Application caching is critical to running any large-scale web application. Redis is here to help you with this task.
Each of us met the situation when an application was working slowly. Even the best code will slow down its performance under heavy load.
Caching can be a fast and relatively cheap way to increase performance and reduce response time.
Redis (REmote DIctionary Server) is an open-source, in-memory data store most often used as a distributed cache. It offers a variety of efficient data structures designed to allow lightning-fast access to your data.
Redis is also known as NoSQL Database and key/value store. Because it stores data in memory rather than on a disk, Redis delivers unparalleled speed, reliability, and performance.
Now, what is the in-memory data store? To put it simply, it is a database that keeps the whole dataset in RAM. Each time you query a database or update data in a database, you only access the main memory.
So, there’s no disk involved in these operations. And this is great because the main memory is way faster than any disk.
Why Use Redis as a Cache
The cache’s primary purpose is to reduce the time needed to access data stored outside the application’s main memory space.
Without using a cache, the application interacts with the data source for every request. In contrast, only a single request to the external data source is needed when a cache is employed, with subsequent access served from the cache.
When an application relies on external data sources, the latency and throughput of those sources can create a performance bottleneck. One way to improve performance is to store and manipulate data in memory, physically closer to the application.
This is where Redis comes into play. Redis is built to store all data in memory, delivering the fastest possible performance when reading or writing data.
Redis is extremely fast. It delivers sub-millisecond response times that enable millions of requests per second to power demanding real-time applications.
Typically, you’ll want to store frequently accessed data in Redis so that whenever the data is requested, it can come from the cache instead of your database.
You can then invalidate the relevant cache whenever a change is made to your data so that you can keep your cache up to date.
How Does Redis Cache Work
Let’s say you have a WordPress-based website.
The first time a WordPress page is loaded, a database query is performed on the server. Redis remembers, or caches, this query.
So, when another user loads the WordPress page, the results are provided from Redis and memory without needing to query the database.
An object cache works by caching the SQL queries in the memory needed to load a WordPress page. Then, when a page loads, the resulting SQL query results are provided from memory by Redis, so the query does not have to hit the database.
The result is faster page load times and less server impact on database resources.
It’s way faster to access data in memory (physical RAM) than in the hard drive. So it’s easy to notice that if the data that the application wants to access is inside the main memory, it’s way easier to reach that data than if it was stored on the Hard Drive.
If a query is not available in Redis, the database provides the result, and Redis adds the result to its cache.
However, suppose a value is updated in the database (for example, a new post or page is created in WordPress). Then, the Redis value for that query is invalidated to prevent insufficient cached data from being presented.
Why Use Redis?
- Quick response database: stores data in memory rather than on a disk; its response time is faster than others when performing read and write operations. It can be used together with other databases as a support to reduce load and improve performance but can also be used as a primary database.
- Data persistence: Redis uses persistent disk storage to survive process outages and network bottlenecks.
- Session Cache: One of the most apparent use cases for Redis is using it as a session cache. Using Redis over other session stores is that Redis offers persistence.
- Key-based access: Redis is based on the key-value model in which data is stored and fetched from Redis by key. Key-based access allows for highly efficient access times, and this model maps naturally to caching.
So, we have only scratched the surface of the information available on this topic. You can visit the documentation with the available resources outlined for more information on learning Redis.