RabbitMQ vs Apache ActiveMQ vs Apache qpid

http://bhavin.directi.com/rabbitmq-vs-apache-activemq-vs-apache-qpid/
6 May, 2010
RabbitMQ vs Apache ActiveMQ vs Apache qpid

Posted by Bhavin Turakhia

We need a simple message queue to ensure asynchronous message passing across a bunch of our server side apps. The message volume is not intended to be very high, latency is not an issue, and order is not important, but we do need to guarantee that the message will be received and that there is no potential for failure irrespective of infrastructure downtime.

Dhruv from my team had taken up the task of researching various persistent message queue options and compiling notes on them. This is a compendium of his notes (disclaimer – this is an outline of our experience, there may be inaccuracies) -
RabbitMQ

General:

    * Some reading on clustering http://www.rabbitmq.com/clustering.html
    * DNS errors cause the DB(mnesia) to crash
    * A RabbitMQ instance won’t scale to LOTS of queues with each queue having fair load since all queues are stored in memory (queue metadata) and also in a clustered setup, each queue’s metadata (but not the queue’’s messages) is replicated on each node. Hence, there is the same amount of overhead due to queues on every node in a cluster
    * No ONCE-ONLY semanamntics. Messages may be sent twice by RabbitMQ to the consumer(s)
    * Multiple consumers can be configured for a single queue, and they will all get mutually exclusive messages
    * Unordered; not FIFO delivery
    * Single socket multiple connections. Each socket can have multiple channels and each channel can have multiple consumers
    * No provision for ETA
    * maybe auto-requeue (based on timeout) — needs investigation
    * Only closing connection NACKs a message. Removing the consumer from that channel does NOT. Hence, all queues being listened to on that channel/connetion are closed for the current consumer
    * NO EXPONENTIAL BACKOFF for failed consumers. Failed messages are re-tried almost immediately. Hence an error in the consumer logic that crashes the consumer while consuming a particular message may potentially block the whole queue. Hence, the consumer needs to be programmed well — error free. However, apps are like; well apps…
    * Consumer has to do rate limiting by not consuming messages too fast (if it wants to); no provision for this in RabbitMQ

Persistence:

    * It will use only it’s own DB — you can’t configure mySQL or any such thing

Clustering and Replication:

    * A RabbitMQ cluster is just a set of nodes running the RabbitMQ. No master node is involved.
    * You need to specify hostname of cluster nodes in a cluster manually on the command line or in a config file.
    * Basic load balancing by nodes in a cluster by redirecting requests to other nodes
    * A node can be a RAM node or a disk node. RAM nodes keep their state only in memory (with the exception of the persistent contents of durable queues which are still stored safely on disc). Disk nodes keep state in memory and on disk.
    * Queue metadata shared across all nodes.
    * RabbitMQ brokers tolerate the failure of individual nodes. Nodes can be started and stopped at will
    * It is advisable to have at least 1 disk node in a cluster of nodes
    * You need to specify which nodes are part of a cluster during node startup. Hence, when A is the first one to start, it will think that it is the only one in the cluster. When B is started it will be told that A is also in the cluster and when C starts, it should be told that BOTH A and B are part of the cluster. This is because if A or B go down, C still knows one of the machines in the cluster. This is only required for RAM nodes, since they don’t persist metadata on disk. So, if C is a memory node and it goes down and comes up, it will have to be manually told which nodes to query for cluster membership (since it itself doesn’t store that state locally).
    * Replication needs to be investigated (check addtl resources) however, from initial reading, it seems queue data replication does not exist
    * FAQ: “How do you migrate an instance of RabbitMQ to another machine?”. Seems to be a very manual process.

Transactions:

    * Any number of queues can be involved in a transaction

Addtl Resources

    * http://somic.org/2008/11/11/using-rabbitmq-beyond-queueing/
    * http://lists.rabbitmq.com/pipermail/rabbitmq-discuss/2009-August/004598.html
    * http://old.nabble.com/Durable-queues—bindings-td22959443.html
    * http://groups.google.com/group/rabbitmq-discuss/msg/e55ae8c821405044
    * RabbitMQ benchmarks (inconclusive): http://www.sheysrebellion.net/blog/2009/06/
    * Some more RabbitMQ benchmarks: http://lists.rabbitmq.com/pipermail/rabbitmq-discuss/2009-October/005189.html
    * If you are still thirsty: http://www.rabbitmq.com/faq.html

Apache qpid

    * Supports transactions
    * Persistence using a pluggable layer — I believe the default is Apache Derby
    * This like the other Java based product is HIGHLY configurable
    * Management using JMX and an Eclipse Management Console application - http://www.lahiru.org/2008/08/what-qpid-management-console-can-do.html
    * The management console is very feature rich
    * Supports message Priorities
    * Automatic client failover using configurable connection properties -
          o http://qpid.apache.org/cluster-design-note.html
          o http://qpid.apache.org/starting-a-cluster.html
          o http://qpid.apache.org/cluster-failover-modes.html
    * Cluster is nothing but a set of machines have all the queues replicated
    * All queue data and metadata is replicated across all nodes that make up a cluster
    * All clients need to know in advance which nodes make up the cluster
    * Retry logic lies in the client code
    * Durable Queues/Subscriptions
    * Has bindings in many languages
    * For the curious: http://qpid.apache.org/current-architecture.html
    * In our tests -
          o Speed: Non-persistent mode: 5000 messages/sec (receive rate), Persistent mode: 1100 messages/sec (receive rate) (send rate will be typically a bit more, but when you start off with an empty queue, they are almost the same for most queue implementations). However, the interesting bit is that even in transacted mode, I saw a lot of message loss if I crashed the broker (by crash I mean Ctrl+C, not even the more -9 signal type of thing that I usually do). Why I stress this is that apps. can usually hook on to Ctrl+C and save data before quitting, but qpid didn’t think it prudent to do so. Out of 1265 messages sent (and committed), only 1218 were received by the consumer (before the inflicted crash). Even on restarting the broker and consumer, that didn’t change. We observed similar behaviour with RabbitMQ in our tests. However, RabbitMQ docs. mention that you need to run in TRANSACTED mode (not just durable/persistent) for guaranteed delivery. We haven’t run that test yet.

Apache ActiveMQ

    * HIGHLY configurable. You can probably do anything you want it to with it
    * You can choose a message store. 4 are already available
    * Has lots of clustering options:
          o Shared nothing Master-Slave: ACK sent to client when master stores the message
          o Shared Database: Acquires a lock on the DB when any instance tries to access the DB
          o Shared Filesystem: Locks a file when accessing the FS. Issues when using NFS with file-locking; or basically any network based file system since file locking is generally buggy in network file systems
    * Network of brokers: This is an option that allows a lot of flexibility. However, it seems to be a very problematic/buggy way of doing things since people face a lot of issues with this configuration
    * Scaling:
          o A. Default transport is blocking I/O with a thread per connection. Can be changed to use nio
          o Horizontal scaling: Though they mention this, the way to achieve this is by using a network of brokers
          o Patitioning: We all know Mr. Partitioning, don’t we. The client decides where to route packets and hence must maintain multiple open connections to different brokers
    * Allows producer flow-control!!
    * Has issues wrt lost/duplicate messages, but there is an active community that fixes these issues
    * Active MQ crashes fairly frequently, at least once per month, and is rather slow - http://stackoverflow.com/questions/957507/lightweight-persistent-message-queue-for-linux
    * Seems to have bindings in many languages(just like RabbitMQ)
    * Has lots of tools built around it 12. JMS compliant; supports XA transactions: http://activemq.apache.org/how-do-transactions-work.html
    * Less performant as compared to RabbitMQ
    * We were able to perform some tests on Apache Active MQ today, and here are the results:
          o Non persistent mode: 5k messages/sec
          o Persistent mode: 22 messages/sec (yes that is correct)
    * There are multiple persisters that can be configured with ActiveMQ, so we are planning to run another set of tests with MySQL and file as the persisters. However, the current default (KahaDB) is said to be more scalable (and offers faster recoverability) as compared to the older default(file/AMQ Message Store: http://activemq.apache.org/amq-message-store.html).
    * The numbers are fair. Others on the net have observed similar results: http://www.mostly-useless.com/blog/2007/12/27/playing-with-activemq/
    * With MySQL, I get a throughput of 8 messages/sec. What is surprising is that it is possible to achieve much better results using MySQL but ActiveMQ uses the table quite unwisely.
    * ActiveMQ created the tables as InnoDB instead of MyISAM even though it doesn’t seem to be using any of the InnoDB features.
    * I tried changing the tables to MyISAM, but it didn’t help much. The messages table structure has 4 indexes !! Insert takes a lot of time because MySQL needs to update 4 indexes on every insert. That sort of kills performance. However, I don’t know if performance should be affected for small (< 1000) messages in the table. Either ways, this structure won’t scale to millions of messages since everyone will block on this one table.