8 dépôts
The mechanism of appending events to a stream to notify other services of state changes.
Distinct from Event Streaming Pipelines: Distinct from pipelines which transform and route; this is the primitive act of implementing the stream as a signaling mechanism.
Explore 8 awesome GitHub repositories matching data & databases · Event Stream Implementation. Refine with filters or upvote what's useful.
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
Appends events to named streams to signal state changes or trigger actions in other services.
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
Produces cryptographically signed streams of smart contract events for verification by light clients.
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
Provides concrete implementations of debouncing and polling patterns for mobile event streams.
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
Publishes stream events from a task to the orchestration API for consumption by separate subscribers.
BLAKE3 est une implémentation haute performance de l'algorithme de hachage cryptographique BLAKE3 utilisé pour calculer des digests de données sécurisés et des empreintes digitales. Il fonctionne comme un outil de hachage cryptographique parallèle qui distribue les charges de travail sur plusieurs threads de processeur pour traiter rapidement de grands jeux de données. Le projet fournit des outils spécialisés pour le hachage avec clé et la génération de codes d'authentification de message. Il inclut également une fonctionnalité pour la dérivation de clé cryptographique, permettant la création de sous-clés secrètes uniques à partir d'une clé maîtresse et de chaînes de contexte. L'implémentation prend en charge la vérification de l'intégrité des données via le calcul de hachage parallèle et le streaming de données vérifié. Ces capacités sont fournies sous forme de bibliothèque inter-langages pour les environnements Rust et C et incluent une interface en ligne de commande pour calculer les digests de fichiers ou d'entrée standard.
Allows for the incremental integrity verification of data chunks during streaming.
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
Appends new events to a named stream, preserving the order and history of state changes.
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
Persists events as immutable, ordered records in streams, preserving the full audit trail.
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
Enables publishing processed function results to broker streams for event-driven data pipelines.