Confluent Blog

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

Building off part 1 where we discussed an event streaming architecture that we implemented for a customer using Apache Kafka, KSQL, and Kafka Streams, and part 2 where we discussed

Apache Kafka® based applications stand out for their ability to decouple producers and consumers using an event log as an intermediate layer. One result of this is that producers and

This blog post is the third in a series about the Streams API of Apache Kafka, the new stream processing library of the Apache Kafka project, which was introduced in Kafka v0.10.

Apache Kafka (the basis for the Confluent Platform) delivers an advanced stream processing platform for streaming data across AWS, GCP, and Azure at scale, used by thousands of companies. Amazon

At the beginning of June several Confluent team members attended Berlin Buzzwords 2016, where we gave three talks focused on stream processing and distributed computing. These talks, which we summarize

I’m happy to announce that Confluent will be hosting the first Stream Data Hackathon this April 25th in San Francisco! Apache Kafka has recently introduced two new major features: Kafka

I’m pleased to announce the launch of Confluent University: world-class Apache Kafka training now available both onsite and at public venues. Although we’ve been offering onsite training to our customers

When Apache Kafka® was originally created, it shipped with a Scala producer and consumer client. Over time we came to realize many of the limitations of these APIs. For example,

I ran into the schema-management problem while working with my second Hadoop customer. Until then, there was one true database and the database was responsible for managing schemas and pretty