Introduction
If you work with big data, you are probably familiar with both Apache Pulsar and Apache Kafka - two popular messaging systems used to handle data streaming. In this blog, we will compare these two messaging systems in terms of performance, scalability, and architecture.
Performance
When it comes to performance, Apache Pulsar has the upper hand over Apache Kafka. According to Yahoo, Apache Pulsar can handle 40 million messages per second with a latency of less than 10 milliseconds. While Apache Kafka can also handle millions of messages per second, its latency is usually higher than Pulsar's.
Scalability
Both Apache Pulsar and Apache Kafka are designed to be scalable, but Pulsar has a clear advantage thanks to its versatile architecture. Unlike Kafka, Pulsar can be scaled horizontally and vertically, which means you can add more nodes to your cluster or increase processing power of existing nodes on-the-fly.
Architecture
Architecturally, Apache Pulsar and Apache Kafka differ significantly. Kafka follows the publish-subscribe model, where producers publish messages to topics, and consumers subscribe to those topics to receive messages. On the other hand, Pulsar uses a more flexible approach called publish-subscribe-messaging, which allows messages to be published to a topic and consumed from a subscription to that topic.
Pulsar's architecture also allows for complex messaging patterns, such as geo-replication, tiered storage, and hierarchical topics. Additionally, Pulsar supports multiple protocols, including Kafka, which means you can use Pulsar as a drop-in replacement for Kafka without having to modify your existing codebase.
Conclusion
Both Apache Pulsar and Apache Kafka have their strengths and weaknesses, but we hope this comparison gave you a better idea of which messaging system is better suited for your specific use case. If you prioritize performance and scalability, Pulsar might be the way to go. However, if you prefer a messaging system that is simple and easy to use with a strong community and multiple integrations, Kafka might be a better fit.