Confluent Blog

Using Apache Kafka to decouple microservices is a successful way to build a more resilient, flexible, and scalable architecture. However, it is very common for such microservices to pair with a database. This blog provides a real-world use case on how Kafka replaces a database with ksqlDB.

This article summarizes dynamic versus static consumer group membership in Apache Kafka. It shows how the approaches affect rebalancing in heavy state applications and teaches the user how to choose between the methods.

Who isn’t familiar with Michelin? Whether it’s their extensive product line of tires for nearly every vehicle imaginable (including space shuttles), or the world-renowned Michelin Guide that has determined the standard of excellence for fine dining for over 100 years, you’ve probably heard of them.

Learn how to avoid confusion by implementing co-partitioning.

Learn what windowing is in Kafka Streams and get comfortable with the differences between the main types.

Apache Kafka 3.4 includes early access to ZooKeeper to KRaft migrations, enabling existing Kafka clusters to migrate to KRaft mode and gain scalability and resiliency benefits. Additionally, 3.4 includes several updates to Kafka Core, Streams, Connect, and more.

When I first joined Confluent, I just wanted to make an impact. Of course, everyone wants to grow in their careers, but especially as a proud first-generation American from a Hispanic family, being able to get my engineering degree and find a successful role at a tech company has been deeply

Announcing the latest updates to Confluent’s cloud-native data streaming platform, centralized identity management, enhanced RBAC, Client Quotas, and more.

Confluent is pleased to announce that the Confluent CLI—the leading command-line tool for managing enterprise Kafka deployments and modern data flow—is now source available under the Confluent Community License.

At Treehouse Software, when we speak with customers who are planning to modernize their enterprise mainframe systems, there’s a common theme: they are faced with decades of mission-critical and historical legacy mainframe data in disparate databases,

Building data streaming applications, and growing them beyond a single team is challenging. Data silos develop easily and can be difficult to solve. The tools provided by Confluent’s Stream Governance platform can help break down those walls and make your data accessible to those who need it.

Change data capture (CDC) converts all the changes that occur inside your database into events and publishes them to an event stream. You can then use these events to power analytics, drive operational use cases, hydrate databases, and more. The pattern is enjoying wider adoption than ever before.

I'm excited to share our intent to acquire Immerok! Together, we’ll build a cloud-native service for Apache Flink that delivers the same simplicity, security, and scalability that you expect from Confluent for Kafka.

Capturing tech trends has become a bit tricky these days: whatever industry you’re in, uncertainty abounds. That’s made planning more difficult, but businesses are finding new ways to innovate with emerging technology and respond quickly to fast-changing market conditions.