Redis data types and their common usage scenarios

Redis data types and their common usage scenarios

The official website provides visual client and more detailed introduction: https://redis.io/docs/

Redis (Remote Dictionary Server) is a high-performance key-value storage database that supports multiple data types, making it an ideal choice for a wide range of scenarios such as caching, message queues, counters, and session storage. The following is a brief introduction to the common data types of Redis and their usage scenarios.

1. String

String is the most basic data type in Redis. It can contain any type of data, such as text, JSON data, serialized objects, etc. The maximum length of each string is 512 MB.

Common usage scenarios:

• Caching: Cache frequently accessed data in Redis to speed up reading.
• Counter: can store and increment/decrement integer values, suitable for implementing functions such as likes and counting.
• Distributed locks: Distributed locks can be implemented based on the SETNX command to ensure atomic operations in a distributed environment.

2. List

A list is an ordered collection of strings, and elements can be inserted and deleted at both ends of the list. It allows duplicate elements to exist.

Common usage scenarios:

• Message queue: Add tasks to one end of the list, and then use the other end to consume the tasks to implement a simple message queue function.
• Latest news: Maintain a chronological message list to display the latest news content.

3. Set

A set is an unordered collection of strings that does not allow duplicate elements.

Common usage scenarios:

• Social network: stores the user's watch list, fan list, etc.
• Deduplication: Can be used to deduplicate data and quickly identify whether a collection contains an element.

4. Hash

A hash table is a collection of key-value pairs, which can be understood as storing a Map or Dictionary data structure into Redis. Each hash table can store 2^32 - 1 key-value pairs.

Common usage scenarios:

• Object storage: Store object fields in the form of hash tables to facilitate reading and update operations.
• Account information: Stores the user's account information, such as user name, email, points, etc.

5. Sorted Set

Sorted sets are similar to sets, but each member is associated with a score, which is used for sorting. Members are unique, but scores can be repeated.

Common usage scenarios:

• Ranking list: Rank users according to their scores, suitable for ranking functions such as games and article readings.
• Range query: Query based on score range, such as finding data within a specified time period.

6. Geospatial index (GeoSpatial)

Geospatial index is a data type introduced in Redis version 3.2, which is used to store geographical location information and support spatial queries.

Common usage scenarios:

• People nearby: Query other nearby users based on the user's geographical location to implement social functions.
• Geofencing: Perform a fence query on a geographical area to determine whether a certain location is within the fence.

Redis provides a rich data structure that can flexibly meet the needs of different scenarios. However, when using Redis, you must also pay attention to the selection and reasonable use of data structures to ensure the performance and stability of the system.