Confluent Blog

At the heart of Apache Kafka® sits the log—a simple data structure that uses sequential operations that work symbiotically with the underlying hardware. Efficient disk buffering and CPU cache usage,

Apache Kafka® is at the heart of the data transportation layer at Pinterest. The amount of data that runs through Kafka has constantly grown over the years. This growth sometimes

One of the most highly requested enhancements to ksqlDB is here! Apache Kafka® messages may contain data in message keys as well as message values. Until now, ksqlDB could only

Consuming messages in parallel is what Apache Kafka® is all about, so you may well wonder, why would we want anything else? It turns out that, in practice, there are

Users of messaging technologies such as JMS and AMQP often use message prioritization so that messages can be processed in a different order based on their importance. It doesn’t take

Apache Kafka® is the de facto standard for event streaming today. The semantics of the partitioned consumer model that Kafka pioneered have enabled scale at a level and at a

Consumer shopping patterns have changed drastically in the last few years. Shopping in a physical store is no longer the only way. Retail shopping experiences have evolved to include multiple

Fraud detection, payment systems, and stock trading platforms are only a few of many Apache Kafka® use cases that require both fast and predictable delivery of data. For example, detecting

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

In Kafka, a topic can have multiple partitions to which records are distributed. Partitions are the unit of parallelism. In general, more partitions leads to higher throughput. However, there are