IronMQ vs Kestrel

Overview

IronMQ

Stacks35

Followers49

Votes36

Kestrel

Stacks37

Followers58

Votes0

IronMQ vs Kestrel: What are the differences?

What is IronMQ? Message Queue for any deployment. An easy-to-use highly available message queuing service. Built for distributed cloud applications with critical messaging needs. Provides on-demand message queuing with advanced features and cloud-optimized performance.

What is Kestrel? Simple, distributed message queue system. 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.

IronMQ and Kestrel can be categorized as "Message Queue" tools.

Some of the features offered by IronMQ are:

Instant High Availability- Runs on top cloud infrastructures and uses multiple high-availability data centers. Uses reliable datastores for message durability and persistence.
Easy to Use- IronMQ is super easy to use. Simply connect directly to the API endpoints and you're ready to create and use queues. There are also client libraries available in any language you want – Ruby, Python, PHP, Java, .NET, Go, Node.JS, and more
Scalable / High Performance- Built using high-performance languages designed for concurrency and runs on industrial-strength clouds. Push messages and stream data at will without worrying about memory limits or adding more servers.

On the other hand, Kestrel provides the following key features:

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

Kestrel is an open source tool with 2.8K GitHub stars and 326 GitHub forks. Here's a link to Kestrel's open source repository on GitHub.

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Detailed Comparison

IronMQ	Kestrel
An easy-to-use highly available message queuing service. Built for distributed cloud applications with critical messaging needs. Provides on-demand message queuing with advanced features and cloud-optimized performance.	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.
Instant High Availability- Runs on top cloud infrastructures and uses multiple high-availability data centers. Uses reliable datastores for message durability and persistence.;Easy to Use- IronMQ is super easy to use. Simply connect directly to the API endpoints and you're ready to create and use queues. There are also client libraries available in any language you want – Ruby, Python, PHP, Java, .NET, Go, Node.JS, and more;Scalable / High Performance- Built using high-performance languages designed for concurrency and runs on industrial-strength clouds. Push messages and stream data at will without worrying about memory limits or adding more servers.;Realtime Monitoring- Get realtime monitoring of your message queues through IronMQ's beautiful dashboard. This allows you to quickly find, diagnose, and resolve problems before others notice.;One-time FIFO delivery;Push Queues and publish-subscribe support;Queue messages using webhooks	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 35	Stacks 37
Followers 49	Followers 58
Votes 36	Votes 0
Pros & Cons
Pros 12 Great Support 8 Heroku Add-on 3 Push support 3 Delayed delivery upto 7 days 2 Ease of configuration Cons 1 Can't use rabbitmqadmin	No community feedback yet
Integrations
Amazon EC2 Heroku Engine Yard Cloud Rackspace Cloud Servers Red Hat OpenShift StackMob AppFog cloudControl	No integrations available

What are some alternatives to IronMQ, Kestrel?

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

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

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 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

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

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

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 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

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