RabbitMQ Streams are designed for high-throughput scenarios, but what happens when your ingress rate is low? Low message rates can significantly impact delivery performance, reducing message consumption rates by an order of magnitude. RabbitMQ 4.2 introduces an optimization that dramatically improves delivery rates for low-throughput streams, benefiting all supported protocols.
RabbitMQ 4.1 is around the corner (update: has been released) and, as usual, apart from new features, we have made some internal changes that should provide better performance.
There are at least 4 notable changes:
This blog post outlines ten advantages of AMQP 1.0 flow control over AMQP 0.9.1, supported by two benchmarks demonstrating significant performance gains. Additionally, we delve into the powerful AMQP 1.0 flow control primitives and how they are used in RabbitMQ.
This blog post demonstrates that native AMQP 1.0 in RabbitMQ 4.0 provides significant performance and scalability improvements compared to AMQP 1.0 in RabbitMQ 3.13.
Additionally, this blog post suggests that AMQP 1.0 can perform slightly better than AMQP 0.9.1 in RabbitMQ 4.0.
We've already announced two major new features of 3.13 in separate blog posts:
This post focuses on the changes to the classic queues in this release:
RabbitMQ 3.12 will be released soon with many new features and improvements.
This blog post focuses on the the performance-related differences.
The most important change is that the lazy mode for classic queues is now the standard behavior (more on this below).
The new implementation should be even more memory efficient
while proving higher throughput and lower latency than both lazy or non-lazy implementations did in earlier versions.
For even better performance, we highly recommend switching to classic queues version 2 (CQv2).
RabbitMQ's core protocol has been AMQP 0.9.1. To support MQTT, STOMP, and AMQP 1.0, the broker transparently proxies via its core protocol. While this is a simple way to extend RabbitMQ with support for more messaging protocols, it degrades scalability and performance.
In the last 9 months, we re-wrote the MQTT plugin to not proxy via AMQP 0.9.1 anymore. Instead, the MQTT plugin parses MQTT messages and sends them directly to queues. This is what we call Native MQTT.
The results are spectacular:
Native MQTT turns RabbitMQ into an MQTT broker opening the door for a broader set of IoT use cases.
Native MQTT ships in RabbitMQ 3.12.
Recent Erlang/OTP versions ship with Linux perf support. This blog post provides step by step instructions on how you can create CPU and memory flame graphs in RabbitMQ to quickly and accurately detect performance bottlenecks. We also provide examples of how flame graphs have helped us to increase message throughput in RabbitMQ.
RabbitMQ 3.10 was released on the 3rd of May 2022, with many new features and improvements. This blog post gives an overview of the performance improvements in that release. Long story short, you can expect higher throughput, lower latency and faster node startups, especially with large definitions files imported on startup.
