Quix | The easy-to-use PyFlink alternative

Accelerating test and development at:

Why Quix?

Code and debug in pure Python

Getting PyFlink apps in production takes 6-12 months. Your problems start on day 1 when $ pip install apache-flink returns "No matching distribution found for numpy==1.21.4" Then you’ll need to learn PyFlink Table API for simple operations, DataStream API for more complex use cases. You’ll also find yourself setting up remote debugging, installing pydevd-pycharm, and modifying Flink JVM arguments. Skip that all and use your Python skills to their fullest. Bring in your favorite Python libraries and IDE. Enjoy the ease of developing, testing and debugging your stateful stream processing application in pure Python.
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Simply $ pip install quixstreams to get started and see for yourself.

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Simple stateful operators

Flink is so popular because its been the only reliable solution for stateful stream processing—but many applications don’t need Flink’s full power (and complexity). It’s like trying to crack a nut with a jackhammer. Now there’s a simpler alternative.

Quix provides a lightweight Python library with built-in state management that is designed to run in Docker containers. With Quix you can build and run stateful operators whilst our library takes care of at-least-once processing guarantees, managing state stores, error handling and graceful application shutdown. Windowed calculations lie at the heart of stream processing. Our library includes declarative operators for Sliding, Tumbling, Hopping and Session Windows.

Lightweight Python library

Most real-world applications aren’t working with "big data". So why use a gigantic framework to tackle small problems? Quix applications have a small footprint and run in Docker. If you need more processing power you can scale the container horizontally with replicas, all without changing a line of code.

Because our library is based on Docker, it's easy to add system dependencies or libraries to support your application, that’s not the case with Flink! It’s also super easy to build and deploy your container with Quix. Just a few clicks and we take your code through build and deployment pipelines to run it in a fully managed serverless Kubernetes engine with all the logs and monitoring you need.

Quix has the best CI/CD processes in place to simplify deployment and development for engineers. Way better than any other platform I've used.

Carey McLean

Senior Software Engineer at TIGER 21

Quix Streams is one of the more interesting options because it's more or less Faust 2.0 - pure Python with the annoying bits handled.

Ben Gamble

Field CTO at Ververica

Quix saved us from hiring a whole data engineering team to build a real-time predictive maintenance application.

Jonathan Wilkinson

CTO at Airedale

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A concise, pure Python alternative to PyFlink