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11 repositorios

Awesome GitHub RepositoriesEvent-Based Stream Processing

Processing of large data files as a sequence of events to minimize memory footprint.

Distinct from Streaming Processing: None of the candidates cover general event-based streaming for data serialization formats.

Explore 11 awesome GitHub repositories matching data & databases · Event-Based Stream Processing. Refine with filters or upvote what's useful.

Awesome Event-Based Stream Processing GitHub Repositories

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • reactivex/rxgoAvatar de ReactiveX

    ReactiveX/RxGo

    5,091Ver en GitHub↗

    RxGo es una biblioteca de programación reactiva funcional y una implementación de ReactiveX para el lenguaje Go. Sirve como un kit de herramientas de procesamiento de flujos asíncronos diseñado para coordinar programas basados en eventos y flujos de datos utilizando el patrón observable. La biblioteca permite la construcción de pipelines de procesamiento asíncrono que transforman, filtran y combinan secuencias de eventos. Se distingue por el uso de operadores funcionales para componer estos pipelines y proporciona mecanismos para gestionar la ejecución concurrente. El kit de herramientas cubre una amplia gama de capacidades de orquestación de flujos, incluyendo agregación de datos, combinación de múltiples flujos y la conversión de flujos en estructuras de datos estáticas. Incluye soporte integrado para recuperación de errores, control de contrapresión (backpressure) para regular las velocidades de producción de datos y agrupación de workers para paralelizar el procesamiento a través de núcleos de CPU.

    The library selects specific items from a stream based on predicates, time-based debouncing, or index positions.

    Goasyncasynchronousconcurrency
    Ver en GitHub↗5,091
  • reactivex/rxpyAvatar de ReactiveX

    ReactiveX/RxPY

    5,014Ver en GitHub↗

    RxPY es una librería de programación reactiva funcional y una librería de observables ReactiveX para Python. Funciona como un procesador de flujos asíncronos y un framework de coordinación basado en eventos, utilizado para construir pipelines de datos que reaccionan a cambios de estado o flujos de eventos a lo largo del tiempo. La librería proporciona un kit de herramientas para componer programas asíncronos y basados en eventos mediante secuencias observables y operadores. Se distingue por el uso de planificadores (schedulers) configurables para gestionar la concurrencia, el timing y los ciclos de vida de las suscripciones. El proyecto cubre una amplia gama de capacidades de procesamiento de flujos, incluyendo agregación, filtrado y combinación de datos. Proporciona mecanismos para la difusión de eventos, almacenamiento en búfer de secuencias y gestión de errores, así como herramientas para coordinar flujos observables con bucles de eventos asíncronos. Las pruebas y el aseguramiento de la calidad se apoyan en la simulación de tiempo virtual, el modelado con diagramas de mármol y la verificación de emisiones.

    Filters items from event streams based on predicates, indices, or timing criteria.

    Python
    Ver en GitHub↗5,014
  • dropbox/leptonAvatar de dropbox

    dropbox/lepton

    4,997Ver en GitHub↗

    Lepton es una herramienta especializada y un formato de archivo diseñado para la compresión sin pérdida y el almacenamiento eficiente de datos de imagen JPEG. Funciona como un compresor sin pérdida y optimizador de almacenamiento que reduce el tamaño de los archivos sin alterar los datos originales de los píxeles, garantizando una reconstrucción bit a bit de las imágenes. El proyecto se centra en reducir el espacio en disco y los requisitos de ancho de banda de red para archivos de imágenes digitales. Proporciona capacidades tanto para la compresión como para la descompresión de archivos JPEG, manteniendo un almacenamiento de imágenes de alta calidad y minimizando la huella de datos general. La implementación utiliza diversas técnicas de codificación de entropía y procesamiento de datos, incluyendo codificación aritmética y de Huffman, modelado predictivo y procesamiento basado en flujos. También integra operaciones de matriz optimizadas para el procesamiento de grandes bloques de datos de imagen.

    Processes large image files as a sequence of bytes to maintain a low memory footprint.

    C++compressioncompression-algorithmdecompression
    Ver en GitHub↗4,997
  • effector/effectorAvatar de effector

    effector/effector

    4,837Ver en GitHub↗

    Effector is a reactive state management library designed for building complex, event-driven applications. It functions as a data flow engine that models application logic as a directed acyclic graph, ensuring that state updates propagate automatically through interconnected nodes. By utilizing atomic state updates and declarative unit composition, the library maintains data consistency and provides a predictable execution model for managing application state. The project distinguishes itself through its framework-agnostic architecture, which decouples business logic from user interface implem

    Filters data streams by applying conditional logic to event triggers before they reach target effects.

    TypeScriptbusiness-logiceffectorevent-driven
    Ver en GitHub↗4,837
  • riemann/riemannAvatar de riemann

    riemann/riemann

    4,266Ver en GitHub↗

    Riemann is a Clojure-based event stream processor and real-time analytics engine. It functions as a network telemetry pipeline and extensible event router that ingests, transforms, and routes event data from distributed systems. The system uses a domain-specific language to compute metrics and statistical patterns over continuous streams, enabling network trend analysis and real-time alerting. It supports dynamic plugin loading from the classpath and allows for live configuration reloading without interrupting active event streams. Capabilities include centralized telemetry aggregation, even

    Transforms event streams using complex operations including linear prediction, rate calculation, and event coalescing.

    Clojure
    Ver en GitHub↗4,266
  • theturtle32/websocket-nodeAvatar de theturtle32

    theturtle32/WebSocket-Node

    3,784Ver en GitHub↗

    WebSocket-Node is a server-side implementation of the WebSocket protocol for Node.js environments. It serves as a framework for establishing persistent, bidirectional communication channels and low-latency data exchange between clients and servers. The project provides a secure socket implementation using transport layer security and includes an integrated client for establishing outbound encrypted connections. It utilizes a formal protocol-state machine and an event-driven connection framework to manage high-concurrency network streams. The framework covers server-side infrastructure includ

    Processes network data as a continuous stream of events to minimize memory overhead during high concurrency.

    JavaScript
    Ver en GitHub↗3,784
  • bruin-data/ingestrAvatar de bruin-data

    bruin-data/ingestr

    3,714Ver en GitHub↗

    ingestr is a command-line tool for copying and syncing data between different database engines and third-party platforms without writing custom code. It functions as an ETL pipeline utility that extracts data from diverse sources and loads it into destinations. The tool features a schema-agnostic data loader that maps source fields to destination columns dynamically, removing the need for predefined static table definitions. It also operates as an incremental data synchronizer, updating destination tables by appending new records or merging changes to maintain current datasets. The system pr

    Processes large datasets in small chunks to maintain a low memory footprint during data transfer.

    Go
    Ver en GitHub↗3,714
  • aaubry/yamldotnetAvatar de aaubry

    aaubry/YamlDotNet

    2,807Ver en GitHub↗

    YamlDotNet is a YAML serialization library and data mapping tool for .NET. It functions as a parser and generator that converts between .NET objects and YAML formatted text for data storage and configuration. The project provides capabilities for YAML document parsing and data object mapping. It transforms YAML streams into low-level representations or high-level object models for programmatic analysis and converts structured data objects back into valid YAML strings. The library covers general data serialization and configuration file management, allowing application data structures to be m

    Allows reading large YAML files as a sequence of events to avoid loading entire documents into memory.

    C#dotnetparserserialization
    Ver en GitHub↗2,807
  • pulldown-cmark/pulldown-cmarkAvatar de pulldown-cmark

    pulldown-cmark/pulldown-cmark

    2,610Ver en GitHub↗

    pulldown-cmark is a pull-parsing library that transforms Markdown text into a stream of events based on the CommonMark specification. It functions as an event-based processor that represents document structure as an iterator of events rather than a concrete syntax tree, serving as both a parser and a renderer to convert Markdown into HTML strings. The library is designed for memory efficiency by processing text as a stream to minimize resource usage. It supports programmatic document transformation, allowing users to map or filter the event stream before final rendering. The project includes

    Processes Markdown as an event stream to ensure low memory overhead and high speed.

    Rustcommonmarkmarkdownparser
    Ver en GitHub↗2,610
  • reactphp/socketAvatar de reactphp

    reactphp/socket

    1,285Ver en GitHub↗

    This library provides a framework for building event-driven, non-blocking network applications in PHP. It enables the development of asynchronous TCP and TLS servers and clients that manage multiple concurrent connections without stalling the main execution thread. By utilizing an event-loop architecture, the library handles network operations and data exchange through asynchronous streams, ensuring that the application remains responsive during high-throughput tasks. The project distinguishes itself through its integration with operating system primitives, such as raw file descriptors and Un

    Manages high-throughput data exchange by processing incoming and outgoing network chunks incrementally through non-blocking, event-based interfaces.

    PHPphpreactphpserver-socket
    Ver en GitHub↗1,285
  • mrsuichuan/data-warehouse-learningAvatar de MrSuiChuan

    MrSuiChuan/data-warehouse-learning

    1,154Ver en GitHub↗

    Data warehouse learning is a reference implementation of a real-time stream processing system and open-source data lakehouse architecture. It combines stream processing engines, open lakehouse formats, and analytical data warehouses into a complete e-commerce data warehouse system built for both offline and real-time analytics pipelines. The project implements hybrid data warehouse architectures utilizing multi-layer storage models and stream-batch processing pipelines. It features change data capture pipelines that stream database transaction logs into messaging systems, progressive data tra

    Applies progressive transformations across staging, dimensional, and summary layers using stream processing queries.

    Javadatartdinkydolphinscheduler
    Ver en GitHub↗1,154
  1. Home
  2. Data & Databases
  3. Event-Based Stream Processing

Explorar subetiquetas

  • Batch-Based Stream ProcessingProcessing large datasets in small chunks to minimize memory usage during transfer. **Distinct from Event-Based Stream Processing:** Distinct from Event-Based Stream Processing: focuses on fixed-size chunking for memory efficiency rather than event-driven triggers.
  • Event Stream Filtering1 sub-etiquetaSelecting specific items from an event stream based on predicates, indices, or timing. **Distinct from Event-Based Stream Processing:** Distinct from Event-Based Stream Processing as it focuses specifically on the filtering logic rather than the overall processing architecture.