Awesome GitHub RepositoriesEvent Stream Implementation

Redis is a high-performance in-memory key-value store that functions as a distributed cache, message broker, and NoSQL database. It provides sub-millisecond read and write access to data stored in RAM and can operate as a vector database for indexing high-dimensional embeddings. The system supports a wide range of data storage and synchronization primitives, including the management of strings, hashes, lists, sets, and JSON documents. It enables real-time data operations through atomic transactions, hybrid persistence using snapshots and append-only logs, and high-availability configurations

Sui is a blockchain platform featuring an object-centric state model and resource-oriented smart contracts. It utilizes parallel transaction execution to increase network throughput and supports programmable transaction blocks that bundle multiple operations into single atomic units. The platform distinguishes itself with a capability-based access control system and zero-knowledge login mechanisms, enabling users to authenticate via identity providers without seed phrases. It also implements deterministic object addressing to allow predictable state lookups and supports the creation of soulbo

This project is a sample library and implementation guide for using RxJava to manage asynchronous data streams and concurrent tasks in Android applications. It provides a collection of reference implementations for reactive programming, focusing on functional operators to transform and combine asynchronous data flows. The library demonstrates specific Android architectural patterns, such as implementing decoupled event buses for component communication and coordinating parallel network requests. It includes concrete examples of mobile-specific patterns including search input debouncing, list

Hatchet is an open-source durable workflow engine and task orchestration platform. It provides a framework for building and executing fault-tolerant, multi-step pipelines as directed acyclic graphs (DAGs), with automatic retries, scheduling, and real-time observability. The system is built around durable task checkpointing, which persists execution state after each step so work can resume from the last checkpoint after a worker crash or restart, and it supports event-driven task resumption that pauses a task until a matching external event arrives. The platform distinguishes itself through it

BLAKE3 este o implementare de înaltă performanță a algoritmului de hashing criptografic BLAKE3, utilizat pentru calcularea digest-urilor de date securizate și a amprentelor digitale. Funcționează ca un instrument de hashing criptografic paralel care distribuie sarcinile de lucru pe mai multe fire de execuție ale procesorului pentru a procesa rapid seturi de date mari. Proiectul oferă instrumente specializate pentru hashing cu cheie și generarea de coduri de autentificare a mesajelor. Include, de asemenea, funcționalitate pentru derivarea cheilor criptografice, permițând crearea de sub-chei secrete unice dintr-o cheie master și șiruri de context. Implementarea suportă verificarea integrității datelor prin calculul hash paralel și streaming-ul verificat al datelor. Aceste capabilități sunt oferite ca o bibliotecă cross-language pentru medii Rust și C și includ o interfață de linie de comandă pentru calcularea digest-urilor fișierelor sau a input-ului standard.

KurrentDB is an event-native database designed for event sourcing and event-driven architectures. It stores application state as an immutable, ordered sequence of events rather than updating rows in place, preserving full history for audit, replay, and distributed consistency. The database combines event storage with real-time streaming and a built-in JavaScript projection engine that transforms and aggregates event streams into materialized views. The system provides official gRPC client libraries for Python, Node.js, Java, .NET, Go, and Rust, enabling multi-language application development

KurrentDB is an event-native database designed for event sourcing and event-driven architectures. It stores events as immutable, ordered records in streams, preserving a complete audit trail and enabling temporal queries. The database uses gRPC for all client-server and inter-node communication, providing efficient binary serialization and bidirectional streaming, and supports atomic multi-stream writes that ensure consistency across multiple streams in a single transaction. The database distinguishes itself with a built-in JavaScript projection engine that transforms, filters, and aggregates

FastStream is an asynchronous Python framework designed for building event-driven microservices. It provides a unified abstraction layer for interacting with various message brokers, enabling developers to manage event production and consumption through a consistent interface while maintaining access to native provider-specific features. The framework centers on a decorator-based routing model that binds application logic directly to broker topics, supported by a built-in dependency injection container that resolves resources at runtime. The framework distinguishes itself through its deep int