Yes, Redis is highly scalable. It provides various mechanisms that can be used to scale the system and meet different application demands.
# Start Redis Server redis-server --maxmemory 10gb
There are two primary ways you can do this:
import redis pool = redis.ConnectionPool(host='localhost', port=6379, db=0) r = redis.Redis(connection_pool=pool) r.set('key', 'value')
# Creating a Redis Cluster redis-cli --cluster create 127.0.0.1:7000 127.0.0.1:7001 \ 127.0.0.1:7002 127.0.0.1:7003 127.0.0.1:7004 127.0.0.1:7005 \ --cluster-replicas 1
Remember, while sharding allows for horizontal scaling and improves overall performance, it does increase complexity as data consistency becomes more challenging to manage.
# In the slave node configuration file, add: slaveof <masterip> <masterport>
However, replication is not designed to provide additional write scalability. Writes still have to go to the master node, and the slaves synchronize data from the master.
Please remember that each scaling method comes with its own trade-offs, so you should choose what suits your needs best.
Dragonfly is fully compatible with the Redis ecosystem and requires no code changes to implement.