schema_registry_converter VS obm_confluent_blog

The source for the current version of the library can be found on Github. I had to increase the major version because I needed to break the API in order to support all formats supported by the current Schema Registry version. I also added the possibility to set an API key, so it can be used with Confluent Cloud, the cloud offering from Confluent. As part of the latest major refactoring it's also supporting async. This might improve performance of your app, and is also the default for the major Kafka client, more information about why you would want to use async can be found in the async book. The schemas retrieved from the Schema Registry are cached. This way the schema is only retrieved once for each id, and reused for other messages with the same id.

So what is actually the Schema Registry? And how does it help to make sense of binary data? In essence Schema Registry is an application with some Rest endpoints, from which schema's can be registered and retrieved. It used to only support Apache Avro. Later support for Protobuf and JSON Schema was added. Part of the same Github project, and what makes Schema Registry easy to use, is a Collection of Java classes that are used to go from bytes to typed objects and vice versa. There are several classes that support Kafka Streams and ksqlDB next to the more low level Kafka [Producer(https://kafka.apache.org/documentation/#producerapi) and Consumer clients. There are more advanced use cases, but basically you supply the url for the Schema Registry, and the library will handle the rest. For producing data this will mean optionally register a new schema too get the correct id. The consumer will use the encoded id to fetch the schema used to produce the data. It can also be used with other frameworks like Spring Cloud Stream. For example in the Kotlin Command Handler by using the SpecificAvroSerde class. You might need to set additional properties to get this working.