64 posts tagged with "New Features"

RabbitMQ 4.1 introduces an exciting new feature: AMQP filter expressions for streams.

This feature enables RabbitMQ to support multiple concurrent clients, each consuming only a specific subset of messages while preserving message order. Additionally, it minimizes network traffic between RabbitMQ and its clients by dispatching only the messages that match the clients' interests.

In this blog post, we’ll explore what AMQP filter expressions are and walk through a simple Java example of how to use them.

This blog post explores use cases of the AMQP 1.0 modified outcome.

We are pleased to announce that RabbitMQ 4.0 supports AMQP 1.0 as a core protocol, providing the following benefits:

• Modernized RabbitMQ to natively support the latest AMQP standard
• Support for more AMQP 1.0 features
• Significantly better AMQP 1.0 performance and scalability compared to RabbitMQ 3.13
• Greater interoperability with other AMQP 1.0 message brokers
• AMQP 1.0 is enabled by default in RabbitMQ 4.0

A previous post gave an introduction to stream filtering, a new and exciting feature in RabbitMQ 3.13. In this post we cover the internals of stream filtering. Knowing the design and implementation will help you to configure and use stream filtering in the most optimal way for your use cases.

Stream filtering is a new feature in RabbitMQ 3.13. It allows to save bandwidth between the broker and consuming applications when those applications need only a subset of the messages of a stream.

Keep reading to find out how stream filtering works and see it in action.

Native MQTT released in RabbitMQ 3.12 has delivered substantial scalability and performance improvements for IoT use cases.

RabbitMQ 3.13 will support MQTT 5.0 and will therefore be the next big step in our journey to make RabbitMQ one of the leading MQTT brokers.

This blog post explains how the new MQTT 5.0 features are used in RabbitMQ.

RabbitMQ 3.11 will bring a feature with one of the coolest names in its history: super streams. Super streams are a way to scale out by partitioning a large stream into smaller streams. They integrate with single active consumer to preserve message order within a partition.

This blog post gives an overview of super streams and the use cases they unlock. Read on to learn more, we value your feedback to make this feature the best it can be.

RabbitMQ 3.11 will bring a noteworthy feature to streams: single active consumer. Single active consumer provides exclusive consumption and consumption continuity on a stream. It is also critical to get the most out of super streams, our solution for partitioning, that provide scalability for streams.

Read on to find out more about single active consumer for streams and don't hesitate to experiment with what is already available: try it, break it, tell us what you like and don't like, what's missing. Your feedback is essential to make this feature the best it can be.

RabbitMQ 3.10 has recently been released and has some major new features which focus on optimizations, performance, and stability.

Release notes page includes information about the specific changes in this version as well as various installation assets. See our upgrade guide for more information about upgrading to 3.10.0.

Let's have a tour!

Quorum queues in RabbitMQ 3.10 provide a safer form of dead lettering that uses at-least-once guarantees for the message transfer between queues. This blog post explains everything you need to know to start using at-least-once dead lettering.

This post also introduces two other RabbitMQ 3.10 features: message Time-To-Live (TTL) for quorum queues and Prometheus metrics for dead lettered messages.