How to Turn a REST API Into a Data Stream with Kafka and Flink

REST APIs are widely used for delivering current data because they are familiar, scalable, supported by mature tools, and flexible enough to handle both read and write operations, although consumers must generally work with the API formats providers offer. Using live flight data from the OpenSky Network, the example demonstrates how an HTTP Source Connector can ingest REST API responses into an Apache Kafka topic in Confluent Cloud, where Flink SQL transforms nested, array-based flight records into a cleansed, self-documenting stream with named fields and correctly cast data types. The process uses operations including CROSS JOIN UNNEST to expand arrays into rows, RTRIM to remove trailing whitespace, and CAST and timestamp conversion to standardize values. Processing data on the backend rather than in clients can improve security, maintainability, and usability, particularly when sensitive information or changing schemas are involved. The approach also addresses unreliable REST services through configurable connector retries, allowing Kafka and Flink SQL to bridge REST-based data sources with streaming pipelines.

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