To transform data from a Kafka topic to another, you should use which of the following?

To transform data from a Kafka topic to another, you should use which of the following?

• A. Kafka Connect
• B. Kafka Streams
• C. KSQL
• D. Producer API

Answer: (B)

Streaming data between topics is about building a processor that reads from a source topic, applies transformation logic, and writes the results to a target topic in real time. Kafka Streams is the best fit for this because it is a dedicated client library designed to implement exactly that kind of streaming application. It lets you read from one or more input topics, perform a wide range of operations—stateless like map and filter as well as stateful like aggregations, windowing, and joins—and then emit the transformed results to output topics. It manages fault tolerance, offsets, and state backing with Kafka itself, so the processing can scale horizontally and recover cleanly after failures. Kafka Connect, while great for moving data in and out of Kafka and applying simple transformations, isn’t built for complex, application-level streaming logic within your own processor. KSQL (ksqlDB) offers a SQL-based way to transform streams, which is powerful for many scenarios, but it abstracts you away from the full programmatic control that Kafka Streams provides. The Producer API only sends messages and has no built-in mechanism for reading or transforming streams.

Streaming data between topics is about building a processor that reads from a source topic, applies transformation logic, and writes the results to a target topic in real time. Kafka Streams is the best fit for this because it is a dedicated client library designed to implement exactly that kind of streaming application. It lets you read from one or more input topics, perform a wide range of operations—stateless like map and filter as well as stateful like aggregations, windowing, and joins—and then emit the transformed results to output topics. It manages fault tolerance, offsets, and state backing with Kafka itself, so the processing can scale horizontally and recover cleanly after failures.

Kafka Connect, while great for moving data in and out of Kafka and applying simple transformations, isn’t built for complex, application-level streaming logic within your own processor. KSQL (ksqlDB) offers a SQL-based way to transform streams, which is powerful for many scenarios, but it abstracts you away from the full programmatic control that Kafka Streams provides. The Producer API only sends messages and has no built-in mechanism for reading or transforming streams.