Python Stream Processing
- kafka-streams
- kafka
- python
- asyncio
Repository Index
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Apache Storm
- storm
- apache
- distributed
- streaming
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.
- java
- hazelcast
- in-memory
- big-data
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.
- cloud-native
- streaming
- rust
- real-time
Distributed stream processing engine in Rust
Python Stream Processing. A Faust fork
Distributed Stream Processing
- stream-processing
- stream-processor
- stream-processing-engine
- pony-language
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
- python
- python3
- stream
- data-pipeline
Haskell distributed stream processing with exactly-once semantics
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.
- nodejs
- stream-processing
- transform-as-a-service
- real-time
Stream Processing Made Easy
- machine-learning
- reactive-programming
- kafka
- reactive-systems