Why and when to use Redis ?

Before diving into Redis, let's explore why Redis has become a critical component in modern IT landscapes.

Over the years, information technology has revolutionized business processes, evolving from a mere luxury to an absolute necessity for enterprises worldwide. Applications lie at the heart of these processes, and their importance has grown exponentially. Consequently, response time has become a paramount concern. Swift data retrieval significantly influences user experiences and stands as a pivotal requirement in nearly all commercial applications. Several factors, including the overhead of fetching data from databases, network latency, protocols, hardware, software, and internet speed, can impact response times. The vast IT infrastructure and ever-increasing demands for system performance pose significant challenges to organizations' strategic objectives.

This section aims to shed light on caching mechanisms as a means to enhance application performance.

Understanding Caching

Caching involves temporarily storing frequently accessed data in a memory buffer, thus improving performance by eliminating the need to retrieve data repeatedly from the original source. Caching is a concept that has found applications across various domains in the computer and networking industry. A common example is the web browser cache, which stores requested objects to prevent redundant data retrieval.

In-Memory Databases

In-memory databases, also known as main memory databases, store data in RAM rather than on a hard disk, enabling faster responses. These databases use compressed data formats and offer robust SQL support. In-memory databases can be integrated into an existing application stack without requiring changes to the application layer. However, scaling an in-memory database typically involves vertical scaling.

In-Memory Distributed Caching

Distributed caching, employing key-value pairs, can be implemented externally to an application. It stores frequently accessed data in RAM, reducing the need for continuous data fetching from the data source. Distributed caches can be deployed across a cluster of multiple nodes, creating a unified logical view. Hashing algorithms determine the location of objects within the cluster nodes.

Introducing Redis

Redis, according to its homepage, is an open-source (BSD licensed) in-memory data structure store utilized as a database, cache, and message broker. Redis supports various data structures, including strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes with radius queries, and streams.

Redis: A Unique Approach

Redis popularized the concept of a system that serves as both a store and a cache. It maintains data in the primary computer memory while also storing it on disk in a format unsuitable for random data access. This design choice is distinct from traditional relational database management systems (RDBMS), where user commands articulate queries executed by the database engine. Redis, instead, provides specific operations performed on abstract data types, necessitating data storage conducive to swift retrieval without the assistance of secondary indexes or common RDBMS features. Redis relies heavily on the Fork system call to duplicate processes holding data, allowing the parent process to continue serving clients while the child process recreates the data in memory following system restarts.

Why Redis?

Redis serves a multitude of purposes. As an example, Redis can store website sessions, enabling "sticky sessions" across multiple servers. This ensures that a user's login persists even when connecting to different servers within the same website, similar to how platforms like Facebook maintain user sessions across server instances. Beyond session storage, Redis finds applications in various scenarios, including message broadcasting, real-time data storage, job queues, and rate limiting. Its support for diverse value types and structures opens up numerous use cases.

Advantages of Redis

Redis offers a multitude of advantages:

→ Large Data Storage: Redis can store key-value pairs as large as 512 MB, allowing for extensive data storage.

→ Custom Hashing: Redis uses its unique Redis Hashing mechanism for storing data.

→ Data Replication: Redis supports data replication, ensuring that updates to the master node are automatically reflected in slave nodes.

→ Cross-Platform Client Support: Redis boasts client APIs for popular programming languages.

→ Pub/Sub Messaging: Redis facilitates high-performing messaging applications using Publisher/Subscriber technologies.

→ Mass Data Insertion: Redis simplifies the insertion of large data quantities into its cache.

→ IoT Compatibility: Redis can be installed on IoT devices like Raspberry Pi and ARM devices.

→ Simple Protocol: Redis employs the Redis Serialization Protocol (RESP), which is straightforward and human-readable.

→ Transaction Support: Redis supports transactions, allowing multiple commands to be executed as a queue.

→ NoSQL Database: Redis operates as a NoSQL database, eliminating the need to learn SQL.

Conclusion

Distributed caching is a widely-adopted design pattern for building robust and scalable applications. By serving data from the cache instead of fetching it repeatedly or recomputing it, overall application performance is significantly improved. Redis is the most popular distributed caching engine today, known for its reliability and a wide range of capabilities that make it an ideal choice for caching layers in applications. Redis Cloud and Redis Labs Enterprise Cluster (RLEC) extend the capabilities of open-source Redis, making it even more suitable for caching purposes.

In summary, Redis is a powerful tool that can elevate application performance, offering speed, versatility, and robustness for a wide array of use cases in modern software development.