Stream Kafka Topic to the Iceberg Tables with Zero-ETL
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For a long time, Kafka has been the standard for distributed messaging. It is heavily used in operational services where a service doesn’t have to communicate directly with hundreds of other services.
Many companies rely on the Kafka protocol. People also use Kafka to ingest data into an analytics repository, which can be a data warehouse, a data lake, or a lakehouse. Suppose we want to build an analytics dashboard from Kafka messages, we must build a pipeline with Kafka Connect, Spark, or Flink to consume messages from the Kafka topic, write them into files, and push these files to the data lake.
Besides the emergence of using object storage for Kafka, ongoing efforts are being made to help organizations streamline the process of converting Kafka’s topic messages to Iceberg tables.
