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The difference between Memcache and Redis :
* In Redis, not all data is always stored in memory. This is the biggest difference compared with Memcache.
* Redis has the characteristics of a database in many aspects, or it is a database system, while Memcache is just a simple K/V cache.
* Their expansion requires clustering; implementation methods: master-slave, Hash.
* In data of more than 100k, Memcache performance is higher than Redis.
* If we want to talk about memory usage efficiency, Memcached has higher memory utilization if simple key-value storage is used. And if Redis uses hash structure for key-value storage, due to its combined compression, its memory The utilization rate will be higher than Memcache. Of course, this depends on your application scenario and data characteristics.
* If you have requirements for data persistence and data synchronization, it is recommended that you choose Redis, because Memcache does not have these two features. Even if you just hope that cached data will not be lost after upgrading or restarting the system, it is wise to choose Redis.
* There is not much difference between Redis and Memcache in terms of writing performance. Memcache is stronger in terms of reading performance, especially batch reading performance.
Common points: Memcache and Redis are both in-memory databases.
Differences :
Memcache
Memcache can take advantage of multi-core. The throughput of a single instance is extremely high, which can reach hundreds of thousands of QPS. It is suitable for maximum load capacity.
Only supports simple key/value data structures, unlike Redis which can support rich type of data.
Unable to be persisted, data cannot be backed up and can only be used for caching, and all data will be lost after restarting
Redis
Supports a variety of data structures, such as string, list, dict, set, zset, hyperloglog
Single-threaded request, all commands are executed serially, and there is no need to consider data consistency issues in concurrent situations.
Supports persistence operations, and can persist aof and rdb data to disk for data backup or data recovery operations, which is a better way to prevent data loss.
aof's compression rules, such as adding and deleting a key, will filter
Supports data replication through Replication. Through the master-slave mechanism, data can be synchronously replicated in real time, and multi-level replication and incremental replication are supported.
Supports pub/sub message subscription mechanism, which can be used for message subscription and notification.
Supports simple transaction requirements, but there are few usage scenarios in the industry and is immature
The difference between Memcache and Redis:
* In Redis, not all data is always stored in memory. This is the biggest difference compared with Memcache.
* Redis has the characteristics of a database in many aspects, or it is a database system, while Memcache is just a simple K/V cache.
* Their expansion requires clustering; implementation methods: master-slave, Hash.
* In data of more than 100k, Memcache performance is higher than Redis.
* If we want to talk about memory usage efficiency, Memcached has higher memory utilization if simple key-value storage is used. And if Redis uses hash structure for key-value storage, due to its combined compression, its memory The utilization rate will be higher than Memcache. Of course, this depends on your application scenario and data characteristics.
* If you have requirements for data persistence and data synchronization, it is recommended that you choose Redis, because Memcache does not have these two features. Even if you just hope that cached data will not be lost after upgrading or restarting the system, it is wise to choose Redis.
* There is not much difference between Redis and Memcache in terms of writing performance. Memcache is stronger in terms of reading performance, especially batch reading performance.
Common points: Memcache and Redis are both in-memory databases.
Differences :
Memcache
Memcache can take advantage of multi-core. The throughput of a single instance is extremely high, which can reach hundreds of thousands of QPS. It is suitable for maximum load capacity.
Only supports simple key/value data structures, unlike Redis which can support rich type of data.
Cannot be persisted, data cannot be backed up, can only be used for caching, and all data will be lost after restart
Redis
Supports a variety of data structures, such as string, list, dict, set, zset, hyperloglog
Single-threaded request, all commands are executed serially, and there is no need to consider data consistency issues in concurrent situations.
Supports persistence operations, and can persist aof and rdb data to disk for data backup or data recovery operations, which is a better way to prevent data loss.
aof's compression rules, such as adding and deleting a key, will filter
Supports data replication through Replication. Through the master-slave mechanism, data can be synchronously replicated in real time, and multi-level replication and incremental replication are supported.
Supports pub/sub message subscription mechanism, which can be used for message subscription and notification.
Supports simple transaction requirements, but there are few usage scenarios in the industry and is immature
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