Redis is an open-source, in-memory data structure store that can be used as a cache. It is designed to deliver high-performance and low-latency access to frequently accessed data. Redis is often utilized as a cache due to its ability to store data in memory, allowing for quick retrieval and reducing the need to fetch data from slower disk-based storage. Redis supports many data structures such as strings, hashes, lists, and more. It also provides features like persistence, replication, and Lua scripting. Redis is commonly used as a cache because it can significantly improve the performance of web applications by reducing the number of requests to the database.

What is Caching?

Caching is a technique used in computer systems to store frequently accessed data in a temporary storage location for quick retrieval. It involves keeping a copy of data or computations in a cache, which is typically a faster and closer-to-access storage medium compared to the original source.

The primary goal of caching is to improve system performance by reducing the time and resources required to retrieve data. When data is requested, instead of directly accessing the original source (such as a database, file system, or API), the system first checks if the data is available in the cache. If it is, the data can be retrieved quickly without the need for accessing the original source, resulting in faster response times and reduced load on the underlying system.

Caching operates based on the principle of locality of reference, which suggests that recently accessed data is likely to be accessed again in the near future. By storing frequently accessed data in a cache, subsequent requests for the same data can be served more efficiently, improving overall system performance.

What is Redis Cache?

Redis Cache refers to the caching functionality provided by Redis, an open-source in-memory data structure store. Redis can be used as a cache to store frequently accessed data in memory, enabling fast retrieval and reducing the need to fetch data from slower data sources such as databases or APIs.

Redis Cache offers the following key features:

In-memory storage:

Redis stores data in RAM, allowing for lightning-fast read and write operations. This provides significant performance benefits compared to disk-based storage systems.

Key-value store: 

Redis follows a key-value data model, where each piece of data is associated with a unique key. This simplicity allows for efficient caching, as data can be quickly accessed and stored based on its corresponding key.

Data expiration and eviction: 

Redis allows you to set an expiration time for cached data. Once the expiration time is reached, the data is automatically removed from the cache. Redis also supports eviction policies, which determine how data should be evicted when the cache reaches its memory limit.

Advanced data structures and operations:

Redis offers a variety of data structures such as strings, lists, sets, hashes, and more. These structures enable complex caching scenarios and support operations like atomic updates, increment/decrement, set operations, and pub/sub messaging.

Persistence options: 

Redis provides options for persisting data to disk, ensuring data durability in case of system restarts or failures. This allows you to configure Redis as a cache with persistence or as a pure in-memory cache, based on your requirements.

Scalability and high availability: 

Redis supports replication and clustering, allowing you to distribute the cache across multiple nodes. This provides scalability and fault tolerance, ensuring that your cache can handle increased traffic and remains highly available.

By utilizing Redis Cache, applications can significantly improve performance by reducing the latency associated with retrieving data from slower storage systems. It enables faster access to frequently accessed data, reduces the load on primary data sources, and enhances overall application responsiveness and scalability.

How Does Redis Work?

Redis works as an in-memory data structure store that follows a client-server model.

Client-Server Communication: 

Redis clients interact with the Redis server using a protocol known as Redis Protocol or RESP. Clients send commands to the server and receive responses in a request-response manner.

In-Memory Data Storage:

 Redis stores data in memory, which allows for high-speed read and write operations. This in-memory storage is one of the key factors that contribute to Redis’ fast performance.

Key-Value Data Model: 

Redis follows a key-value data model, where each piece of data is associated with a unique key. The key is used to store and retrieve data from Redis. Keys can be simple strings or more complex data types such as lists, sets, hashes, or sorted sets.

Data Expiration and Eviction: 

Redis allows you to set an expiration time for keys, after which the data associated with the key is automatically removed from the cache. This feature helps manage memory usage and ensures that stale data is cleared from the cache. Redis also supports eviction policies to handle scenarios when the cache reaches its memory limit.

Advanced-Data Structures and Operations:

Redis offers a variety of data structures such as strings, lists, sets, hashes, and sorted sets. These structures provide flexibility in storing and manipulating data. Redis also provides a rich set of operations for each data structure, enabling efficient data manipulation and retrieval.

When and why to use Redis?

Redis (Remote Dictionary Server) is an open-source, in-memory data structure store that can be used as a database, cache, and message broker. 

Here are some scenarios where Redis is commonly used:

• Redis is often used as a cache due to its exceptional performance and low latency. By storing frequently accessed data in Redis, you can reduce the load on your primary database and speed up read operations. Redis allows you to set expiration times for cached data, making it suitable for scenarios where data needs to be stored temporarily.
• Redis is well-suited for storing session data in web applications. Instead of storing session information on the server’s memory, which can be problematic for scalability, you can store it in Redis. This approach allows you to distribute session data across multiple servers and provides persistence even if a server restarts.
• Redis supports publish/subscribe messaging patterns. It can act as a message broker, enabling communication between different components of your system. Publishers can send messages to specific channels, and subscribers receive those messages in real-time. This feature is useful for building real-time applications, chat systems, and event-driven architectures.
• Redis provides atomic operations, which allow you to perform operations on data in a single step. This capability makes Redis suitable for implementing leaderboards and counters. You can increment or decrement values stored in Redis, allowing you to track scores, votes, likes, or any other type of numerical data.
• Redis provides an extension called Redisearch, which adds full-text search capabilities to Redis. It allows you to index and search text data efficiently. Research supports advanced search features like stemming, tokenization, and exact phrase matching.
• With Redis, you can implement rate limiting and throttling mechanisms for APIs and web applications. By tracking requests per second or per minute, you can control the flow of traffic and prevent abuse or excessive usage of resources.

Redis Language support

Redis supports multiple programming languages through various client libraries. Some of the popular programming languages with Redis client libraries include:

• Python: 
• The official Redis client for Python is called “redis-py.” It provides a high-level Pythonic interface to interact with Redis and supports features like connection pooling, pipelining, and pub/sub messaging.
• Java:
• For Java, the most commonly used Redis client library is “Jedis.” It offers a straightforward API to connect to Redis, execute commands, and handle responses. Another popular option is “Lettuce,” which is a high-performance Redis client with support for asynchronous operations.
• JavaScript:
• Redis has client libraries for JavaScript that enable Redis usage in Node.js applications as well as browser-based applications. Some popular JavaScript Redis client libraries include “ioredis,” “redis,” and “node_redis.”
• Ruby:
• The primary Redis client for Ruby is “redis-rb.” It provides a simple and intuitive API to work with Redis in Ruby applications. Additionally, there are other client libraries like “hired” and “redis-objects” that offer additional features and abstractions.
• PHP:
• Redis has a client library called “phpredis” that provides a fast and efficient way to interact with Redis in PHP applications. It offers both a procedural and an object-oriented API for accessing Redis features.
• C#: 
• Redis clients for C# include “StackExchange.Redis” and “ServiceStack.Redis.” These libraries offer high-performance Redis access and support features like pipelining, pub/sub, and connection pooling.
• Go: 
• The popular Redis client library for Go is “go-redis.” It provides a robust and feature-rich API to work with Redis, including support for transactions, pipelining, and pub/sub.
• Redis vs. Memcached
• Data Structure Support: Redis provides a wider range of data structures compared to Memcached. Redis supports not only simple key-value pairs but also more complex data types like strings, lists, sets, hashes, sorted sets, and more. This allows for more flexibility and enables advanced operations on the cached data.
• Persistence: Redis supports data persistence, which means you can configure Redis to save data to disk periodically or on specific events. This feature ensures that cached data is not lost even in the event of a server restart. Memcached, on the other hand, does not provide built-in persistence and relies solely on in-memory storage.
• Replication and Clustering: Redis supports replication and clustering, allowing you to distribute data across multiple nodes and achieve high availability. Redis provides various replication options, including master-slave replication and Redis Cluster, which allows for sharding and automatic failover. Memcached, however, does not have built-in support for replication or clustering.
• Additional Features: Redis includes several additional features that are not present in Memcached. For example, Redis has built-in support for pub/sub messaging, which allows for message passing between components of a system. Redis also offers Lua scripting, which enables you to execute complex operations on the server side. These features make Redis more versatile and suitable for a broader range of use cases.
• Performance: Both Redis and Memcached are highly performant and designed to provide low-latency access to cached data. However, Redis often boasts slightly better performance due to its more optimized implementation and advanced features like data compression and pipelining.
• Ecosystem and Community: Redis has a larger ecosystem and a more active community compared to Memcached. Redis has a wide range of client libraries available for different programming languages, along with comprehensive documentation and community support. Redis also offers various modules and extensions, such as Redisearch and RedisJSON, which enhance its functionality further.

Redis provides a more feature-rich caching solution compared to Memcached. It offers a broader range of data structures, persistence options, replication, and clustering capabilities. Redis also includes additional features like pub/sub messaging and Lua scripting. However, if you have a simple use case and prioritize raw caching performance, Memcached can still be a suitable choice.

Using Redis on CyberPanel

For Redis to work on your PHP site, you need to create it in CyberPanel and note the PHP version you select when creating the site, as we will use it later to install the Redis PHP Cache extension.

 Read this article to learn how to install Redis  on CyberPanel