Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
- batch-processing
- kafka
- pathway
- python
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Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
Hazelcast is a unified real-time data platform combining stream processing with a fast data store, allowing customers to act instantly on data-in-motion for real-time insights.
🦀 event stream processing for developers to collect and transform data in motion to power responsive data intensive applications.
Compositional, streaming I/O library for Scala
The fastest unified streaming SQL Engine in a single C++ binary. ⚡ Millisecond latency. 100+ GB/s throughput. Continuously compute stateful context from streams, logs, metrics, events, and CDC.
Lightweight data stream processing engine for IoT edge
Stream Processing and Complex Event Processing Engine
A compatibility layer for event-driven abstractions
Esper Complex Event Processing, Streaming SQL and Event Series Analysis
🏎️ Streams & Reactive Programming paradigm for Go: declarative and composable API for event-driven applications
Compositional pipelines
Real-time decision features without streaming infra. Turn live events into product reflexes — no Kafka, no Flink, no feature store.
Multi-core Window-Based Stream Processing Engine
Lightweight SQL-based stream processing engine for IoT edge.
Parallelize _anything_ //
Simple yet powerful live data computation framework.
Simple yet powerful live data computation framework. C++ port of Scramjet framework.