When it was first created, Apache Kafka® had a client API for just Scala and Java. Since then, the Kafka client API has been developed for many other programming languages which enables you to pick the language you want. This freedom of choice ultimately allows you to build an event streaming platform with the language best suited to your business needs.

At Confluent, we have an engineering team dedicated to the development of these Kafka clients. They are constantly adding new features, running functionality, scalability and soak tests, and testing interoperability against different Kafka versions. They make these clients more robust so that you can confidently deploy them in production. Over time Confluent Platform has started providing Kafka clients for the most popular languages, including:

C/C++

Go

Java

.NET

Python

Scala

The open source community also offers Kafka client functionality in an extensive ecosystem of additional programming languages, including:

Erlang

Groovy

Haskell

Kotlin

Lua

Node.js

OCaml

PHP

Ruby

Rust

Tcl

Swift

…and others…

Many of these extensions are built on the C client library for the Kafka protocol called librdkafka, which is itself maintained and supported by Confluent and recently reached v1.0.0. As a result, you can write Kafka client applications in pretty much any language of your choosing. You can run them with an on-prem cluster, or you can use the fully managed services in Confluent Cloud.

Over the past few weeks, we tweeted 12 tech tips, each of which showcased a different language along with a simple example of how to write a producer and consumer to Confluent Cloud. Those examples, plus others, are available to run in GitHub at confluentinc/examples, and we have compiled a list of them below for reference:

We hope this helps you get started with Kafka. If you have any questions or feedback, please don’t hesitate to reach out to us on Slack—there’s a #clients channel, too!

Interested in more?

To learn more, check out Confluent Cloud—a fully managed event streaming service based on Apache Kafka, and listen to the Streaming Audio podcast with Magnus Edenhill on librdkafka 1.0.