[Answered] What is the best distributed cache system?

Answer

Several distributed caching solutions are widely used in the tech industry, each with its own strengths. The following are among the most highly rated:

1. Redis

Redis is a popular open-source, in-memory data structure store. It supports various types of data structures such as strings, hashes, lists, sets, and more. It can be used as a database, a cache, and a message broker.

Some of its features include:

Transactions
Pub/Sub capabilities
Lua scripting
Persistence storage
High Availability - Via Redis Sentinel
Automatic partitioning - Via Redis Cluster

import redis

r = redis.Redis(host='localhost', port=6379, db=0)
r.set('foo', 'bar')
print(r.get('foo'))

2. Memcached

Memcached is another open-source distributed memory object caching system, originally developed by Danga Interactive for LiveJournal, but now used by many other sites.

Some of its features include:

Simple key-value store
LRU Cache Eviction Policy
No persistence
Multi-threaded architecture

from pymemcache.client import base

client = base.Client(('localhost', 11211))
client.set('some_key', 'some_value')
result = client.get('some_key')

3. Apache Ignite

Apache Ignite is an open-source distributed database, caching, and processing platform designed to store and compute on large volumes of data across a cluster of nodes.

Its features include:

SQL Queries
ACID transactions
Distributed computations

Ignite ignite = Ignition.start();

CacheConfiguration cfg = new CacheConfiguration("myCache");

IgniteCache cache = ignite.getOrCreateCache(cfg);

cache.put(1, "Hello");
cache.put(2, "World!");

System.out.println("Got [key=1, val=" + cache.get(1) + ']');
System.out.println("Got [key=2, val=" + cache.get(2) + ']');

The choice between these options depends on your specific use-case. You'll want to consider factors like data size, the complexity of operations you need to perform, the importance of data persistence, and whether multi-threading is important for your application.