A flexible multi-layer Go caching library to deal with in-memory and shared cache by adopting Cache-Aside pattern.
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Updated
Aug 30, 2023 - Go
A flexible multi-layer Go caching library to deal with in-memory and shared cache by adopting Cache-Aside pattern.
A lightweight high-performance distributed two-level cache (in-memory + redis) with loader function library for Go.
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Microservices architecture, event driven architecture, CQRS, event sourcing, clean architecture, containerisation, distributed caching, cache-aside pattern, unit tests
Cache-Aside demo using Redis Enterprise and RDBMS TestContainers
Implementing cache-aside in Go with the Decorator pattern.
Cache-Aside Pattern example using Redis.
Caching based on cache aside strategy (write on miss) using Redis
Redis is a powerful tool for caching data in memory, which can increase application benchmark when consuming
Project created with the aim of training the implementation of cache-aside logic using Redis.
This is a hands-on workshop to create the application Redis Movies Searcher
Cache-Aside pattern implementation using aspnet output caching for a sample Weather forecast application
Sample application written in Java (JDK 21, Spring Boot, Redis OM Spring) that implements a hybrid search strategy (Full-Text Search and Vector Similarity Search) to allows for movies search.
Blazor frontend for Clean Architecture/Modular Monolith backends.
Cache-Aside Pattern example using IDistributedCache.
A high-performance Spring Boot caching service with intelligent cache invalidation strategies. Features cache-aside pattern, automatic invalidation, TTL-based expiration, and comprehensive performance monitoring. Designed for microservices architecture and high-traffic applications requiring optimal data retrieval performance.
A high-performance Spring Boot caching service with intelligent cache invalidation strategies. Features cache-aside pattern, automatic invalidation, TTL-based expiration, and comprehensive performance monitoring. Designed for microservices architecture and high-traffic applications requiring optimal data retrieval performance with consistency.
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