基本信息对比 

主要关注前三个（标红）

支持的 Protocols 对比

The following table lists the supported protocols of each broker.

Client Interfaces 对比

mq benchmark^{[文献 1]}

结论

在传统的 MQ 中rabbitmq 的性能表现最好。

kafka 的性能优于 rabbitmq；

传统 MQ 对比

场景设计：

•       Scenario A: Enqueuing 20,000 messages of 1024 bytes each, then dequeuing them afterwards.

•       Scenario B: Enqueuing and dequeuing simultaneously 20,000 messages of1024 bytes each.

•       Scenario C: Enqueuing and dequeuing simultaneously 200,000 messages of32 bytes each.

•       Scenario D: Enqueuing and dequeuing simultaneously 200 messages of32768 bytes each.

Scenario A

Scenario B

Scenario C

Scenario D

Kafka vs rabbitmq 

结论在 kafka 和 rabbitmq 的对比中，kafka 的性能表现较好。

简介

 rocketmq 的前身为 metaq，metaq 的第一个版本是可以看成是 linkedin 的 kafka（scala）的 java 版本，并对其增加了事务的支持。rocketmq 为 metaq3.0，相比于原始 kafka，其擅长点出了原始的 log collecting 之外，还增加诸如 HA、事务等特性，使得从功能点上讲，可以替代传统大部分 MQ。

目前已经在阿里开始大规模应用，并且预计未来会逐渐在阿里取代 notify，meta 2.x 以前的所有队列。由于 rocketmq 还比较新，且官方没有给出相应的 benchmark。而 rocketmq 社区主要活跃者均是中国国内人员，因此不便于直接对比 rocketmq 和其他队列。在这里用 kafka 和其他队列进行对比，rocketmq 的性能比 kafka 还要好一些。

kafka vs rabbitmq in detail

Kafka is a general purpose message broker, like RabbItMQ, with similar distributed deployment goals, but with very different assumptions on message model semantics.   I would be skeptical of the "AMQP is more mature" argument and look at the facts of how either solution solves your problem.

a)      Use Kafka if you have a fire hose of events (100k+/sec) you need delivered in partitioned order 'at least once' with a mix of online and batch consumers, you want to be able to re-read messages, you can deal with current limitations around node-level HA (or can use trunk code), and/or you don't mind supporting incubator-level software yourself via forums/IRC.  

b)      Use Rabbit if you have messages (20k+/sec) that need to be routed in complex ways to consumers, you want per-message delivery guarantees, you don't care about ordered delivery, you need HA at the cluster-node level now, and/or you need 24x7 paid support in addition to forums/IRC.

Neither offers great "filter/query" capabilities - if you need that, consider using Storm on top of one of these solutions to add computation, filtering, querying, on your streams.   Or use something like Cassandra as your queryable cache.   Kafka is also definitely not "mature" even though it is "production ready". 

Details (caveat - my opinion, I've not used either in great anger, and I have more exposure to RabbitMQ)

Firstly, on RabbitMQ vs. Kafka.   They are both excellent solutions, RabbitMQ being more mature, but both have very different design philosophies.    Fundamentally, I'd say RabbitMQ is broker-centric, focused around delivery guarantees between producers and consumers, with transient preferred over durable messages.   Whereas Kafka is producer-centric, based around partitioning a fire hose of event data into durable message brokers with cursors, supporting batch consumers that may be offline, or online consumers that want messages at low latency.  

RabbitMQ uses the broker itself to maintain state of what's consumed (via message acknowledgements) - it uses Erlang's Mnesia to maintain delivery state around the broker cluster.  Kafka doesn't have message acknowledgements, it assumes the consumer tracks of what's been consumed so far.   Both Kafka brokers & consumers use Zookeeper to reliably maintain their state across a cluster.

RabbitMQ presumes that consumers are mostly online, and any messages "in wait" (persistent or not) are held opaquely (i.e. no cursor).  RabbitMQ pre-2.0 (2010) would fall over if your consumers were too slow, but now it's robust for online and batch consumers - but clearly large amounts of persistent messages sitting in the broker was not the main design case for AMQP in general.   Kafka was based from the beginning around both online and batch consumers, and also has producer message batching - it's designed for holding and distributing large volumes of messages.  

RabbitMQ provides rich routing capabilities with AMQP 0.9.1's exchange, binding and queuing model.   Kafka has a very simple routing approach - in AMQP parlance it uses topic exchanges only.  

Both solutions run as distributed clusters, but RabbitMQ's philosophy is to make the cluster transparent, as if it were a virtual broker.   Kafka makes it explicit, by forcing the producer to know it is partitioning a topic's messages across several nodes, this has the benefit ofpreserving ordered delivery within a partition, which is richer than what RabbitMQ exposes, which is almost always unordered delivery (the AMQP 0.9.1 model says "one producer channel, one exchange, one queue, one consumer channel" is required for in-order delivery).   

Put another way, Kafka presumes that producers generate a massive stream of events on their own timetable - there's no room for throttling producers because consumers are slow, since the data is too massive.  The whole job of Kafka is to provide the "shock absorber" between the flood of events and those who want to consume them in their own way -- some online, others offline - only batch consuming on an hourly or even daily basis.   Kafka can deliver "at least once" semantics per partition (since maintains delivery order), just like RabbitMQ, but it does it in a very different way.  

Performance-wise, if you require ordered durable message delivery, currently it looks like there's no comparison:  Kafka currently blows away RabbitMQ in terms of performance on synthetic benchmarks.   This paper indicates 500,000 messages published per second and 22,000 messages consumed per second on a 2-node cluster with 6-disk RAID 10.   http://research.microsoft.com/en...

Of course this was written by the LinkedIn guys without necessarily expert RabbitMQ input, so YMMV.

Finally, a reminder:  Kafka is an early Apache incubator project.  It doesn't necessarily have all the hard-learned aspects in RabbitMQ. 

Now, a word on AMQP.   Frankly, it seems the standard is a mess.   Officially there is a 1.0 proposed specification that is going through the OASIS standards process.  In practice it is a forked standard, one (0.9.1) supported by vendors, the other (1.0) supported by the working group.    A set of generally available, widely-adopted, production-quality AMQP 1.0 implementations across the major releases (Qpid from Redhat, RabbitMQ, etc.) won't exist until 2013, if ever.

As an external observer with no inside knowledge, here is what it looks like:   the working group spent 5 years on a spec, from 2003 to 2008, culminating in a widely adopted release (0.9.1).   Then a subset of more powerful working group members rewrote the spec by late 2011, completely shifting the focus of the spec from a messaging model to a transport protocol (sort of like TCP++), and declared it 1.0.    So, we have the strange case where the "mature" AMQP is the non-standard 0.9.1 specification and the "immature" AMQP is the actual 1.0 standard.     

This isn't to suggest 1.0 isn't good technology, it likely is, but that it's a much lower-level spec than AMQP intended to be for most of its published life, and is not widely supported yet beyond prototypes and one GA implementation that I know of (IIT SwiftMQ). The RabbitMQ folks have a prototype that has layers the 0.9.1 model on top of 1.0 but have not committed to a GA timeframe.

So, in my opinion, AMQP has lost some of its sheen, as while there's ample evidence it is interoperable from the various connect-fests over the years, the standards politics have delayed the official standard and called into question its widespread support.   On the bright side, one can argue that AMQP has already succeeded in its goal of helping to break the hold TIBCO had on high performance, low latency messaging through 2007 or so.   Now there are many options.  Bet on the broker you choose to use, and don't expect bug-free interoperability for a few years (if ever). Just wanted to add a comment on Stuarts answer. Don't use rabbit if you need clustering for HA their clustering does not actually support network partitions. This is well explained in their documentation.