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Schema Registry in Kafka: Avro, JSON and Protobuf | by Ismael Sánchez Chaves | C# Programming | Medium

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Kafka is a distributed and scalable data processing platform that has become one of the most popular tools in data ingestion and processing. Kafka can handle large volumes of data and allows users to process and analyze this data in real time. But, to ensure that the data is processed, it is essential to use a schema to confirm its structure and avoid runtime errors. In this article, we will discover why using a schema registry in Kafka is important and perform a trade-off analysis of the three common data formats: Avro, JSON, and Protobuf. When using data in Kafka, it is important to ensure that it is well-formed and structured. But, if data is stored in Kafka without prior validation, run-time errors may occur that can be costly and difficult to fix. A schema registry provides a way to ensure that data is validated before it is stored in Kafka. A schema registry is a tool used to define and confirm the structure of data that is stored in Kafka. In a schema registry, developers can de

Schema Registry in Kafka: Avro, JSON and Protobuf The importance of having a structured data schema for messaging-based systems Ismael Sánchez Chaves 7 min read · May 15, 2023 -- 2 Listen Share Press enter or click to view image in full size Photo by Andrew Measham on Unsplash Kafka is a distributed and scalable data processing platform that has become one of the most popular tools in data ingestion and processing. Kafka can handle large volumes of data and allows users to process and analyze this data in real time. But, to ensure that the data is processed, it is essential to use a schema to

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