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Pathway is an open-source framework designed for building real-time data applications using reactive and declarative paradigms. It enables seamless integration of live data streams and structured data into analytical pipelines with minimal latency. Pathway is especially well-suited for scenarios like financial analytics, IoT, fraud detection, and logistics, where high-velocity and continuously changing data is the norm. Unlike traditional batch processing frameworks, Pathway continuously updates the results of your data logic as new events arrive, functioning more like a database that reacts in real-time. It supports Python, integrates with modern data tools, and offers a deterministic dataflow model to ensure reproducibility and correctness.
Features
- Real-time stream processing with low-latency updates
- Declarative programming model using Python
- Deterministic and reproducible dataflows
- Integration with Kafka, PostgreSQL, and webhooks
- Time-travel and replayability of data events
- Native support for joins, filtering, and transformations
- Built-in observability and monitoring tools
- Supports hybrid batch and stream use cases
Project Samples
