Confluent Blog

Apache Kafka is designed to be highly performant, reliable, scalable, and fault tolerant. At the same time, the performance and reliability of a Kafka cluster is highly dependent on the

This post was written by guest blogger Rajiv Kurian from SignalFx. SignalFx is a member of the Confluent partner program. Rajiv is a software engineer with over five years experience building

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

Important: The information in this article is outdated. With recent Kafka versions the integration between Kafka Connect and Kafka Streams as well as KSQL has become much simpler and easier.

I’m really excited to announce a major new feature in Apache Kafka v0.10: Kafka’s Streams API. The Streams API, available as a Java library that is part of the official

For a long time, a substantial portion of data processing that companies did ran as big batch jobs — CSV files dumped out of databases, log files collected at the

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,

When we released Apache Kafka 0.9.0.0, we talked about all of the big new features we added: the new consumer, Kafka Connect, security features, and much more. What we didn’t

Apache Kafka is a high-throughput distributed message system that is being adopted by hundreds of companies to manage their real-time data. Companies use Kafka for many applications (real time stream

Apache Kafka has a data structure called the “request purgatory”. The purgatory holds any request that hasn’t yet met its criteria to succeed but also hasn’t yet resulted in an