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Kafka Schema Evolution: A Guide to the Confluent Schema Registry
Manage episode 423049541 series 3474159
This story was originally published on HackerNoon at: https://hackernoon.com/kafka-schema-evolution-a-guide-to-the-confluent-schema-registry.
Learn Kafka Schema Evolution: Understand, Manage & Scale Data Streams with Confluent Schema Registry. Essential for Data Engineers & Architects.
Check more stories related to programming at: https://hackernoon.com/c/programming. You can also check exclusive content about #kafka, #apache-kafka, #schema, #schema-evolution, #data-streaming, #data-engineering, #data-architecture, #json-scheme, and more.
This story was written by: @aahil. Learn more about this writer by checking @aahil's about page, and for more stories, please visit hackernoon.com.
Schema evolution is the process of managing changes to the structure of data over time. In Kafka, it means handling the modifications to the format of the messages being produced and consumed in Kafka topics. As applications and business requirements evolve, the data they generate and consume also change. These changes must be managed carefully to ensure compatibility between producers and consumers of the data.
346 פרקים
Manage episode 423049541 series 3474159
This story was originally published on HackerNoon at: https://hackernoon.com/kafka-schema-evolution-a-guide-to-the-confluent-schema-registry.
Learn Kafka Schema Evolution: Understand, Manage & Scale Data Streams with Confluent Schema Registry. Essential for Data Engineers & Architects.
Check more stories related to programming at: https://hackernoon.com/c/programming. You can also check exclusive content about #kafka, #apache-kafka, #schema, #schema-evolution, #data-streaming, #data-engineering, #data-architecture, #json-scheme, and more.
This story was written by: @aahil. Learn more about this writer by checking @aahil's about page, and for more stories, please visit hackernoon.com.
Schema evolution is the process of managing changes to the structure of data over time. In Kafka, it means handling the modifications to the format of the messages being produced and consumed in Kafka topics. As applications and business requirements evolve, the data they generate and consume also change. These changes must be managed carefully to ensure compatibility between producers and consumers of the data.
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