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What is the common Message Queue comparison? in view of this question, this article introduces the corresponding analysis and solution in detail, hoping to help more partners who want to solve this problem to find a more simple and feasible method.

RabbitMQ

Is an open source message queue written in Erlang, which supports many protocols: AMQP,XMPP, SMTP, STOMP, which makes it very heavyweight and more suitable for enterprise development. At the same time, a Broker architecture is implemented, which means that messages are queued in a central queue before being sent to the client. Good support for routing (Routing), load balancing (Load balance) or data persistence.

Redis

Is a Key-Value NoSQL database, development and maintenance is very active, although it is a Key-Value database storage system, but it supports MQ functions, so it can be used as a lightweight queue service. For the entry and exit operations of RabbitMQ and Redis, each performed 1 million times, and the execution time was recorded every 100000 times. The test data are divided into four different sizes: 128Bytes, 512Bytes, 1K and 10K. The experimental results show that when joining the team, the performance of Redis is higher than that of RabbitMQ when the data is compared, but it is unbearably slow if the data size exceeds 10K; when leaving the team, Redis shows very good performance regardless of the size of the data, while the performance of RabbitMQ is much lower than that of Redis. (personally, I don't think the data is reasonable when I join the team for 10k.)

Join the team

Get out of the team

128B

512B

1K

10K

128B

512B

1K

10K

Redis

16088

15961

17094

twenty-five

15955

20449

18098

9355

RabbitMQ

10627

9916

9370

2366

3219

3174

2982

1588

ZeroMQ

The so-called fastest message queuing system, especially for high-throughput demand scenarios. ZMQ can implement advanced / complex queues that RabbitMQ is not good at, but developers need to combine a variety of technical frameworks themselves, and the technical complexity is a challenge to the successful application of this MQ. ZeroMQ has a unique non-middleware mode, you do not need to install and run a message server or middleware, because your application will play this service role. You can simply reference the ZeroMQ library, install it using NuGet, and then you can happily send messages between applications. But ZeroMQ only provides non-persistent queues, which means that data will be lost if the downmachine is used. Among them, ZeroMQ is used as the transmission of the data stream in the Storm of Twitter.

ActiveMQ

Is a sub-project under Apache. Similar to ZeroMQ, it can implement queues in proxy and peer-to-peer technologies. At the same time, similar to RabbitMQ, it can efficiently implement advanced application scenarios with a small amount of code. RabbitMQ, ZeroMQ and ActiveMQ all support commonly used multilingual clients such as C++, Java, .net, Python, Php, Ruby and so on.

Jafka/Kafka

Kafka, a sub-project of Apache, is a high-performance cross-language distributed Publish/Subscribe message queuing system, while Jafka is hatched on top of Kafka, which is an upgraded version of Kafka. It has the following characteristics: fast persistence, which can persist messages under O (1) system overhead; high throughput, which can reach the throughput rate of 10W/s on an ordinary server; complete distributed system, Broker, Producer, Consumer all support distribution automatically and realize complex equilibrium automatically. Support Hadoop data parallel loading, for the same log data and offline analysis system as Hadoop, but require real-time processing limitations, this is a feasible solution. Kafka unifies the online and offline message processing through the parallel loading mechanism of Hadoop, which is also valued by the system studied in this paper. Apache Kafka is a very lightweight messaging system compared to ActiveMQ. It is not only a very good performance, but also a well-working distributed system.

Other queue lists HornetQ, Apache Qpid, Sparrow, Starling, Kestrel, Beanstalkd, Amazon SQS are no longer analyzed one by one.

The answer to the question about the common Message Queue comparison is shared here. I hope the above content can be of some help to you. If you still have a lot of doubts to be solved, you can follow the industry information channel to learn more about it.

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