Apache Kafka has been a dominant player in the world of real-time data streaming for years, but it's time to consider alternatives. Apache Pulsar has emerged as a powerful and versatile messaging system that offers distinct advantages over Kafka. This talk will explore why Apache Pulsar is better than Apache Kafka for real-time data streaming.

This talk will provide an overview of Apache Pulsar and Apache Kafka and explain the differences between the two platforms. We will then explore the advantages of using Apache Pulsar over Apache Kafka, including better scalability, multi-tenancy, tiered storage, and geo-replication.

We will explore how Apache Pulsar's architecture is designed to easily handle massive data volumes and provide multi-tenancy, enabling multiple departments within your organization to share a single cluster without affecting each other's performance.

We will delve into the more extensive messaging features Apache Pulsar provides, such as support for work queue messaging semantics, key-shared subscriptions, and negative acknowledgments, which are not present in Apache Kafka. Additionally, we will explore Apache Pulsar's support for multiple messaging protocols, including Kafka, MQTT, and AMQP, enabling seamless integration with existing systems.

Finally, we will discuss some real-world use cases of Apache Pulsar, such as stream processing, microservices communication, and real-time analytics, showcasing the benefits that Apache Pulsar can bring to these applications.

Attendees will leave this talk with a clear understanding of why Apache Pulsar is a better choice than Apache Kafka for real-time data streaming. They will gain practical knowledge of how to use Apache Pulsar and how to migrate from Apache Kafka to Apache Pulsar. This talk is suitable for developers, architects, and data engineers interested in exploring alternatives to Apache Kafka and building scalable, reliable, and efficient real-time data streaming systems.