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