#apex #async #cache #integration #invocable #salesforce #trigger

https://github.com/trailheadapps/apex-recipes

#java #cache #distributed #distributed_locks #executor #hibernate #list #lock #map #mapreduce #queue #redis #redis_client #redis_cluster #scheduler #session #set #spring_cache #tomcat

https://github.com/redisson/redisson

#go #cache #database #databases #disk #distributed_database #distributed_systems #golang #high_performance #key_value #kvstore #leveldb #lsm #nosql #persistence #raft #redis #storage

https://github.com/gitsrc/IceFireDB

#objective_c #cache #carthage #cocoapods #gif #image #ios #jpeg #macos #objective_c #png #sdwebimage #swift #watchos #webp

https://github.com/SDWebImage/SDWebImage

#javascript #avatica #cache #calcite #clickhouse #dbproxy #doris #hive #mysql #oneservice #onesql #tidb

https://github.com/daima/fense

#go #cache #client_side_caching #distributed #generics #golang #lock #redis #redis_client #resp3 #resp3_client

https://github.com/redis/rueidis

#swift #cache #filters #image #image_processor #ios #kingfisher #macos #swift #xcode

Kingfisher is a powerful library for downloading and caching images in your apps. It helps you load images from the web quickly and efficiently. Here are the key benefits:
- It downloads images asynchronously and caches them for faster access later.
- You can customize how images are processed, such as resizing or adding effects.
- It supports both UIKit and SwiftUI, making it versatile for different types of apps.
- It includes features like placeholders, indicators, and transition animations while loading images.
- You can control cache behavior, including expiration dates and size limits.

Using Kingfisher simplifies your code and improves your app's performance when handling images. For example, you can set an image to an `UIImageView` with just a few lines of code, and it will handle the downloading and caching automatically. This makes your app run smoother and saves you time in development.

https://github.com/onevcat/Kingfisher

#java #cache #distributed #distributed_locks #executor #hibernate #java #json #lock #map #micronaut #quarkus #queue #redis #redis_client #scheduler #session #spring #tomcat #valkey #valkey_client

Redisson is a powerful Java client for Redis and other real-time data platforms. It offers high-performance, thread-safe, and asynchronous connections, making it ideal for complex applications. You can use it with various deployment types, such as single, cluster, sentinel, and more, and it is compatible with major cloud services like AWS, Azure, and Google Cloud. Redisson supports many features like distributed locks, counters, collections, and services, as well as integration with popular frameworks like Spring and Micronaut. This makes it easier to manage and scale your data efficiently, ensuring reliability and performance in your applications.

https://github.com/redisson/redisson

#cplusplus #cache #cpp #database #fibers #in_memory #in_memory_database #key_value #keydb #memcached #message_broker #multi_threading #nosql #redis #valkey #vector_search

Dragonfly is a modern in-memory data store compatible with Redis and Memcached, offering up to 25 times higher throughput and better cache efficiency while using up to 80% fewer resources. It scales well with larger servers, supports many Redis commands, and features a unique, memory-efficient cache and fast snapshotting. Dragonfly provides low latency, high performance, and is easy to configure with familiar Redis options. Its design ensures atomic operations and efficient resource use, making it ideal for fast, cost-effective cloud applications needing real-time data access and high scalability. This means you get faster, more efficient caching and data handling with minimal changes to your existing setup[5][2][4].

https://github.com/dragonflydb/dragonfly

#java #cache #caffine #data #draft #fetch #graphql #immer #immutable #immutable_collections #immutable_datastructures #java #jdbc #kotlin #orm #orm_framework #orm_library #orms #redis #redis_cache

Jimmer is a powerful and advanced ORM (Object-Relational Mapping) framework for Java and Kotlin that lets you easily read and write complex data structures without needing to predefine their shapes. It supports dynamic multi-table queries, automatic SQL optimization, and efficient saving of incomplete or nested objects. Jimmer also generates type-safe DTOs (Data Transfer Objects) for complex queries and updates, avoids common problems like "N+1" queries, and offers strong caching and GraphQL support. This means you can build complex business logic faster and with less hassle, improving both development speed and code quality. It works well with modern IDEs and supports both Java and Kotlin seamlessly.

https://github.com/babyfish-ct/jimmer