How to Use Schema Registry and Avro in Spring Boot Applications
TL;DR Following on from How to Work with Apache Kafka in Your Spring Boot Application, which shows how to get started with Spring Boot and Apache Kafka®, here I will
TL;DR Following on from How to Work with Apache Kafka in Your Spring Boot Application, which shows how to get started with Spring Boot and Apache Kafka®, here I will
We know that Apache Kafka® is great when you’re dealing with streams, allowing you to conveniently look at streams as tables. Stream processing engines like ksqlDB furthermore give you the
We are excited to announce the release of Confluent Cloud Schema Registry in general availability (GA), available in Confluent Cloud, our fully managed event streaming service based on Apache Kafka®.
Traditional relational database systems are ubiquitous in software systems. They are surrounded by a strong ecosystem of tools, such as object-relational mappers and schema migration helpers. Relational databases also provide
When it comes to writing a connector, there are two things you need to know how to do: how to write the code itself, and helping the world know about
With the release of Apache Kafka® 2.3 and Confluent Platform 5.3 came several substantial improvements to the already awesome Kafka Connect. Not sure what Kafka Connect is or need convincing
Compliance requirements often dictate that services should not store secrets as cleartext in files. These secrets may include passwords, such as the values for ssl.key.password, ssl.keystore.password, and ssl.truststore.password configuration parameters
Yes, the other definition of event sourcing. 1. Keynotes from leading technologists At Kafka Summit SF, you’ll get to hear incredible keynotes from leading technologists, including Jay Kreps and Neha
We’re excited to announce Tutorials for Apache Kafka®, a new area of our website for learning event streaming. Kafka Tutorials is a collection of common event streaming use cases, with
One of ksqlDB’s most powerful features is allowing users to build their own ksqlDB functions for processing real-time streams of data. These functions can be invoked on individual messages (user-defined
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