There are several redis caching mechanisms

Redis provides the following caching mechanisms: Basic caching: Eliminate key-value pairs that have not been used for the longest time, are used the least, or are used the least. Cache with expiration time: Use TTL to automatically expire key-value pairs, or use AOF and RDB to persist expired key-value pairs. Data structures: Hash tables, deques, sets, and sorted sets. Distributed cache: Clustering and distributed consensus algorithms improve scalability and high availability.

Redis caching mechanism type

Redis provides a variety of caching mechanisms to meet different application needs:

1. Basic cache

• #LRU (Least Recently Used): Eliminate key-value pairs that have not been used for the longest time.
• LRFU (Least Recently Frequently Used): Eliminate the key-value pair with the least usage.
• LFU (Least Frequently Used): Eliminate the least frequently used key-value pair, regardless of timestamp.

2. Cache with expiration time

• TTL (Time to Live): Automatically expires after the specified time Key-value pairs.
• AOF (Append Only File): Persists all write operations and can be used to restore expired key-value pairs after restarting.
• RDB (Redis Database): Periodically creates snapshots of Redis data, which can be used to restore expired key-value pairs after a system failure.

3. Data structure

• Hash table: Stores key-value pairs for quick search and modification.
• Double-ended queue: Can be used as a FIFO (first in first out) or LIFO (last in first out) queue.
• Collection: Stores unique members and is used to quickly find whether a specific member exists.
• Ordered set: Stores members with fractions, used to quickly find and retrieve members sorted by fractions.

4. Distributed Cache

• Cluster: Group Redis instances into clusters to improve scalability and High availability.
• Distributed consistency: Use consistency algorithms such as Raft or Redis Sentinel to ensure data synchronization between different cluster nodes.

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