Cross-platform, customizable ML solutions for live and streaming media.
A high-performance observability data pipeline.
QuestDB is a high performance, open-source, time-series database
Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
Event streaming platform for agentic AI. Continuously ingest, transform, and serve event streams in real time, at scale.
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.
Distributed stream processing engine in Rust
The Fastest Unified Streaming SQL Engine in a Single C++ Binary. β‘ Millisecond latency. 100+ GB/s throughput. Continuously compute real-time context from streams, logs, metrics, events, and CDC.
Fancy stream processing made operationally mundane
The live data layer for apps and AI agents. Create up-to-the-second views into your business, just using SQL
Upserts, Deletes And Incremental Processing on Big Data.
π Online machine learning in Python
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.
π¦ event stream processing for developers to collect and transform data in motion to power responsive data intensive applications.
Fast, Simple and a cost effective tool to replicate data from Postgres to Data Warehouses, Queues and Storage
a curated list of awesome streaming frameworks, applications, etc
Kubernetes-native platform to run massively parallel data/streaming jobs
Python Stream Processing
Stream Processing and Complex Event Processing Engine
Python Streaming DataFrames for Kafka
Zero-cost & Type-safe Reactive Extensions for Rust. Supports both high-performance single-threaded (Local) and thread-safe (Shared) contexts. WASM & Tokio ready.
Framework for building Event-Driven Microservices
Build platforms that flexibly mix SQL, batch, and stream processing paradigms
Lightweight real-time big data streaming engine over Apache Pekko
Apache StreamPipes - A self-service (Industrial) IoT toolbox to enable non-technical users to connect, analyze and explore IoT data streams.
Low-code tool for automating actions on real time data | Stream processing for the users.
Microservices library - scalecube-services is a high throughput, low latency reactive microservices library built to scale. It features: API-Gateways, service-discovery, service-load-balancing, the architecture supports plug-and-play service communication modules and features. built to provide performance and low-latency real-time stream-processing
Play any radios around the globe right from the terminal :zap:
All the things a panda needs
Platform for Situated Intelligence
ZenWeaver enables real-time, distributed audio processing via stream-processing architecture, auto-scaling, and a robust engine within a scalable platform.
Redpanda is a streaming data platform for developers. Kafka API compatible. 10x faster. No ZooKeeper. No JVM!
Fast and Lightweight Logs, Metrics and Traces processor for Linux, BSD, OSX and Windows
A Python stream processing engine modeled after Yahoo! Pipes
π¦ Distributed log streaming engine built from first principles