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courses/level101/messagequeue/further_reading.md
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# Further reading
Message Queue
[https://sudhir.io/the-big-little-guide-to-message-queues](https://sudhir.io/the-big-little-guide-to-message-queues)
[Understanding Message Brokers](http://www.oreilly.com/programming/free/understanding-message-brokers.csp)
[Understanding message brokers: learn the mechanics of messaging though ActiveMQ and Kafka](http://www.oreilly.com/programming/free/understanding-message-brokers.csp)
[The Myth of the Magical Messaging Fabric by Jakub Korab](https://www.youtube.com/watch?v=Ie3--CSpCGs)
[Exactly-once message delivery](https://exactly-once.github.io/posts/exactly-once-delivery/)
[Video: The Myth of the Magical Messaging Fabric by Jakub Korab](https://www.youtube.com/watch?v=Ie3--CSpCGs)
[A Fair Comparison of Message Queuing Systems](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9303425)
[Design Patterns for Cloud Native Applications: Chapter 2 Communication Patterns]()
[Choose between Azure messaging services - Event Grid, Event Hubs, and Service Bus](https://docs.microsoft.com/en-us/azure/event-grid/compare-messaging-services)
[Exactly-once message delivery](https://exactly-once.github.io/posts/exactly-once-delivery/)
[Task Queues](https://taskqueues.com/)
[RabbitMQ tutorial](https://www.rabbitmq.com/getstarted.html)

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courses/level101/messagequeue/intro.md
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# Message Queue
# Messaging services
## What to expect from this course
At the end of training, you will have an understanding of what a Message Queue is, learn about different types of Message Queue implementation and understand some of the underlying concepts & trade offs.
## What is not covered under this course
We will not be deep diving into any specific Message Queue.
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## Introduction
### Types of Message Queue:
### Types of Messaging services:
1. **General-purpose message queue:** .
Typcially it supports various of message queue protocol like AMQP, MQTT, .
Thoughput are under 100K messages per second. Examples are Rabbitmq, ActiveMQ.
2. **Pub/Sub messaging:**
Examples are Azure Event Grid, AWS SNS
3. **Streaming processing:**
processes 1 milion messages per second
To scaling out, those solution will pick a sharding (partitioning). Only the message in the same partition can be processed in order.
Message comsumption is not transtional.
Kafka, AWS Kinesis stream, Azure Event Hubs, RocketMQ, Apache Pulsar, Redis Streams,
1. **General-purpose message broker:** rabbitmq, activemq
2. **Message streaming:** kalfa, rocketmq, Redis Streams, PULSAR?, AWS Kinesis stream
3. **Pub/Sub??:** GCP Pub/Sub, AWS SNS
4. **Brokerless:** ex zeromq, Chronicle Queue
5. **Database-as-queue** Normal people will consider it is an anti-pattern to