The Quix blog

Learn how Streaming DataFrames can simplify real-time data processing in Python with a familiar DataFrame approach.

Quix 2.0 is here 🚀 Designed around the concept of Infrastructure-as-Code, Quix 2.0 makes it easier to build and run reliable, powerful event-streaming applications that scale, with a single source of truth powered by Git.

Lightweight, powerful, no JVM and no need for separate clusters of orchestrators. Here’s a look at our next-gen streaming library for C# and Python developers including feature summaries, code samples, and a sneak peek into our roadmap.

Why we've partnered with MMC Ventures, Project A Ventures and Passion Capital to accelerate our growth.

Bring any type of data into the Quix platform. Here’s how to use the APIs when the SDK doesn’t fit.

When, why, and how to contribute code samples to the Quix library.

Transform big data fast. Now more people can harness the power of data stream processing and develop their own projects.

Dig into our most-read, most-shared content from 2021: our best data stream processing tutorials, explainers and research.

The platform accelerates time to market for live data-driven products. New connectors to live data streams ensure flawless performance in real world production environments.

Today, my co-founders Tomas Neubauer, Peter Nagy, Patrick Mira Pedrol and I are excited to introduce Quix, the cloud data platform we started developing just over a year ago.

Announcing Quix, the first in-memory data stream processing platform for Python professionals looking to build real-time data applications.