Message brokers help applications written in different languages or based on different platforms to communicate with each other. They translate data from the messaging protocol of a sending application into the messaging protocol of the receiving application.
One use case would be when a digital platform needs to process data received from many different IoT devices. A message broker reduces the need for complex solutions like APIs to support each operating system and network protocol.
Message brokers use durable queue systems that store and order persistent messages until they can be processed, to guarantee that messages are always delivered.
This is useful in the event of power or system failure. Think of critical data exchanges such as online credit card transactions, flight bookings, or chat systems where you don’t want messages in the queue to disappear.
Asynchronous queuing allows your application to handle high-volume requests. This is great for scaling your product. Message brokers can also route and distribute messages to different queues according to your business logic.
RabbitMQ does all of the above and more. In addition to a wide range of messaging protocols, it supports delivery acknowledgement and flexible routing. This flexibility enables it to efficiently address a wide variety of messaging challenges.
RabbitMQ is the second most popular message queue tool on StackShare. Its main competitor, Apache Kafka, offers less flexibility, but higher throughput, making it more suitable for big data applications than complex e-commerce platforms.
Marketplaces by their very nature need to integrate many different applications to provide the right features and functionalities to their users. Information sent from third-party applications should also be optimised for efficiency and speed so that your platform can scale. This has made message brokers like RabbitMQ more and more indispensable.
CobbleWeb has used RabbitMQ to increase the performance of several marketplaces, such as MobyPark, a parking marketplace that requires reliable real-time status updates.
We also used it to build Fanpass’s ticketing system due its asynchronous queuing system which prioritises tasks to prevent bottlenecks. Thus when a ticket is bought, confirmation emails, Stripe payment validation, and UPS shipping requests are processed at different stages. This avoids conflicts and congestion and allows the platform to scale rapidly.
Zalando used microservice architecture to build their new communication platform which had to process millions of daily messages. REST APIs were considered too slow for the integrations. They ended up using RabbitMQ due to its proven reliability for guaranteed message delivery, flexible routing of messages and support for high availability.
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