Fancy stream processing made operationally mundane
- message-queue
- stream-processing
- streaming-data
- message-bus
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Fancy stream processing made operationally mundane
Apache Beam is a unified programming model for Batch and Streaming data processing.
Fast and Lightweight Logs, Metrics and Traces processor for Linux, BSD, OSX and Windows
🦀 event stream processing for developers to collect and transform data in motion to power responsive data intensive applications.
Canonical actor model implementation for .NET with local + distributed actors in C# and F#.
Distributed stream processing engine in Rust
Drop-in Apache Spark replacement written in Rust, unifying batch processing, stream processing, and compute-intensive AI workloads.
StreamAlert is a serverless, realtime data analysis framework which empowers you to ingest, analyze, and alert on data from any environment, using datasources and alerting logic you define.
Project Flogo is an open source ecosystem of opinionated event-driven capabilities to simplify building efficient & modern serverless functions, microservices & edge apps.
Fancy stream processing made operationally mundane. This repository is a fork of the original project before the license was changed.
A lightweight stream processing library for Go
The Feldera Incremental Computation Engine
Probabilistic data structures for processing continuous, unbounded streams.
A platform that makes it easy for developers to build realtime, cost-effective, operations-focused applications
High performance Rust stream processing engine seamlessly integrates AI capabilities, providing powerful real-time data processing and intelligent analysis.
Trill is a single-node query processor for temporal or streaming data.
Tenzir is the data pipeline engine for security teams.
Low-code tool for automating actions on real time data | Stream processing for the users.
HStreamDB is an open-source, cloud-native streaming database for IoT and beyond. Modernize your data stack for real-time applications.
🏎️ Streams & Reactive Programming paradigm for Go: declarative and composable API for event-driven applications
Machine is a workflow/pipeline library for processing data
Amazon Kinesis Aggregators provides a simple way to create real time aggregations of data on Amazon Kinesis.
Real-time decision features without streaming infra. Turn live events into product reflexes — no Kafka, no Flink, no feature store.
Small, Fast event processing and monitoring for Erlang/OTP applications.