Mastering Kafka Schema Basics: A Comprehensive Guide
The popular open-source event store and stream processing platform Apache Kafka has developed into the industry standard for data streaming
With IBM Event Streams on IBM Cloud, a fully managed Kafka service, developer Michael Burgess offers an understanding of schemas and schema management to enhance your event-driven applications
It is unable to see what kinds of data are being sent or received or what kinds of data it might contain. Kafka doesn’t go into your messages’ metadata
Decoupling producing and consuming applications so they interact through a Kafka topic rather than directly is one of Kafka’s features
Within the context of Kafka, a schema explains the data structure of a message. It outlines the types of fields that are required in every message as well as the fields that must be present
By acting as a repository for managing and validating schemas inside your Kafka cluster, a schema registry helps your cluster
In your Kafka context, a schema registry is effectively an agreement about the structure of your data. You may prevent typical mistakes in application development
A schema registry, which offers an easy way to track and audit changes to your topic data formats
Makes it easier to comply with data governance and data quality requirements by acting as a store of versions of schemas used inside a Kafka cluster, both past and present