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  1. Stackups
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  5. Amazon MQ vs Kestrel

Amazon MQ vs Kestrel

OverviewDecisionsComparisonAlternatives

Overview

Kestrel
Kestrel
Stacks37
Followers58
Votes0
Amazon MQ
Amazon MQ
Stacks55
Followers325
Votes12

Amazon MQ vs Kestrel: What are the differences?

Introduction

Amazon MQ and Kestrel are message queue services used for handling messaging between applications in a distributed system.

  1. Protocol Support: Amazon MQ supports popular messaging protocols such as MQTT, AMQP, and STOMP, providing flexibility for different types of applications to communicate. On the other hand, Kestrel only supports the Thrift protocol, limiting its compatibility with other messaging systems.

  2. Managed Service: Amazon MQ is a fully managed service provided by AWS, offering hassle-free setup, maintenance, and scalability. Kestrel, on the other hand, requires manual configuration and monitoring, making it more suitable for organizations with specific customization needs and the technical expertise to manage it.

  3. Scaling Capabilities: Amazon MQ offers auto-scaling capabilities, allowing the service to adjust resources based on demand to ensure optimal performance and cost efficiency. Kestrel, although capable of horizontal scaling, relies on manual intervention for scaling operations, which can be cumbersome and time-consuming in high-traffic environments.

  4. Redundancy and High Availability: Amazon MQ provides out-of-the-box redundancy and high-availability features, ensuring message reliability and fault tolerance. In contrast, Kestrel may require custom configurations and additional setup to achieve similar levels of redundancy and availability.

  5. Monitoring and Metrics: Amazon MQ offers comprehensive monitoring and metrics through AWS CloudWatch, providing insights into message queue performance and health. Kestrel, being a more lightweight solution, may lack built-in monitoring capabilities and may require integration with third-party tools for monitoring and analysis.

  6. Integration with AWS Services: Amazon MQ seamlessly integrates with various AWS services such as Lambda, S3, and EC2, facilitating seamless communication and data exchange within the AWS ecosystem. Kestrel, being an independent service, may require additional configuration and setup to integrate with AWS services, potentially adding complexity to the integration process.

In Summary, Amazon MQ and Kestrel differ in terms of protocol support, managed service, scaling capabilities, redundancy, monitoring, and integration with AWS services.

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Advice on Kestrel, 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

Kestrel
Kestrel
Amazon MQ
Amazon MQ

Kestrel is based on Blaine Cook's "starling" simple, distributed message queue, with added features and bulletproofing, as well as the scalability offered by actors and the JVM.

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.

Written by Robey Pointer;Starling clone written in Scala (a port of Starling from Ruby to Scala);Queues are stored in memory, but logged on disk
-
Statistics
Stacks
37
Stacks
55
Followers
58
Followers
325
Votes
0
Votes
12
Pros & Cons
No community feedback yet
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
No integrations available
AWS IAM
AWS IAM
Amazon CloudWatch
Amazon CloudWatch
ActiveMQ
ActiveMQ

What are some alternatives to Kestrel, 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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