Redis as Cache: How it Works and Why to Use it
Redis as Cache: How it Works and Why to Use it. In this article, I introduce Redis and it’s function of caching. Additionally you learn how it works and why is it worth using it.
Topic of a cache is definitely gaining a lot of popularity globally. Not only the process is very fast, but it is also incredibly easy to use. Please, stay tuned and let me explain why you should be the one to use Redis as a cache.
Surely, most people have encountered a situation where an application runs slowly. Even the best code, under heavy load slows down its performance. The solution is caching. A relatively cheap and fast way to improve performance and reduce response times.
Please continue with this article about Redis cache further.
Redis as Cache
As for Redis, Redis stands for Remote Dictionary Server. In nutshell, it is a caching system, that works by temporarily storing information in key value data structures.
So yes, Redis is often used as a cache due to its high performance and in memory storage features. It is used to store frequently accessed data that can be retrieved quickly. Thanks to this feature, it reduces the load on the database and improves the overall performance of the application. What is more, Redis also provides various data structures such as lists, sets, and hashes that are used to store different types of data and support more complex caching scenarios.
What is Caching?
First off, what is caching? Mostly, caching is a temporary storage mechanism that allows websites to load information faster. Instead of accessing the database directly, the website accesses a cached version and retrieves the information it needs from server memory.
All in all, caching is used to improve the performance of many types of applications such as web applications, mobile applications, and APIs. It is used to cache different types of data such as HTML, JSON, images and other files. Not forgetting the benefit of caching, that it leads to a database performing much faster, by keeping frequently accessed data in memory.
How exactly does the Redis Cache work?
Well, primarily, Redis cache keeps frequently accessed data in memory for fast retrieval. When a data request is made, Redis first checks memory to see if the requested data is already stored in memory. When data is found, it is immediately returned to the client. If it can’t find the data in memory, Redis looks for it in disk storage, or requests data from the underlying data source, if configured. Once data is retrieved, it is stored in memory for future requests.
In addition, it also supports a feature called “expiration” or “Time to Live” (TTL), which allows data to be automatically deleted from the cache after a certain period of time. This feature helps keep the cache from growing too large and keeps the data stored in the cache up-to-date.
Another feature of Redis is called “Least Used Items” (LRU) that automatically removes the least used items when memory is low. This feature helps control the cache size.
Besides, redis supports various exclusion policies, such as LFU to remove the least frequently accessed element and Random to remove random elements.
Cache Purpose
The main purpose of cache is primarily to reduce the interaction time to data that is stored outside of our application’s main memory.
When not using the cache, the application interacts with the data source for each request. Conversely, when caching is applied, only one request to the external data source is required, and subsequent accesses are made from the cache.
In fact, when an application supports itself on external data sources then the bandwidth of these sources and their latency create quite slow performance. In this case, the main performance improvement we make is by storing and manipulating data, physically in the application.
But, this is where Redis comes into play. Designed to keep all data in memory, providing the best possible performance when reading or writing data.
All in all, processing is very fast. With sub millisecond response times, it handles millions of requests per second for demanding real time applications.
Typically, purpose of storage of data frequently accessed is so, whenever the data is requested, it is fetched from a cache rather than a database.
Generally you keep the cache up to date by invalidating that cache whenever data changes.
Cache in Redis (use cases)
Afterwards, caching is used in many forms and at different levels of application. For example:
A). Implements a highly available in memory cache, that in turn leads to decrease data access latency, improved throughput and easing load in relational databases or NoSQL database.
B). Additionally it serves frequently requested items at millisecond response times. That leads to faster scaling of your loads.
C). Then another example is database query results caching, as well as persistent session caching.
D). Also we have web page caching, including caching of frequently used objects (files, images and metadata).
E). Web applications caching as well as operating systems and also content delivery networks (CDNs). Then, caching stores data on a network of geographically dispersed servers and the nearest location delivers the data to users.
F). Improves input/output operations per second (IOPS). That is for heavily loaded applications, such as social networking apps and media sharing systems. Not to mention, cache benefits for big performance computing simulations.
H). Client side caching, where data is stored in the client’s browser.
More about why Use Redis?
Session Cache – One of the most obvious use cases for Redis is it’s session cache. That leads to persistence.
Key based access – It is based on the key value model of storing and retrieving data by key in Redis. Key based access provides highly efficient access times, and this model maps naturally to caching.
Quick response database – It stores data in memory rather than disk. When performing read and write operations, the response time is faster than others. It is used with other databases as support to reduce load and improve performance, but can also be used as a primary database.
Benefits of Redis as cache?
Redis offers several advantages when used as a cache:
Speed – Because Redis stores all data in memory, data access and retrieval is faster than traditional disk storage systems. This makes it an ideal choice for high performance applications requiring fast data retrieval.
Popularity – Widely used and has a large and active community, making it easy to find support and resources for development and troubleshooting.
Data Persistence – Supports various save options such as RDB and AOF, allowing data to be saved to disk and restored in case of crash or restart. This helps ensure that no data is lost in the event of a crash.
Scalability – Easily scale horizontally by adding more nodes to your cluster to increase storage capacity and improve performance. This makes it suitable for use in high traffic, highly scalable applications.
Advanced eviction policies – There are built in eviction policies such as LRU, LFU, Random and TTL to help control cache size and keep data fresh.
Data structures – Redis supports various data structures such as strings, hashes, lists, sets, etc. This allows you to use the data structure that best suits your caching needs.
Easy to use – Redis is an easy to use caching solution and provides simple commands for storing and retrieving data.
Thank you for reading Redis as Cache: How it Works and Why to Use it. We shall conclude the article now.
Redis as Cache: How it Works and Why to Use it Conclusion
In conclusion, Redis is an excellent choice for a cache because of its speed, persistence, scalability, support for data structures, and ease of use. Its in memory architecture and persistence support make it well suited for high performance systems and real time applications. Lastly, it is a popular and reliable choice for a variety of system types and use cases.
Visit our to read more about Redis over here.
