Apache Kafka Practice Exam 2025 – The Complete All-in-One Guide for Exam Success!

Having more partitions in Kafka significantly contributes to higher throughput. Throughput is the rate at which messages are processed by the system, and by increasing the number of partitions, Kafka can distribute message consumption across multiple consumers. This allows for parallel processing of messages, as each consumer can read from a different partition simultaneously.

Additionally, having more partitions enhances the system's ability to handle a larger volume of data being produced and consumed, because it effectively allows Kafka to scale horizontally. When the workload increases, more consumers can be added to process partitions independently, leading to improved message handling and faster processing times overall.

In contrast, while having more partitions can also influence availability and latency under certain circumstances, the primary benefit is the capability to increase throughput, allowing businesses to meet the demands of high-speed data scenarios effectively.