Apache Kafka Practice

Kafka is designed to be a versatile messaging system that can handle various data formats. The correct choice indicates that it supports multiple formats including JSON, Avro, and Protobuf. These formats are commonly used in data serialization due to their efficiency and ability to handle complex data structures.

JSON is straightforward for developers to read and write, making it a popular choice for web applications and APIs. Avro is favored in big data environments for its compact binary format and schema evolution capabilities, which allows the structure of the data to change over time without breaking compatibility with older readers. Protobuf, developed by Google, is known for its efficiency and performance, particularly in remote procedure calls and data serialization for communication between services.

This capability to handle diverse formats enables Kafka to be more adaptable and suitable for a wide range of applications, from log aggregation to stream processing and data pipelines, thus enhancing its utility in modern data architectures. The other options do not reflect the broad compatibility that Kafka offers, limiting the scope of data formats to just a few or specific types, which undermines its flexibility in handling different data sources effectively.