Quix Announces New Open Source Library to Process Streaming Data in Python

Quix, a real-time telemetry data platform founded by Formula 1 data engineers, is open-sourcing their data streaming library called “Quix Streams” on the platform’s three-year anniversary.
Quix Streams makes it quick and easy to build real-time applications that process high volumes of telemetry data when developers need a quick response and guaranteed reliability at scale.
The library is written in C#, available in Python, and designed to be easily extended to other programming languages.
It includes many useful features, such as:
Software, ML, and Data Engineers can now manage the ever-greater volume and velocity of time-series data with ease, as Quix Streams makes streaming data more easily accessible.
“Our goal is to empower engineers and data scientists from all parts of the data ecosystem,” said Founder and CTO Tomas Neubauer. “With the release of Quix Streams, we want Python developers to enjoy the scalability and resiliency of Java and Scala-based technologies that have been traditionally used to process data streams but without the hassle of working with JVM environments. We also believe that open-sourcing our library will encourage collaboration and innovation across the industry, and we’re excited to see what people will do with it.”
In the next version, the Quix team plans to introduce a new feature called “streaming data frames” that simplifies stateful stream processing for users coming from a batch processing environment.
Learn more about Quix by visiting quix.io or reading the developer documentation at docs.quix.io. To book a product demo, reach out to an expert.
Source: Quix