Consider databases the backbone of any application; without them, you’re left stranded, like a skeleton in the sea, useless. In general, the overall app performance is mainly dependent on database performance. Many factors affect performance, including the use of indexes. To have a better app performance, it is good to use a Redis database system which is the most preferable.
A relational database system without having a cache works in the following way:
- The user will send the request to the server.
- To fetch the relevant data, the server queries the database
- The database retrieves and sends the data to the server.
You even write better queries to optimize this system which improves the performance. Anyway, this will not be helpful when it comes to scaling the application for thousands of users.
What is database cache and the types of cache?
A database cache is a system that saves results from the database to return the result faster next time when you send the query request.
There are two types of database cache:
- Internal Cache: In this, everything will be kept ready thinking that you may need based on the usage patterns.
- Query Cache: If the query is made more than once, the result will be cached and returned from RAM instead. When the allotted RAM runs out, the system deletes the least recently used query to make space for new ones.
How to use Redis as Cache?
Here are the steps to follow for Redis to implement as cache.
- Step 1: Install Redis – For Ubuntu – apt-get install Redis-server, for Mac – brew install redis
- Step 2: Configure Node.js and Redis: npm i redis
How do caching works?
Fast access hardware, such as RAM, typically stores the data cache and may also be used in parallel with a software component. A cache’s primary purpose is to enhance data retrieval performance by reducing the need to access the underlying slower storage layer.
What is Redis: In-memory datastore?
Redis, an open-source, in-memory data structure store, serves as a database, cache, and message broker, and it’s so fast because it’s developed in the C programming language.
What are the languages supported by Redis database?
Redis generally supports several programming languages with a vast list of Redis clients. Here’s a list of some popular programming languages below:
- C
- C#
- C++
- PHP
- Perl
- Java
- Js
- PL/SQL
- Swift
- Scala
- Go
Redis supports many data types, such as:
- Strings
- Hashes
- Lists
- Sets
- Bitmaps
- Hyperloglogs
- Geospatial Indexes
What is the architecture overview of Redis?
A single Redis architecture comprises of:
- Redis Client
- Redis Server
These two components will be on the same computer. The Redis server looks after storing and handling the data. The Redis Client is a Redis console or a programming language’s Redis API. It is volatile, as Redis stores everything on RAM. Hence you need to ensure that the data is persistent.
What is Redis Persistence?
Redis achieves persistence in the following ways:
- RDB Mechanism
- AOF
- SAVE
How does Redis Work?
Redis cache stores data in an in-memory format in the form of key-value pairs which means that the Redis stores data in the RAM enabling for a quick read and write speeds when compared to relational databases that stores data on SSDs or HDDs. Redis can do away with seek time suspensions by storing data in-memory. The critical data type can be a string, but the value of the data types that it uphold such as string, list, and so on.
Example of Redis key-value pairs:
What are the benefits of Redis Database?
- Network calls to the database will get reduced: The best example to describe this is the Facebook User Profile which is accessed frequently. Each time the user sends queries to the server, the system caches the data, eliminating the need for a network call to the database.
- Lessens re-computations and database load from multiple servers: Complex database computations results will be stored on your cache for faster turnaround times and lessening database rework. The critical factor for this is deciding which computations users request most frequently and storing only those in the cache.
- Highly scalable and available: A cache-based system reduces or distributes the number of queries that your database needs to handle. By this way, the server can handle more concurrent requests and reduce the load on your database.
- Performance: Server performance can be analyzed based on how quick it can handle a request. The cache, positioned between the server and database, significantly reduces response times for data already available in it.
- Open-source community: As Redis is an open-source database having huge community to support for data formats and languages. So it won’t have vendor lock-in or technological barrier issues.
Top use cases of Redis
Redis can be used for a myriad of things:
- Caching: Redis has impressive caching speed both for read and write, which result from being stored on the primary in-memory. Redis has sub-millisecond response times and highly reduced latency and load on your traditional RDMS/NoSQL database.
- Forums: Forums mostly rely on a high-performing message broker, with Redis supporting List data structures and hashes, making it ideal.
- Live chat rooms: Live chat rooms also utilize robust high-performing message brokers, with Redis extensively supporting list data structures and hashes.
- Live game leaderboards: Redis database is the best-opted database with Sorted Set data structure.
- Media Streaming: Redis makes the users stream the content without any lag, as online media streaming companies like Youtube, Netflix always need fast cache for metadata, viewing histories, timelines for extremely smooth viewer experience.
- Real-time analytics: With a high-speed about sub-milliseconds latency, Redis helps with real-time data analytics for social media, ad-tech and many more.
What is the cache policy?
No one will invest everything just on the cache as it is a bad idea. Calling the process of deciding what to put in the cache and what to evict from it cache policy. Here are two reasons why it is a bad idea to invest everything in the cache.
Reason 1: Hardware used for caching is costly
Reason 2: Search times increase when the cache has a lot of data. Cache becomes counterproductive.
What are the strategies for designing your Cache policy?
Basing on the use cases, there are different types of caching strategies for designing your cache policy. Some of the cache policy designs are:
- Read-through: The Cache sits in-line between the server and database
- Write-back/write-behind: This is similar to write -through the only difference is it won’t update the database for every write operation. To reduce network calls, the system updates the queries after a certain period of delay.
- Cache-aside: Server queries the cache first to fetch the data. You should securely host and adequately resource your database.
- Write-through: This is similar to read-through in which all writes will go through the cache. This is consistent with the database.
To Conclude
Redis database caching can improve user experience and application performance. Optimizing database performance is not just one and done deal, and it needs diligence and ongoing communication between admin and developers. You should securely host and adequately resource your database. Using Redis, you can deliver the best experience to your users.
Krify is one of the top mobile app and website development company based in India and UK having skilled APIs developers who can provide immense knowledge on using Redis database. For more details, contact us now.
