Pulsar vs. RabbitMQ vs. NATS Performance
In our 2023 test comparing the performance of Pulsar, RabbitMQ, and NATS JetStreams, we found:
Pulsar showed a higher peak consumer throughput of 2.6M msg/s compared to RabbitMQ’s 48K msg/s and NATS JetStream’s 160K msg/s.
Pulsar was able to support a producer rate of 1M msg/s — 33x faster than RabbitMQ and 20x faster than NATS JetStream.
Pulsar outperformed RabbitMQ during the backlog drain with a stable publish rate of 100K msg/s, while RabbitMQ's publish rate dropped by more than 50%
Pulsar's p99 latency is 300x better than RabbitMQ and 40x better than NATS JetStream at a topic count of 50.
Pulsar demonstrated better scalability, handling increasing loads and numbers of topics more effectively than NATS JetStream and RabbitMQ.
RabbitMQ can process 20K msg/s, and NATS JetStream can support 30K msg/s for topic counts up to 500, while Pulsar can achieve 1M msg/s up to 50 topics and provided a publish rate above 200K msg/s for up to 20K topics.
Pulsar provides a multi-layer architecture that decouples compute and storage. Pulsar’s design allows organizations to elastically scale compute independently from storage and achieve different levels of resource isolation. Pulsar’s architecture offers key benefits, including:
Pulsar has the flexibility to serve a wide range of messaging and event streaming use cases in one platform. Users can deploy Pulsar as a centralized messaging platform as well as for batch and event streaming. Pulsar is inherently able to serve a wide range of messaging use cases because it can send and retain. For example, Pulsar can ingest, process, and analyze real-time data streams.
In comparison, RabbitMQ primarily targets asynchronous pub-sub use cases, with no event streaming support. RabbitMQ can only serve simple message queuing and routing use cases, i.e. send and forget type of messaging use cases. RabbitMQ is good for long-running tasks, running background jobs, and request-response between and within applications.
NATS is good for simple pub/sub and queue-based messaging patterns like IoT applications where each device has limited resources and connectivity.
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