KA

Kafka Streams

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description Kafka Streams Overview

Kafka Streams is a client library that enables stream processing on Apache Kafka. It provides high-performance, fault-tolerant stream processing capabilities with easy integration into existing applications. Ideal for building real-time data pipelines and event-driven architectures.

help Kafka Streams FAQ

Is Kafka Streams a separate server or a client library?

Kafka Streams is a client library embedded in a Java or Scala application, not a separate processing cluster. Its input and output data are stored in Apache Kafka, and additional application instances provide parallel scaling. [Apache Kafka introduction](https://kafka.apache.org/43/streams/introduction/)

What is the difference between a KStream and a KTable?

A KStream represents an ongoing sequence of events, while a KTable represents the latest value for each key in a changing table. Kafka Streams uses both abstractions for event processing, aggregation, and stream-table joins. [Kafka Streams core concepts](https://kafka.apache.org/35/streams/core-concepts/)

Can Kafka Streams perform joins, aggregations, and windowing?

Yes, the Kafka Streams DSL supports transformations such as map, filter, joins, aggregations, and time windows. Stateful operations use local state stores, which Kafka Streams can restore after failure. [Kafka Streams core concepts](https://kafka.apache.org/33/streams/core-concepts/)

Does Kafka Streams support exactly-once processing?

Yes, current Kafka documentation lists exactly-once processing through the processing.guarantee setting, while at-least-once remains the default. The current setting name for exactly-once version 2 is exactly_once_v2. [Kafka Streams configuration](https://kafka.apache.org/42/streams/developer-guide/config-streams/)

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