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The relationship between redis and database

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Redis and database are different data storage systems. Redis is an in-memory database that emphasizes high-performance reading and writing and flexible data structures, while the database is a persistent database that emphasizes data persistence and structuring. Inquire. Therefore, they can be used complementary, with Redis serving as a cache or temporary storage to accelerate database read and write operations and reduce database pressure.

The relationship between redis and database

The relationship between Redis and database

Redis is an in-memory data structure storage system, and the database is an A persistent data storage system. There are different relationships between them:

1. Data persistence

Redis is an in-memory database. The data is stored in the server memory. After a power outage, the data will be lost. Databases are usually persistent, and data will not be lost even if the server is powered off.

2. Performance

Since data is stored in memory, Redis has extremely high read and write performance and can handle a large number of concurrent requests. The performance of the database is limited by hard disk IO, so the performance is often lower than Redis.

3. Data structure

Redis supports a variety of data structures, such as strings, hashes, lists, sets and ordered sets, and can flexibly store and query data. . Databases usually only support table structures, and the data organization method is relatively fixed.

4. Use cases

Redis is typically used in scenarios that require high-performance reading and writing, caching, or temporary storage of data, such as website sessions, rankings, or message queues. Databases are used to store data that requires persistence, structure, and relational querying, such as user data, transaction records, or product catalogs.

5. Complementarity

Redis and the database can be used complementary. Redis serves as a cache or temporary storage, which can accelerate the read and write operations of the database and reduce the pressure on the database.

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