Apache Kafka is a distributed event streaming platform designed for high-throughput, real-time data pipelines and applications. In a streaming ETL (Extract, Transform, Load) workflow, Kafka often serves as the backbone for reliable data ingestion, processing, and distribution. Its scalability and fault-tolerance make it a vital component for handling continuous data streams across diverse systems.

• Real-Time Data Ingestion: Serve as the primary source for capturing and buffering high-velocity data from various producers.

• Distributed Processing: Enable transformation of streaming data through Kafka Streams or integration with processing frameworks like Apache Flink or Spark.
• Event-Driven Workflows: Trigger ETL workflows based on specific events, ensuring timely transformations and data delivery.
• Data Distribution: Act as a central hub for distributing transformed data to multiple destinations, such as databases, data lakes, or analytics platforms.