message-queue

I've been asked to evaluate RabbitMQ instead of Kafka but found it hard to find a reason that it's doing something better than Kafka. Does anyone know if it is really better in throughput, durability, latency, or ease-of-use? Lovisa Johansson RabbitMQ is a solid, general purpose message broker that supports several protocols such as AMQP, MQTT, STOMP etc. It can handle high-throughput and common use cases for it is to handle background jobs or as message broker between microservices. Kafka is a message bus optimized for high-ingress data streams and replay. Kafka can be seen as a durable

I am trying to connect to IBM MQ using JMS and client channel definition table (CCDT). I was able to connect successfully to the QueueManager when i specify the MQ properties individually. But when i try to use CCDT file i get the below exception. As client channel definition table (CCDT) is used to determine the channel definitions used by client applications to connect to the queue manager i didnt set QueueManager Name. ERROR> com.ssc.ach.mq.JMSMQReceiver[main]: errorMQJMS2005: failed to create MQQueueManager for '' javax.jms.JMSException: MQJMS2005: failed to create MQQueueManager for '' at

We're using amqplib to publish/consume messages. I want to be able to read the number of messages on a queue (ideally both acknowledged and unacknowledged). This will allow me to show a nice status diagram to the admin users and detect if a certain component is not keeping up with the load. I can't find any information in the amqplib docs about reading queue status. Can someone point me in the right direction? Using pika: import pika pika_conn_params = pika.ConnectionParameters( host='localhost', port=5672, credentials=pika.credentials.PlainCredentials('guest', 'guest'), ) connection = pika

I'm currently working on a project where I need to interface with an IBM system which communicates with the outside world through WebSphere MQ. I need to query the system in a "request-response" fashion using queues, and I will be doing this through a queue manager. However, I can't quite get my head around how this works in practical terms. Say I've got multiple instances of the same application which puts a message onto a request queue. The message gets a CorrelationId and MessageId upon leaving the application, and a ReplyToQueue property gets set on each message to make sure that the queue

I am building a website in CakePHP that processes files uploaded though an XML-RPC API and though a web frontend. Files need to be scanned by ClamAV, thumbnails need to be generated, et cetera. All resource intensive work that takes some time for which the user should not have to wait. So, I am looking into asynchronous processing with PHP in general and CakePHP in particular. I came across the MultiTask plugin for CakePHP that looks promising. I also came across various message queue implementations such as dropr and beanstalkd . Of course, I will also need some kind of background process,

I have an application in Django, that needs to send a large number of emails to users in various use cases. I don't want to handle this synchronously within the application for obvious reasons. Has anyone any recommendations for a message queuing server which integrates well with Python, or they have used on a Django project? The rest of my stack is Apache, mod_python, MySQL. So far I have found no "nice" solution for this. I have some more strict soft realtime requirements (taking a picture from a cardboard box being labeled) so probably one of the approaches is fast enough for you. I assume

We are implementing a REST API, which will kick off multiple long running backend tasks. I have been reading the RESTful Web Services Cookbook and the recommendation is to return HTTP 202 / Accepted with a Content-Location header pointing to the task being processed. (e.g. http://www.example.org/orders/tasks/1234 ), and have the client poll this URI for an update on the long running task. The idea is to have the REST API immediately post a message to a queue, with a background worker role picking up the message from the queue and spinning up multiple backend tasks, also using queues. The