4 रिपॉजिटरी
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 is a Go-based framework and toolkit designed for building, hosting, and scaling services within the AT Protocol ecosystem. It provides the foundational infrastructure for decentralized social networking, enabling developers to implement relay services, manage cryptographically signed user repositories, and handle identity resolution across federated environments. The project distinguishes itself through a robust architecture that decouples content hosting from discovery, allowing for independent moderation and algorithmic feed generation. It utilizes content-addressed storage and Merkl
Collects and streams data records from multiple personal data servers into a unified feed for real-time network monitoring and indexing.