A memory cache written in Typescript with support for stale-while-revalidate and background refresh
A simple key/value storage using files to persist the data
Memory adapter for Better Auth
High Performance In-Memory Cache for Node.js
An LRU cache of weak references
A cache object that deletes the least-recently-used items.
Require hook for automatic V8 compile cache persistence
JavaScript Performance Monitor
A simple in-memory cache. put(), get() and del()
In-memory Cache Module for Medusa
Require hook for automatic V8 compile cache persistence
High Performance Layer 1 / Layer 2 Caching with Keyv Storage
Useful TypeScript utilities.
useMemo and useCallback but with a stable cache
MongoDB Server for testing (auto-download latest version). The server will allow you to connect your favourite ODM or client library to the MongoDB Server and run parallel integration tests isolated from each other.
Multi-strategy cache service with tag-based invalidation support
Memory adapter for catbox
TypeScript definitions for memory-cache
walk paths fast and efficiently
A lightweight, zero-dependency in-memory cache for TypeScript and JavaScript with TTL expiration, LRU eviction, wildcard pattern deletion, and a powerful @cached decorator for method-level memoization. Perfect for API response caching, session storage, an
Memoize/cache function results
A set of efficient utilities that extend the use of JSON (streaming, estimate size, NDJSON/JSONL, etc.)
Simple “Least Recently Used” (LRU) cache
EditorConfig File Locator and Interpreter for Node.js
Generates memory-optimal immutable ActiveRecord dupes that are easily serializable and behaves much like ARs. Define required attributes before-hand and use them just as you would on an AR, for better memory optimization. Ideally, suitable in place of caching AR objects with cache stores like Memcached, where serialization and de-serialization are memory-hungry. Optars can save upto 90% of your memory(object allocations), while being upto 20x faster, when fetching huge AR results.
Use Mysql AUTO_INCREMENT to support key value cache, which should be combined by an integer and string. It means to reduce the database storage size, and improve query performance. All cache will store in process memory, and will never be expired, until the process dies, so the less kvs you use, the better performance you will get. BTW, 100,000 general strings use 10MB memory. Some relatived articles: http://en.wikipedia.org/wiki/Correlation_database Usage ------------------------------------------ ## setup ```ruby create_table :kv_browser_names, :options => 'ENGINE=MyISAM DEFAULT CHARSET=utf8' do |t| t.string :name t.timestamps end class KvBrowserName < ActiveRecord::Base include IdNameCache end ``` or ```ruby create_table :common_tag, :options => 'ENGINE=MyISAM DEFAULT CHARSET=utf8' do |t| t.integer :tagid t.string :tagname end class CommonTag < ActiveRecord::Base self.table_name = :common_tag self.primary_key = :tagid include IdNameCache; set_key_value :tagid, :tagname # include IdNameCache; set_key_value_without_create :tagid, :tagname # if you dont want create it automately end ``` ### use cases ```text ruby-1.9.3-rc1 :001 > QuizTag[1] QuizTag Load (0.3ms) SELECT `common_tag`.* FROM `common_tag` WHERE `common_tag`.`tagid` = 1 LIMIT 1 => "Android" ruby-1.9.3-rc1 :002 > QuizTag[1] => "Android" ruby-1.9.3-rc1 :003 > QuizTag['Android'] QuizTag Load (0.5ms) SELECT `common_tag`.* FROM `common_tag` WHERE `common_tag`.`tagname` = 'Android' LIMIT 1 => 1 ruby-1.9.3-rc1 :004 > QuizTag['Android'] => 1 ``` == Copyright MIT, David Chen at eoe.cn
Contentful API wrapper library exposing an ActiveRecord-like interface
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