4 repositorios
Tools that collect and present a chronological stream of events from a specific API.
Distinct from GitHub API Aggregators: Focuses on the aggregation of event streams into a unified view rather than just metadata fetching.
Explore 4 awesome GitHub repositories matching data & databases · Event Stream Aggregators. Refine with filters or upvote what's useful.
Devhub is a cross-platform developer tool and event aggregator designed to monitor GitHub activities. It provides a unified interface for tracking issues, notifications, and user actions across multiple repositories, consolidating these updates into a single view to reduce notification clutter. The application utilizes a multi-column dashboard for organizing data streams via customizable filters and saved searches. This interface allows for the management of review queues, the monitoring of specific user actions, and the display of notification context without requiring navigation to the sour
Collects repository updates and user actions into a single view to reduce notification clutter.
Pinot is a distributed, columnar analytical database designed for high-concurrency, low-latency query processing. It functions as a real-time OLAP datastore, enabling interactive, user-facing analytics by ingesting and querying massive datasets from both streaming and batch sources. The system architecture relies on a centralized controller for cluster coordination and a distributed segment-based storage model to ensure horizontal scalability. The platform distinguishes itself through a hybrid ingestion pipeline that unifies real-time event streams and historical batch data into a single quer
Consumes events from streaming sources to create a unified, queryable SQL view across microservice architectures.
Cube is a time-series analytics platform and event data store designed for real-time performance monitoring. It functions as a metrics engine that ingests timestamped event streams and persists raw logs to enable the computation of statistical summaries, quantiles, and histograms. The system distinguishes itself through a reactive processing model that automatically invalidates metric caches when new events arrive, ensuring query results remain current. It supports both real-time event streaming via persistent connections and the calculation of post hoc statistics from stored event sets. The
Converts raw event streams into aggregate statistics, quantiles, and histograms for high-level system observation.
Indigo es un framework y kit de herramientas basado en Go diseñado para construir, alojar y escalar servicios dentro del ecosistema AT Protocol. Proporciona la infraestructura fundamental para redes sociales descentralizadas, permitiendo a los desarrolladores implementar servicios de retransmisión (relay), gestionar repositorios de usuarios firmados criptográficamente y manejar la resolución de identidad a través de entornos federados. El proyecto destaca por una arquitectura robusta que desacopla el alojamiento de contenido del descubrimiento, permitiendo una moderación independiente y la generación de feeds algorítmicos. Utiliza almacenamiento direccionado por contenido y estructuras de repositorio basadas en árboles de Merkle para asegurar la integridad de los datos, mientras que su generación de esquemas basada en léxico crea automáticamente estructuras con seguridad de tipos para la comunicación entre servicios. Al mapear identificadores legibles por humanos a identificadores descentralizados, el sistema mantiene la propiedad verificable del usuario y la portabilidad de la cuenta a través de proveedores de alojamiento independientes. Más allá de su identidad central, el proyecto cubre una superficie integral para gestionar el estado distribuido, incluyendo streaming de eventos en tiempo real, sincronización y moderación automatizada. Proporciona herramientas extensas para la simulación de actividad de red, telemetría operativa e indexación de flujos de datos globales. El framework está diseñado para entornos de producción, ofreciendo opciones de despliegue contenedorizado y endpoints de diagnóstico para monitorear la salud de la sincronización y el rendimiento del sistema.
Collects and streams data records from multiple personal data servers into a unified feed for real-time network monitoring and indexing.