Python Stream Processing
- kafka-streams
- kafka
- python
- asyncio
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Python Stream Processing
Apache Storm
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
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.
🦀 event stream processing for developers to collect and transform data in motion to power responsive data intensive applications.
Distributed stream processing engine in Rust
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
Ruby and Rails efficient Kafka processing framework
A lightweight stream processing library for Go
Python Stream Processing. A Faust fork
👜 Tiny and fast reactive/iterable programming library
Stream Processing and Complex Event Processing Engine
Distributed Stream Processing
A compatibility layer for event-driven abstractions
Build platforms that flexibly mix SQL, batch, and stream processing paradigms
HStreamDB is an open-source, cloud-native streaming database for IoT and beyond. Modernize your data stack for real-time applications.
.NET Stream Processing Library for Apache Kafka 🚀
Streaming reactive and dataflow graphs in Python
Machine is a workflow/pipeline library for processing data
Haskell distributed stream processing with exactly-once semantics
Multi-core Window-Based Stream Processing Engine
Scramjet Platform is a distributed runtime supervisor that can run data processing programs called Sequences and manage local resources on any Linux server, Docker on small edge servers, and even large-scale Kubernetes clusters in the cloud or datacenters without exposing network ports to the public internet.