Technology

This blog series explores how technologies like generative AI, RAG, VectorDBs, and DSPs can work together to provide the freshest and most actionable data. Part 1 lays the foundation for understanding how data fuels AI, and why having the right data at the right time is essential for success.

Continuing our discussion of JVM microservices frameworks used with Apache Kafka, we introduce Micronaut. Let’s integrate a Micronaut microservice with Confluent Cloud—using Stream Governance—and test the Kafka integration with TestContainers.

Adding queue support to Kafka opens up a world of new possibilities for users, making Kafka even more versatile. By combining the strengths of traditional queue systems with Kafka’s robust log-based architecture, customers now have a solution that can handle both streaming and queue processing.

Confluent launches the general availability of a new JavaScript client for Apache Kafka®, a fully supported Kafka client for JavaScript and TypeScript programmers in Node.js environments.

This blog details an end-to-end real-time prediction project leveraging the combined capabilities of Confluent Cloud stacks and Google Cloud Vertex AI. This project aims to deliver a streamlined solution for real-time prediction applications, catering to the evolving needs and challenges of moder...

Tableflow can seamlessly make your Kafka operational data available to your AWS analytics ecosystem with minimal effort, leveraging the capabilities of Confluent Tableflow and Amazon SageMaker Lakehouse.

This blog announces the general availability of Confluent Platform 7.8 and its latest key features: Confluent Platform for Apache Flink® (GA), mTLS Identity for RBAC Authorization, and more.

With both Confluent and Amazon Redshift supporting mTLS, streaming developers and architects are able to take advantage of a native integration that allows Amazon Redshift to query Confluent Cloud topics.

Since its inception, change data capture (CDC) technology has significantly evolved, transitioning from a tool primarily used for database replication and migration to a cornerstone of real-time streaming. Its pivotal role in modern data architectures enables businesses to harness real-time data...

Dive into the inner workings of brokers as they serve data up to a consumer.

We are proud to announce the release of Apache Kafka 3.9.0. This is a major release, the final one in the 3.x line. This will also be the final major release to feature the deprecated Apache ZooKeeper® mode. Starting in 4.0 and later, Kafka will always run without ZooKeeper.

Building a headless data architecture requires us to identify the work we’re already doing deep inside our data analytics plane, and shift it to the left. Learn the specifics in this blog.

A headless data architecture means no longer having to coordinate multiple copies of data, and being free to use whatever processing or query engine is most suitable for the job. This blog details how it works.