The framework offers a wide range of connectors to external data sources, supports stateless and stateful transformations, and provides persistence to save the state of computation. It also ensures consistency in computations and comes with LLM helpers for easy integration of LLMs with data pipelines. Pathway requires Python 3.10 or above and can be installed using pip. It can be run locally, using Docker, or on the cloud with Kubernetes. The free version offers "at least once" consistency, while the enterprise version provides "exactly once" consistency.
Key takeaways:
- Pathway is a Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG. It is powered by a scalable Rust engine and can be easily deployed with Docker and Kubernetes.
- Pathway supports a wide range of connectors to external data sources, stateless and stateful transformations, persistence to save the state of computation, and consistency in computations. It also provides LLM helpers for integrating LLMs with data pipelines.
- Pathway can be installed using pip and requires Python 3.10 or above. It can be run locally, using Docker, or on the cloud with Kubernetes. It also provides a monitoring dashboard for tracking the system's performance.
- Pathway is distributed on a BSL 1.1 License which allows for unlimited non-commercial use, as well as use of the Pathway package for most commercial purposes, free of charge. The code in this repository automatically converts to Open Source (Apache 2.0 License) after 4 years.