Overview

IronMQ

Stacks35

Followers49

Votes36

Kafka

Stacks24.2K

Followers22.3K

Votes607

GitHub Stars31.2K

Forks14.8K

IronMQ vs Kafka: What are the differences?

Introduction: IronMQ and Kafka are both popular messaging systems used for real-time data processing and communication in distributed systems. While they serve similar purposes, there are key differences between the two that make them suitable for different use cases.

Data Retention: IronMQ provides message retention of up to 7 days by default, with an option to extend it further if needed, making it suitable for short-term message processing scenarios. On the other hand, Kafka allows users to retain messages for much longer periods, ranging from days to months or even years, making it ideal for use cases requiring long-term data storage and analysis.
Scalability: Kafka is known for its high throughput and horizontal scalability, allowing it to handle large volumes of data across multiple servers seamlessly. IronMQ, while scalable, may not offer the same level of performance and scalability as Kafka, particularly in scenarios where massive data ingestion and processing are required.
Persistence: Kafka stores messages in disk-based commit logs, ensuring durability and fault tolerance in case of system failures. In contrast, IronMQ is a cloud-based messaging system that may not provide the same level of persistence as Kafka, making it more suitable for applications where data durability is not a primary concern.
Ease of Use: IronMQ is often praised for its simplicity and ease of setup, making it a preferred choice for straightforward messaging needs that do not require complex configurations. On the other hand, Kafka's robust feature set and configuration options cater to more advanced use cases, making it a better fit for organizations with specific requirements around data processing and delivery.
Community Support: Kafka benefits from a large and active community of developers and users, contributing to its ongoing development and support resources. While IronMQ also has a dedicated user base, Kafka's community-driven approach ensures faster updates, bug fixes, and a wealth of resources for troubleshooting and optimization.
Integration Capabilities: Kafka is well integrated with popular big data technologies like Apache Hadoop, Apache Spark, and others, making it a go-to choice for data streaming and processing in the big data ecosystem. While IronMQ offers integrations with various platforms and languages, its compatibility with big data tools may not be as extensive as Kafka's.

In Summary, IronMQ and Kafka serve as powerful messaging solutions, with IronMQ being more straightforward and suitable for short-term processing, while Kafka excels in scalability, persistence, and integration with big data technologies.

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Advice on IronMQ, Kafka

Tarun

Senior Software Developer at Okta

Dec 4, 2021

Review

We have faced the same question some time ago. Before I begin, DO NOT use Redis as a message broker. It is fast and easy to set up in the beginning but it does not scale. It is not made to be reliable in scale and that is mentioned in the official docs. This analysis of our problems with Redis may help you.

We have used Kafka and RabbitMQ both in scale. We concluded that RabbitMQ is a really good general purpose message broker (for our case) and Kafka is really fast but limited in features. That’s the trade off that we understood from using it. In-fact I blogged about the trade offs between Kafka and RabbitMQ to document it. I hope it helps you in choosing the best pub-sub layer for your use case.

153k views153k

Comments

viradiya

Apr 12, 2020

Needs adviceon

AngularJS

ASP.NET Core

MSSQL

We are going to develop a microservices-based application. It consists of AngularJS, ASP.NET Core, and MSSQL.

We have 3 types of microservices. Emailservice, Filemanagementservice, Filevalidationservice

I am a beginner in microservices. But I have read about RabbitMQ, but come to know that there are Redis and Kafka also in the market. So, I want to know which is best.

933k views933k

Comments

Kirill

GO/C developer at Duckling Sales

Feb 16, 2021

Decided

Maybe not an obvious comparison with Kafka, since Kafka is pretty different from rabbitmq. But for small service, Rabbit as a pubsub platform is super easy to use and pretty powerful. Kafka as an alternative was the original choice, but its really a kind of overkill for a small-medium service. Especially if you are not planning to use k8s, since pure docker deployment can be a pain because of networking setup. Google PubSub was another alternative, its actually pretty cheap, but I never tested it since Rabbit was matching really good for mailing/notification services.

266k views266k

Comments

Detailed Comparison

IronMQ	Kafka
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.	Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
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 at LinkedIn in Scala;Used by LinkedIn to offload processing of all page and other views;Defaults to using persistence, uses OS disk cache for hot data (has higher throughput then any of the above having persistence enabled);Supports both on-line as off-line processing
Statistics
GitHub Stars -	GitHub Stars 31.2K
GitHub Forks -	GitHub Forks 14.8K
Stacks 35	Stacks 24.2K
Followers 49	Followers 22.3K
Votes 36	Votes 607
Pros & Cons
Pros 12 Great Support 8 Heroku Add-on 3 Push support 3 Delayed delivery upto 7 days 2 Super fast Cons 1 Can't use rabbitmqadmin	Pros 126 High-throughput 119 Distributed 92 Scalable 86 High-Performance 66 Durable Cons 32 Non-Java clients are second-class citizens 29 Needs Zookeeper 9 Operational difficulties 5 Terrible Packaging
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, Kafka?

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.

Apache Pulsar

Apache Pulsar is a distributed messaging solution developed and released to open source at Yahoo. Pulsar supports both pub-sub messaging and queuing in a platform designed for performance, scalability, and ease of development and operation.