Confluent Blog

One of the most highly requested enhancements to ksqlDB is here! Apache Kafka® messages may contain data in message keys as well as message values. Until now, ksqlDB could only

How do you process IoT data, change data capture (CDC) data, or streaming data from sensors, applications, and sources in real time? Apache Kafka® and Apache Spark® are widely adopted

When operating cloud infrastructure, “time is money” is more than a cliché—it is interpreted literally as every processing second stacks up on the monthly bill. ksqlDB strives to reduce these

In the article Should You Put Several Event Types in the Same Kafka Topic?, Martin Kleppmann discusses when to combine several event types in the same topic and introduces new

Event stream processing solves many business challenges, from big data ingestion and data integration, to real-time data processing and IoT. It gives you the ability to analyze big data streams

The Elasticsearch sink connector helps you integrate Apache Kafka® and Elasticsearch with minimum effort. You can take data you’ve stored in Kafka and stream it into Elasticsearch to then be

Although starting out with one Confluent Schema Registry deployment per development environment is straightforward, over time, a company may scale and begin migrating data to a cloud environment (such as

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

When you build microservices architectures, one of the concerns you need to address is that of communication between the microservices. At first, you may think to use REST APIs—most programming

Part 1 of this blog series introduced a self-paced tutorial for developers who are just getting started with stream processing. The hands-on tutorial introduced the basics of the Kafka Streams