Cross-platform, customizable ML solutions for live and streaming media.

Redpanda is a streaming data platform for developers. Kafka API compatible. 10x faster. No ZooKeeper. No JVM!

Open-source graph database, tuned for dynamic analytics environments. Easy to adopt, scale and own.

High-performance, low-footprint SQL database written in C++. Process millions of rows per second from Kafka/Pulsar, Iceberg, or ClickHouse, and seamlessly write results back. Supports powerful features like JOIN, CDC, UPSERT, and LOOKUP, enabling real-time analytics and ETL at scale.

MAGE - Memgraph Advanced Graph Extensions 🔮

The Refreshingly Simple Cross-Platform C++ Dataflow / Patching / Pipelining / Graph Processing / Stream Processing / Reactive Programming Framework

Daggy - Data Aggregation Utility and C/C++ developer library for data streams catching

A high performance/ real-time C++ Kafka streams framework (C++17)

Generic Reusable Parallel Patterns Interface

A C++17 Data Stream Processing Parallel Library for Multicores and GPUs

Multi-core Window-Based Stream Processing Engine

Cross-Platform Graphical Tool for DSPatch

The purpose of this project is to apply mediapipe to more AI chips.

A header-only C++ library for system-level verification and declarative testing of real-time systems with Python bindings.

DSPatch Component Repository

A high-throughput, structured streaming framework built atop Redis Streams. C++, Python, and MATLAB support.

ECSNeT++ is a simulation framework built on OMNeT++ for Distributed Stream Processing applications running on Edge and Cloud computing environments.

Suite of Benchmark Applications for Stream Processing Systems

SPBench: A Framework for Benchmarking Stream Processing Applications

SPar is an internal DSL for high-level stream parallelism