本文对比了VMware Tanzu RabbitMQ 1.3和Confluent Kafka在VMware Tanzu Kubernetes Grid（TKG）上的性能表现。研究重点关注了Tanzu RabbitMQ 1.3在吞吐量和流处理方面的改进，并分析了Kafka在Kubernetes环境中的部署和性能。研究结果显示，Tanzu RabbitMQ 1.3在低延迟消息传递和高可用性方面表现出色，而Kafka更适合大规模实时数据流处理。文章还提供了关于两者在不同应用场景下的选择建议。

🚀 Tanzu RabbitMQ 1.3：与之前的版本相比，吞吐量提高了30%，尤其是在Quorum Queue场景下。它在处理不同大小的消息时展现出更高的效率，例如，小消息处理速度约为55,634条/秒，大消息处理速度约为15,334条/秒。RabbitMQ Streams在多流设置中达到了每秒247万条消息的处理速度。

💡 Apache Kafka：在测试中，Kafka使用了3个broker，12个分区，并配置了不同的复制设置。在单生产者配置下，Kafka实现了峰值149MB/秒的吞吐量。异步复制在性能和持久性之间取得了平衡。对于1KB的消息，端到端的消息延迟为3毫秒。

⚙️ 架构与部署：两款解决方案均部署在4节点的VMware Tanzu Kubernetes Grid集群上。硬件配置包括每节点24个vCPU、72GB RAM和2TB存储。Kafka利用Strimzi Operator实现自动化和扩展。Tanzu RabbitMQ的warm standby复制确保了高可用性和灾难恢复。

🎯 结论：Tanzu RabbitMQ 1.3适合低延迟消息传递、灵活路由和高可用性需求。Apache Kafka更适用于事件驱动架构和大规模实时数据流。

With the growing demand for scalable and high-performance messaging solutions, VMware Tanzu RabbitMQ 1.3 and Confluent Kafka have emerged as key players in event streaming and message queue technologies. A recent performance study on VMware Tanzu Kubernetes Grid (TKG) highlights key improvements in Tanzu RabbitMQ and provides insights into Apache Kafka’s deployment on Kubernetes. Below, we summarize the key takeaways.

Key Technologies Evaluated

The study focused on the following technologies running on VMware Tanzu Kubernetes Grid:

• Tanzu RabbitMQ 1.3 – An enterprise-grade message broker with improvements in Quorum Queues and streaming capabilities.

• Confluent Kafka – A widely used distributed event streaming platform with support for large-scale real-time data processing.

• Strimzi – A Kubernetes operator for deploying Kafka clusters with ease.

Performance Highlights

Tanzu RabbitMQ 1.3: Significant Throughput Gains

• 30% higher throughput compared to previous versions, especially in Quorum Queue scenarios.

• Increased efficiency in handling messages of different sizes:

• Small messages (~55,634 messages/sec)

• Large messages (~15,334 messages/sec)

• RabbitMQ Streams reached up to 2.47 million messages/sec in a multi-stream setup.

Apache Kafka: High Throughput with Tuning

• Kafka was tested using 3 brokers, 12 partitions, and different replication settings.

• Achieved peak throughput of 149MB/sec with single-producer configurations.

• Replication overhead was noticeable, but asynchronous replication provided a balance between performance and durability.

• End-to-end message latency was 3ms for 1KB messages.

Architecture & Deployment Insights

• Both solutions were deployed on a 4-node VMware Tanzu Kubernetes Grid cluster.

• Hardware Setup:

• 24 vCPUs per node

• 72GB RAM per node

• 2TB storage per node

• Kafka’s Strimzi Operator was leveraged for automation and scaling.

• Tanzu RabbitMQ’s warm standby replication ensured high availability and disaster recovery.

Conclusion: Which One to Choose?

• Tanzu RabbitMQ 1.3 is ideal for low-latency message delivery, flexible routing, and high availability.

• Apache Kafka is better suited for event-driven architectures and large-scale real-time data streaming.

For businesses leveraging VMware Tanzu Kubernetes Grid, both technologies offer powerful messaging and event streaming capabilities, each with distinct advantages depending on the workload.