Fancy stream processing made operationally mundane
- message-queue
- stream-processing
- streaming-data
- message-bus
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Fancy stream processing made operationally mundane
Python Stream Processing
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.
The live data layer for apps and AI agents. Create up-to-the-second views into your business, just using SQL
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Asynchronous Python framework for event-driven services. A thin client for Kafka, RabbitMQ, NATS, Redis and MQTT with full access to native broker features, plus AsyncAPI docs, in-memory tests and observability out of the box.
Ultra-high performance reactive programming
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High-performance time-series aggregation for PostgreSQL
Project Flogo is an open source ecosystem of opinionated event-driven capabilities to simplify building efficient & modern serverless functions, microservices & edge apps.
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.
Python Stream Processing
Python Stream Processing. A Faust fork
Stream Processing and Complex Event Processing Engine
Python Streaming DataFrames for Kafka
High performance Rust stream processing engine seamlessly integrates AI capabilities, providing powerful real-time data processing and intelligent analysis.
Real-time stream processing for python
A compatibility layer for event-driven abstractions
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Esper Complex Event Processing, Streaming SQL and Event Series Analysis
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HStreamDB is an open-source, cloud-native streaming database for IoT and beyond. Modernize your data stack for real-time applications.
Streaming reactive and dataflow graphs in Python