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  5. Amazon MQ vs Apache RocketMQ

Amazon MQ vs Apache RocketMQ

OverviewDecisionsComparisonAlternatives

Overview

Apache RocketMQ
Apache RocketMQ
Stacks48
Followers200
Votes8
Amazon MQ
Amazon MQ
Stacks55
Followers325
Votes12

Amazon MQ vs Apache RocketMQ: What are the differences?

<Apache RocketMQ vs Amazon MQ>

1. **Communication Protocol Compatibility**: Amazon MQ supports multiple messaging protocols like AMQP, MQTT, OpenWire, and STOMP, while Apache RocketMQ mainly focuses on the support for the MQTT protocol.
   
2. **Message Persistence Mechanism**: Amazon MQ uses a managed message broker service that provides message persistence by default, ensuring durability of messages in case of failures, while Apache RocketMQ provides configurable persistence options allowing users to customize the persistence mechanism as per their requirements.

3. **Cloud Provider Integration**: Amazon MQ is a fully managed service provided by Amazon Web Services (AWS) and seamlessly integrates with other AWS services, facilitating easy deployment and scalability within the AWS ecosystem, whereas Apache RocketMQ is an open-source messaging solution that can be deployed on various cloud platforms, providing flexibility but requiring more manual configuration for integration.

4. **Partitioning and Scalability**: Apache RocketMQ offers built-in support for message queue partitioning, allowing for better scalability and performance handling large volumes of messages, while Amazon MQ provides a more straightforward but less customizable setup for partitioning and handling scalability requirements.

5. **Monitoring and Management Tools**: Amazon MQ includes comprehensive monitoring and management tools within the AWS Management Console, streamlining operational tasks such as configuring alarms, tracking metrics, and scaling resources, whereas Apache RocketMQ users may need to rely on third-party tools or develop custom solutions for monitoring and managing their deployments.

6. **Community Support and Development**: Apache RocketMQ benefits from a vibrant open-source community that contributes to its ongoing development and support, providing a range of resources, forums, and updates, while Amazon MQ, being a managed service, has limited community-driven development but receives consistent updates and support from AWS.

In Summary, Amazon MQ and Apache RocketMQ differ in their communication protocol compatibility, message persistence mechanism, cloud provider integration, partitioning and scalability capabilities, monitoring and management tools, and community support and development approaches.

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Advice on Apache RocketMQ, Amazon MQ

MITHIRIDI
MITHIRIDI

Software Engineer at LightMetrics

May 8, 2020

Needs adviceonAmazon SQSAmazon SQSAmazon MQAmazon MQ

I want to schedule a message. Amazon SQS provides a delay of 15 minutes, but I want it in some hours.

Example: Let's say a Message1 is consumed by a consumer A but somehow it failed inside the consumer. I would want to put it in a queue and retry after 4hrs. Can I do this in Amazon MQ? I have seen in some Amazon MQ videos saying scheduling messages can be done. But, I'm not sure how.

303k views303k
Comments

Detailed Comparison

Apache RocketMQ
Apache RocketMQ
Amazon MQ
Amazon MQ

Apache RocketMQ is a distributed messaging and streaming platform with low latency, high performance and reliability, trillion-level capacity and flexible scalability.

Amazon MQ is a managed message broker service for Apache ActiveMQ that makes it easy to set up and operate message brokers in the cloud.

Statistics
Stacks
48
Stacks
55
Followers
200
Followers
325
Votes
8
Votes
12
Pros & Cons
Pros
  • 2
    Million-level message accumulation capacity in a single
  • 2
    Support tracing message and transactional message
  • 1
    Low latency
  • 1
    BigData Friendly
  • 1
    High throughput messaging
Pros
  • 7
    Supports low IQ developers
  • 3
    Supports existing protocols (JMS, NMS, AMQP, STOMP, …)
  • 2
    Easy to migrate existing messaging service
Cons
  • 4
    Slow AF
Integrations
Docker
Docker
AWS IAM
AWS IAM
Amazon CloudWatch
Amazon CloudWatch
ActiveMQ
ActiveMQ

What are some alternatives to Apache RocketMQ, Amazon MQ?

Kafka

Kafka

Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.

RabbitMQ

RabbitMQ

RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.

Celery

Celery

Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well.

Amazon SQS

Amazon SQS

Transmit any volume of data, at any level of throughput, without losing messages or requiring other services to be always available. With SQS, you can offload the administrative burden of operating and scaling a highly available messaging cluster, while paying a low price for only what you use.

NSQ

NSQ

NSQ is a realtime distributed messaging platform designed to operate at scale, handling billions of messages per day. It promotes distributed and decentralized topologies without single points of failure, enabling fault tolerance and high availability coupled with a reliable message delivery guarantee. See features & guarantees.

ActiveMQ

ActiveMQ

Apache ActiveMQ is fast, supports many Cross Language Clients and Protocols, comes with easy to use Enterprise Integration Patterns and many advanced features while fully supporting JMS 1.1 and J2EE 1.4. Apache ActiveMQ is released under the Apache 2.0 License.

ZeroMQ

ZeroMQ

The 0MQ lightweight messaging kernel is a library which extends the standard socket interfaces with features traditionally provided by specialised messaging middleware products. 0MQ sockets provide an abstraction of asynchronous message queues, multiple messaging patterns, message filtering (subscriptions), seamless access to multiple transport protocols and more.

Apache NiFi

Apache NiFi

An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.

Gearman

Gearman

Gearman allows you to do work in parallel, to load balance processing, and to call functions between languages. It can be used in a variety of applications, from high-availability web sites to the transport of database replication events.

Memphis

Memphis

Highly scalable and effortless data streaming platform. Made to enable developers and data teams to collaborate and build real-time and streaming apps fast.

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