Apache Kafka is an open-source and distributed event store stream-processing platform. It can be used to gather application logs on a large scale. Confluent Kafka is a data streaming platform that includes most of Kafka’s functionality and a few additional ones. Its primary goal is not just to provide a pub-sub platform, but also to provide data storage and processing services.

What is Apache Kafka?

Apache Kafka can publish, subscribe to, store, and process streams of records in real time and decouple data streams and systems. Apache Kafka is easy to use delivers real-time feedback and offers a low latency. This is because it separates the message and allows the customer to absorb it a time. Kafka allows you to connect to external systems and provides the Kafka Streams libraries for stream processing applications. Kafka uses a binary TCP-based protocol that is designed for efficiency and depends on a message set concept that automatically groups messages to reduce network roundtrip time.

What is Confluent Kafka?

Confluent Kafka serves as a data streaming platform that includes almost all of Kafka’s functionality and a few other things. Its primary goal is not just to provide a pub-sub platform, but also to provide data storage and processing services. It allows different applications to limit data-parallel execution, which occurs when one record executes without waiting for the previous record’s output. As a result, a distributed streaming platform allows users to streamline the streaming process and execute it in parallel. The platform is underpinned by fully uptime SLA and committer-driven expertise, which provides support and services from a team with over one million hours of Kafka technical knowledge.

Difference between Apache Kafka and Confluent Kafka