Confluent Blog

I’m proud to announce the release of Apache Kafka 3.2.0 on behalf of the Apache Kafka® community. The 3.2.0 release contains many new features and improvements. This blog will highlight

On behalf of the Apache Kafka® community, it is my pleasure to announce the release of Apache Kafka 3.1.0. The 3.1.0 release contains many improvements and new features. We’ll highlight

Classic relational database management systems (RDBMS) distribute and organize data in a relatively static storage layer. When queries are requested, they compute on the stored data and then return results

Kafka Streams is an abstraction over Apache Kafka® producers and consumers that lets you forget about low-level details and focus on processing your Kafka data. You could of course write

Machine learning on real-time data is a powerful combination because you gain direct insights into your data, can make powerful decisions, and consequently improve your business processes and outcomes. It

Companies adopt streaming data and Apache Kafka® because it provides them with real-time information about their business and customers. In practice, the challenge is that this information is spread across

Stream processing has become an important part of the big data landscape, a new programming paradigm bringing asynchronous, long-lived computations to unbounded data in motion. But many people still think

LiveStreams is a YouTube show about Confluent, real-time data streaming, and related technologies that help you maximize data in motion on any cloud. Every episode of LiveStreams will teach you

Apache Kafka ships with Kafka Streams, a powerful yet lightweight client library for Java and Scala to implement highly scalable and elastic applications and microservices that process and analyze data

Apache Kafka® is at the core of a large ecosystem that includes powerful components, such as Kafka Connect and Kafka Streams. This ecosystem also includes many tools and utilities that