Apache Pulsar vs Confluent: What are the differences?

Apache Pulsar and Confluent both play crucial roles in stream processing and messaging, but they have key differences that set them apart.

1. Architecture: Apache Pulsar is designed as a multi-tenant, high-performance solution with a separation of compute and storage layers, enabling scalability and flexibility. On the other hand, Confluent is built as an event streaming platform based on Apache Kafka, emphasizing the use of Kafka Connect and Kafka Streams for stream processing.

2. Messaging Model: Apache Pulsar supports both traditional queuing and publish-subscribe messaging paradigms, providing more flexibility for different use cases. In contrast, Confluent focuses primarily on the publish-subscribe model, with Kafka's topic-based messaging system at its core.

3. Integration: Apache Pulsar is more interoperable with external systems and tools, offering robust connectors for seamless integration with various databases and services. Confluent, being tightly integrated with Kafka, excels in ecosystem compatibility and seamless interactions within the Kafka ecosystem.

4. Ease of Use: Confluent provides extensive tooling and support for managing Kafka clusters and stream processing applications, making it easier for users to set up and maintain their data pipelines. In comparison, while Apache Pulsar offers similar functionalities, it may require more configuration and management effort due to its distributed nature.

5. Scalability: Apache Pulsar's architecture enables easy horizontal scalability by adding more instances to the compute and storage layers independently, providing better resource utilization and performance optimization. Confluent also offers scalability options, but its design is more closely tied to Kafka's distributed architecture, which may require additional considerations for scaling.

In Summary, Apache Pulsar and Confluent differ in their architecture, messaging model, integration capabilities, ease of use, and scalability options.