Kafka vs RabbitMQ vs Redis Pub/Sub - Visual Side-by-Side Comparison

Process Flow - Kafka vs RabbitMQ vs Redis Pub/Sub

Message Produced

↓

Kafka Broker

↓

Kafka Consumer

↓

Message Processed

Messages flow from producers to brokers (Kafka, RabbitMQ, Redis), then to consumers or subscribers, showing different delivery and storage models.

Execution Sample

Kafka

producer.send('topic', 'message')
consumer.poll()

# Simplified for Kafka

# RabbitMQ and Redis have similar publish-subscribe calls

Shows a message sent by a producer and received by a consumer in Kafka, similar patterns apply to RabbitMQ and Redis Pub/Sub.

Process Table

Step	System	Action	Message State	Delivery Guarantee	Notes
1	Producer	Sends message to Kafka topic	Message queued in Kafka	At least once	Kafka stores message on disk
2	Kafka Broker	Stores message in partition	Message persisted	Durable	Supports replay by consumers
3	Consumer	Polls messages	Message delivered	At least once	Consumer offset tracks progress
4	Producer	Sends message to RabbitMQ exchange	Message routed to queue	At least once	RabbitMQ stores in memory/disk
5	RabbitMQ Broker	Routes message to queue	Message queued	Durable if configured	Supports acknowledgments
6	Consumer	Receives message from queue	Message delivered	At least once	Manual ack controls re-delivery
7	Publisher	Publishes message to Redis channel	Message sent to subscribers	At most once	No message storage
8	Subscriber	Receives message if connected	Message delivered	No durability	Missed if disconnected
9	End	No more messages	N/A	N/A	Execution stops

💡 No more messages to process or subscribers connected

Status Tracker

Variable	Start	After Kafka Produce	After Kafka Consume	After RabbitMQ Produce	After RabbitMQ Consume	After Redis Publish	After Redis Subscribe
Message State	None	Queued in Kafka	Delivered to Kafka Consumer	Queued in RabbitMQ	Delivered to RabbitMQ Consumer	Published on Redis channel	Received by Redis Subscriber

Key Moments - 3 Insights

Why does Redis Pub/Sub not guarantee message delivery?

Because Redis Pub/Sub does not store messages; if a subscriber is disconnected, it misses messages (see execution_table step 7 and 8).

How does Kafka ensure messages can be replayed?

Kafka stores messages durably on disk in partitions, allowing consumers to replay from offsets (see execution_table step 2).

What controls message re-delivery in RabbitMQ?

RabbitMQ uses manual acknowledgments from consumers; if not acknowledged, messages can be re-delivered (see execution_table step 6).

Visual Quiz - 3 Questions

Look at the execution_table, at which step does Kafka store the message persistently?

A Step 2

B Step 4

C Step 1

D Step 7

💡 Hint

Check the 'Message State' and 'Notes' columns for Kafka in step 2.

According to variable_tracker, what is the message state after RabbitMQ consume?

A Queued in RabbitMQ

B Delivered to RabbitMQ Consumer

C Published on Redis channel

D Delivered to Kafka Consumer

💡 Hint

Look at the 'After RabbitMQ Consume' column for 'Message State'.

If a Redis subscriber disconnects, what happens to messages sent during that time?

A Messages are queued in Redis

B Messages are stored and delivered later

C Messages are lost and not delivered

D Messages are sent to RabbitMQ

💡 Hint

Refer to execution_table steps 7 and 8 about Redis Pub/Sub delivery guarantees.

Concept Snapshot

Kafka, RabbitMQ, and Redis Pub/Sub are messaging systems.
Kafka stores messages durably with replay support.
RabbitMQ routes messages with acknowledgments for reliability.
Redis Pub/Sub sends messages live without storage.
Choose based on delivery guarantees and use case.

Full Transcript

This visual execution compares Kafka, RabbitMQ, and Redis Pub/Sub messaging systems. Messages start from producers or publishers and go to brokers or servers. Kafka stores messages durably on disk, allowing consumers to replay messages by tracking offsets. RabbitMQ routes messages to queues and requires consumers to acknowledge messages to avoid re-delivery. Redis Pub/Sub sends messages live to subscribers without storing them, so disconnected subscribers miss messages. The execution table shows each step, message state, and delivery guarantees. Variable tracking shows message state changes after each system's produce and consume actions. Key moments clarify why Redis does not guarantee delivery, how Kafka supports replay, and how RabbitMQ controls re-delivery. The quiz tests understanding of message storage steps, message states, and Redis delivery behavior. The snapshot summarizes key differences and when to use each system.

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