I'm looking for (simple) examples of problems for which JMS is a good solution, and also reasons why JMS is a good solution in these cases. In the past I've simply used the database as a means of passing messages from A to B when the message cannot necessarily be processed by B immediately.
A hypothetical example of such a system is where all newly registered users should be sent a welcome e-mail within 24 hours of registration. For the sake of argument, assume the DB does not record the time when each user registered, but instead a reference (foreign key) to each new user is stored in the pending_email table. The e-mail sender job runs once every 24 hours, sends an e-mail to all the users in this table, then deletes all the pending_email records.
This seems like the kind of problem for which JMS should be used, but it's not clear to me what benefit JMS would have over the approach I've described. One advantage of the DB approach is that the messages are persistent. I understand that JMS message queues can also be persisted, but in that case there seems to be little difference between JMS and the "database as message queue" approach I've described?
What am I missing? - Don
Answer
JMS and messaging is really about 2 totally different things.
- publish and subscribe (sending a message to as many consumers as are interested - a bit like sending an email to a mailing list, the sender does not need to know who is subscribed
- high performance reliable load balancing (message queues)
See more info on how a queue compares to a topic
The case you are talking about is the second case, where yes you can use a database table to kinda simulate a message queue.
The main difference is a JMS message queue is a high performance highly concurrent load balancer designed for huge throughput; you can send usually tens of thousands of messages per second to many concurrent consumers in many processes and threads. The reason for this is that a message queue is basically highly asynchronous - a good JMS provider will stream messages ahead of time to each consumer so that there are thousands of messages available to be processed in RAM as soon as a consumer is available. This leads to massive throughtput and very low latency.
e.g. imagine writing a web load balancer using a database table :)
When using a database table, typically one thread tends to lock the whole table so you tend to get very low throughput when trying to implement a high performance load balancer.
But like most middleware it all depends on what you need; if you've a low throughput system with only a few messages per second - feel free to use a database table as a queue. But if you need low latency and high throughput - then JMS queues are highly recommended.