# cpp

Kafka-compatible streaming platform, no JVM required

Redpanda is a Kafka-compatible streaming data platform written in C++ using the Seastar framework. It eliminates the need for ZooKeeper and the JVM, delivering up to 10x lower tail latencies and significantly reduced operational complexity. Redpanda ships as a single binary with a built-in schema registry, HTTP proxy, and message broker. It supports the Kafka wire protocol, so existing producers, consumers, and tools work without code changes. Backed by $165M+ in funding with 12.0K GitHub stars.

Lightweight C++ inference for Google Gemma models

gemma.cpp is Google's standalone C++ inference engine built specifically for running Gemma language models without Python or CUDA dependencies. It provides optimized CPU inference using SIMD instructions and Highway library, supports Gemma 2 and Gemma 3 models, and runs on x86 and ARM architectures. Designed for embedded systems, edge devices, and server deployments needing minimal overhead.

On-device ML solutions for mobile and edge AI

MediaPipe is Google's open-source framework for building on-device machine learning pipelines across mobile, web, desktop, and edge platforms. It provides pre-built solutions for face detection, hand tracking, pose estimation, object detection, image classification, text classification, and on-device LLM inference. MediaPipe runs entirely locally without cloud dependencies, supporting Android, iOS, Python, and web browsers.

Open-source high-performance key/value datastore

Valkey is a Linux Foundation-backed open-source fork of Redis 7.2.4 under BSD 3-Clause license, created after Redis changed to restrictive licensing. It provides a drop-in Redis replacement for caching, message queues, and real-time data workloads. Valkey 9 adds JSON, Bloom filters, vector search, cluster scaling to 2000 nodes, and over one billion requests per second in benchmarks. Backed by AWS, Google, Oracle, and Ericsson.