpected Message Loss in Redis Pub/Sub

You implemented a Redis Pub/Sub system but notice that some messages are lost when subscribers are disconnected briefly. What is the root cause?

A Redis Pub/Sub uses a message broker that crashed.

B Redis Pub/Sub does not queue messages; if a subscriber is offline, it misses messages sent during that time.

C Redis Pub/Sub stores messages on disk but the disk is full.

D Redis Pub/Sub requires explicit message acknowledgments to prevent loss.

💡 Hint

Think about how Redis Pub/Sub handles message delivery and subscriber state.

Redis Pub/Sub delivers messages only to currently connected subscribers. It does not store or queue messages, so any subscriber disconnected during message publishing will miss those messages.

📝 Syntax

advanced

Kafka Consumer Group Configuration

Which Kafka consumer configuration option ensures that multiple consumers share the load of a topic's partitions?

A Setting 'auto.offset.reset' to 'latest'.

B Setting different 'group.id' values for each consumer.

C Setting 'enable.auto.commit' to false.

D Setting the same 'group.id' for all consumers to form a consumer group.

💡 Hint

Consumer groups allow load balancing across consumers.

Consumers with the same 'group.id' form a group and share partitions of the topic, enabling parallel processing. Different 'group.id's mean independent consumers each get all messages.

🚀 Application

expert

Choosing the Right System for Real-Time Analytics

You need to build a real-time analytics pipeline that processes millions of events per second with guaranteed message delivery and the ability to replay events for debugging. Which system is the best choice?

A Kafka, because it supports high throughput, durability, and replayable event streams.

B RabbitMQ, because it is optimized for lightweight real-time messaging without persistence.

C Redis Pub/Sub, because it stores all messages and supports complex routing.

D None of these systems can handle real-time analytics at scale.

💡 Hint

Consider throughput, durability, and replay features.

Kafka is designed for high-throughput event streaming with durable storage and allows consumers to replay events from any point, making it ideal for real-time analytics pipelines.

Practice

1. Which messaging system is best suited for storing message history and handling large data streams?

easy

A. None of the above

B. RabbitMQ

C. Redis Pub/Sub

D. Kafka

Solution

1. Step 1: Understand Kafka's purpose

   Kafka is designed to handle large data streams and keeps a durable log of messages, allowing message history to be stored.

2. Step 2: Compare with RabbitMQ and Redis Pub/Sub

   RabbitMQ focuses on reliable delivery and routing, while Redis Pub/Sub is fast but does not store messages.

3. Final Answer:

   Kafka -> Option D

4. Quick Check:

   Message history and big data = Kafka [OK]

Hint: Remember: Kafka stores history; Redis Pub/Sub does not [OK]

Common Mistakes:

• Confusing Redis Pub/Sub as storing messages
• Thinking RabbitMQ stores message history
• Assuming all systems keep message logs

2. Which of the following is the correct statement about Redis Pub/Sub?

easy

A. Redis Pub/Sub guarantees message delivery even if subscribers are offline.

B. Redis Pub/Sub does not store messages; it only delivers messages to active subscribers.

C. Redis Pub/Sub supports complex message routing like RabbitMQ.

D. Redis Pub/Sub is designed for batch processing of messages.

Solution

1. Step 1: Analyze Redis Pub/Sub behavior

   Redis Pub/Sub delivers messages only to subscribers currently connected; it does not store messages for offline clients.

2. Step 2: Check other options

   Redis Pub/Sub guarantees message delivery even if subscribers are offline. is false because Redis Pub/Sub does not guarantee delivery if subscribers are offline. Redis Pub/Sub supports complex message routing like RabbitMQ. is false because Redis Pub/Sub lacks complex routing. Redis Pub/Sub is designed for batch processing of messages. is false because Redis Pub/Sub is for real-time messaging, not batch processing.

3. Final Answer:

   Redis Pub/Sub does not store messages; it only delivers messages to active subscribers. -> Option B

4. Quick Check:

   Redis Pub/Sub delivers only to active subscribers [OK]

Hint: Redis Pub/Sub = no message storage, only live delivery [OK]

Common Mistakes:

• Assuming Redis Pub/Sub stores messages
• Confusing Redis with RabbitMQ routing features
• Thinking Redis Pub/Sub supports offline message delivery

3. Given the following scenario: You need a messaging system that supports flexible routing and guarantees message delivery even if consumers are temporarily offline. Which system fits best?

medium

A. Kafka

B. Redis Pub/Sub

C. RabbitMQ

D. None of the above

Solution

1. Step 1: Understand RabbitMQ features

   RabbitMQ supports flexible routing through exchanges and queues and guarantees message delivery with acknowledgments and persistence.

2. Step 2: Compare with Kafka and Redis Pub/Sub

   Kafka stores messages but is less flexible in routing. Redis Pub/Sub is fast but does not guarantee delivery if consumers are offline.

3. Final Answer:

   RabbitMQ -> Option C

4. Quick Check:

   Flexible routing + guaranteed delivery = RabbitMQ [OK]

Hint: Flexible routing and delivery guarantees point to RabbitMQ [OK]

Common Mistakes:

• Choosing Kafka for flexible routing
• Assuming Redis Pub/Sub guarantees delivery
• Ignoring RabbitMQ's message acknowledgment feature

4. You have a system using Redis Pub/Sub, but messages are lost when subscribers disconnect. What is the best way to fix this issue?

medium

A. Switch to Kafka to store messages and allow offline consumption.

B. Increase Redis server memory to store more messages.

C. Use Redis Pub/Sub with message persistence enabled.

D. Configure Redis to retry sending messages to offline subscribers.

Solution

1. Step 1: Identify Redis Pub/Sub limitation

   Redis Pub/Sub does not store messages; if subscribers disconnect, messages are lost.

2. Step 2: Choose a system that stores messages

   Kafka stores messages durably, allowing consumers to read messages even after being offline.

3. Final Answer:

   Switch to Kafka to store messages and allow offline consumption. -> Option A

4. Quick Check:

   Redis Pub/Sub no storage; Kafka stores messages [OK]

Hint: Redis Pub/Sub can't store messages; Kafka can [OK]

Common Mistakes:

• Trying to enable persistence on Redis Pub/Sub (not supported)
• Assuming Redis memory increase solves message loss
• Expecting Redis to retry offline delivery automatically

5. You want to build a real-time analytics system that processes large volumes of data and keeps a full history of all events for auditing. Which combination of messaging systems is the best approach?

hard

A. Use Kafka for event storage and Redis Pub/Sub for real-time notifications.

B. Use RabbitMQ for event storage and Redis Pub/Sub for message routing.

C. Use Redis Pub/Sub alone for both storage and real-time processing.

D. Use RabbitMQ alone for storing large data streams and real-time analytics.

Solution

1. Step 1: Identify requirements

   The system needs to handle large data volumes, keep full event history, and provide real-time notifications.

2. Step 2: Match systems to requirements

   Kafka is ideal for storing large data streams and keeping history. Redis Pub/Sub is fast for real-time notifications but does not store data.

3. Step 3: Evaluate other options

   RabbitMQ is good for routing and delivery but less suited for big data storage. Redis Pub/Sub alone cannot store messages. RabbitMQ alone is not optimized for large data streams.

4. Final Answer:

   Use Kafka for event storage and Redis Pub/Sub for real-time notifications. -> Option A

5. Quick Check:

   Kafka stores history + Redis Pub/Sub fast notifications [OK]

Hint: Combine Kafka storage with Redis Pub/Sub speed [OK]

Common Mistakes:

• Using Redis Pub/Sub alone for storage
• Assuming RabbitMQ handles big data storage well
• Ignoring Kafka's strength in event history