Confluent Blog

Now that we’ve learned about the processing layer of Apache Kafka® by looking at streams and tables, as well as the architecture of distributed processing with the Kafka Streams API […]

Part 2 of this series discussed in detail the storage layer of Apache Kafka: topics, partitions, and brokers, along with storage formats and event partitioning. Now that we have this […]

Part 1 of this series discussed the basic elements of an event streaming platform: events, streams, and tables. We also introduced the stream-table duality and learned why it is a […]

This four-part series explores the core fundamentals of Kafka’s storage and processing layers and how they interrelate. In this first part, we begin with an overview of events, streams, tables, […]

Introduction What’s great about the Kafka Streams API is not just how fast your application can process data with it, but also how fast you can get up and running […]

Ever wondered what it’s like to run Kafka in production? What about building and deploying microservices that process streams of data in real-time, at large scale?  Or, maybe just the […]

The Google Dataflow team has done a fantastic job in evangelizing their model of handling time for stream processing. Their key observation is that in most cases you can’t globally […]

I’m happy to announce Confluent will be hosting another Kafka Summit Hackathon on May 7th in New York City! The free hackathon will take place a day prior to Kafka […]

This blog post is the second 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. Current […]

This blog post is the first 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. Current […]