Quix Streams client library

Quix Streams v2 is a cloud native library for processing data in Kafka using pure Python. It’s designed to give you the power of a distributed system in a lightweight library by combining the low-level scalability and resiliency features of Kafka with an easy to use Python interface.

Quix Streams has the following benefits:

• No JVM, no orchestrator, no server-side engine.
• Easily integrates with the entire Python ecosystem (pandas, scikit-learn, TensorFlow, PyTorch etc).
• Support for many serialization formats, including JSON (and Quix-specific).
• Support for stateful operations using RocksDB.
• Support for aggregations over tumbling and hopping time windows
• A simple framework with Pandas-like interface to ease newcomers to streaming.
• "At-least-once" Kafka processing guarantees.
• Designed to run and scale resiliently via container orchestration (like Kubernetes).
• Easily runs locally and in Jupyter Notebook for convenient development and debugging.
• Seamless integration with the Quix platform.
• Use Quix Streams to build event-driven, machine learning/AI or physics-based applications that depend on real-time data from Kafka.

See the Quix Streams GitHub page for detailed project information, and all source code.

Next steps

• Quix Streams Quickstart

Check out Quix Streams tutorials for more in-depth examples:

• Tutorial - Word Count
• Tutorial - Anomaly Detection
• Tutorial - Purchase Filtering