11 repositorios
Specific patterns for using data stores to cache frequently accessed application data.
Distinct from Redis Clients: Distinct from Redis Clients: focuses on the caching strategy and usage of the store rather than just the connection library.
Explore 11 awesome GitHub repositories matching data & databases · Caching Implementations. Refine with filters or upvote what's useful.
Revel is a full-stack web framework and toolkit for building applications with the Go language. It implements a model-view-controller architecture to separate business logic from user interface rendering, providing a comprehensive system for routing, parameter binding, and session management. The project distinguishes itself with a high-productivity development environment featuring automatic code compilation and hot-reloading, which refreshes the application state and templates upon file changes without requiring manual restarts. It also employs reflection-based parameter binding to automati
The project stores frequently used data in a Redis store to speed up response times for high-traffic requests.
Falcor is a JavaScript library that models remote data as a single virtual JSON graph, providing a path-based query engine for efficient client-side data retrieval and updates. It represents multiple remote data sources as a unified document where entities are accessed via globally unique identity paths. The system distinguishes itself by treating the remote data model as a virtual JSON resource, allowing the client to query specific paths without managing individual endpoints. It uses a reference-aware graph model to handle many-to-many relationships and prevents data duplication. Network ef
Provides custom callback functions to react to cache changes and transform incoming errors.
RedisInsight is a graphical user interface and management tool for browsing, analyzing, and administering Redis databases. It provides a visual environment for exploring key-value data structures, managing database instances, and performing data analysis across different operating systems and deployments. The tool distinguishes itself by providing dedicated visual managers for complex operations, including a vector database manager for configuring embeddings and similarity searches, a query workbench for executing raw commands and Lua scripts, and a performance monitoring dashboard for tracki
Enables the implementation and tuning of caching patterns, including semantic and write-through strategies.
Riverpod is a reactive state management framework for Dart that manages application state through providers which automatically track dependencies and rebuild dependents when values change. It functions as an asynchronous data caching library, caching results of async operations and exposing loading, error, and data states to widgets without manual future handling. The framework includes a provider composition system that combines multiple providers into derived values that recompute automatically when any dependency changes, along with code generation for state providers that reduces boilerpl
Associates a single provider with multiple independent states keyed by unique parameter combinations for per-parameter caching.
Hazelcast is a distributed data platform that combines an in-memory data grid with a stream processing engine to support real-time analytics and event-driven applications. It functions as a partitioned, distributed key-value store that replicates data across cluster nodes to provide low-latency access and high availability. The platform also serves as a distributed SQL query engine, allowing users to execute standard SQL statements against both in-memory datasets and external data sources. What distinguishes Hazelcast is its use of a distributed consensus subsystem to maintain strongly consis
Stores frequently accessed data across a cluster using a specification-compliant caching implementation.
Moleculer is a Node.js microservices framework designed for building distributed systems. It functions as a distributed service broker, task orchestrator, and service mesh framework, enabling a decentralized architecture with built-in service discovery and load balancing. The project differentiates itself through a pluggable transport layer supporting protocols such as NATS, Redis, TCP, and Kafka, as well as a dedicated microservices API gateway that maps external HTTP and WebSocket requests to internal service actions. It includes built-in fault tolerance mechanisms, including circuit breake
Allows the creation of specialized caching modules by implementing a standard interface for cache operations.
AndroidVideoCache es un servidor proxy local y caché de medios basado en disco para Android. Intercepta solicitudes de red para almacenar datos de video en streaming en el sistema de archivos local, permitiendo la reproducción offline y un menor uso de datos. El proyecto se diferencia al funcionar como un caché proxy HTTP que puede inyectar encabezados de solicitud personalizados. Esto permite la entrega de contenido de video autenticado satisfaciendo los requisitos de seguridad y autenticación del lado del servidor durante el proceso de caché. El sistema gestiona el almacenamiento mediante caché de disco a nivel de byte, mapeo de URL a archivo y la aplicación de cuotas de almacenamiento utilizando la política de desalojo least-recently-used (LRU). También incluye utilidades para rastrear el progreso del caché y lógica de nombrado de archivos personalizable para evitar colisiones.
Uses custom filename generation logic to prevent collisions caused by dynamic session tokens in video URLs.
HanekeSwift es una biblioteca de almacenamiento en caché genérica para iOS y un framework de almacenamiento en caché de imágenes especializado. Proporciona un sistema de múltiples niveles que almacena tipos de datos arbitrarios en memoria y en almacenamiento en disco persistente para reducir las solicitudes de red. El proyecto cuenta con un manejador de imágenes especializado que gestiona la carga asíncrona, el cambio de tamaño y el almacenamiento en disco para componentes de interfaz de usuario. Incluye un sistema de recuperación en segundo plano que obtiene contenido remoto y completa automáticamente las cachés locales. La biblioteca cubre el almacenamiento de datos clave-valor con retrocesos secuenciales, donde verifica la memoria, luego el disco y finalmente las fuentes remotas. Implementa la gestión automática de capacidad a través de políticas de desalojo de memoria y maneja la descompresión y transformaciones de datos fuera del hilo principal.
Allows defining custom formats and fetchers to add support for new data types or retrieval methods.
opennextjs-aws es un adaptador de infraestructura serverless y herramienta de despliegue que transforma los artefactos de build de Next.js en paquetes compatibles para su alojamiento en AWS Lambda y S3. Funciona como un adaptador de despliegue que mapea las salidas específicas del framework a funciones serverless y almacenamiento de objetos. El proyecto se distingue por implementar optimizaciones específicas para serverless, incluyendo un gestor de caché que sincroniza la regeneración estática incremental y las cachés de fetch a través de S3 o DynamoDB. Cuenta con un optimizador de cold start que utiliza minificación de bundles y calentamiento programado de funciones para reducir la latencia, junto con un pipeline de optimización de imágenes dedicado para obtener archivos fuente de S3 y entregarlos a través de CDN. El sistema cubre una amplia gama de capacidades, incluyendo integración de middleware en el edge, revalidación en segundo plano basada en colas y distribución de rutas multi-objetivo. También gestiona el tráfico a través de enrutamiento CDN, inyección de datos de geolocalización y streaming de respuestas del servidor para mejorar el tiempo hasta el primer byte (TTFB). La herramienta proporciona amplias opciones de personalización para pipelines de build, comportamientos de adaptadores y lógica de servidor para soportar necesidades arquitectónicas variadas y estructuras de monorepo.
Implements custom cache providers using S3 and DynamoDB for incremental and tag-based caching.
The BeeAI Framework is an LLM agent framework and multi-agent orchestration engine used to build autonomous agents that coordinate reasoning, tool execution, and complex workflows. It functions as a structured AI output controller and RAG integration library, providing a unified interface to manage multiple language model providers. The framework is distinguished by its implementation of the Model Context Protocol, allowing agents, tools, and models to be shared between different AI platforms and hosted as agentic tooling servers. It enables the design of collaborative agent teams through dec
Allows developers to extend the base cache interface to create specialized storage providers with custom key generation.
Fast-memoize.js is a JavaScript memoization library that caches function return values for identical arguments to speed up expensive execution in JavaScript applications. It operates as a caching utility that stores and retrieves function outputs by serializing input parameters into unique keys. The library optimizes execution through arity-based function specialisation, generating tailored internal call paths based on the expected number of arguments. It features deterministic argument serialization to convert complex and variadic input parameters into unique string keys for reliable cache l
Supply an alternative storage backend implementing standard lookup and insertion methods to control how results are retained.