The Only Redis Guide You'll Ever Need
Redis is an open-source data structure server. It has gained popularity as one of the most famous options with developers among a swarm of the latest database options for speed and performance.

Modern applications have a usual list of requirements to not only survive but progress in today's quick-paced cloud environments. These include quicker response times (less than 100 milliseconds), unlimited scalability, big availability, and considerable performance.

Hence, there are 5 primary aspects you should take care of while using this technology:

1. Maintain a Record of your Keys with Redis Namespace

Databases might store information, however, any database development company can miss the log of some of the information you’re publishing into this server. This can be due to the application’s requirements being dynamic or you changing the method of storing data. Maybe a module of the application has become outdated or you’ve ignored to stop using some of the keys.

Besides namespace, the secondary data store is also a common use case for Redis development to store “hot” data pieces. This happens when you keep the majority of the data in some other database. Developers at times, forget to delete the data from this database while it is transferred to a basic data store.

2. Rely on perfect Data Structures

Depending upon the memory capturing or performance, maybe one data structure is a better option for your data components than another. Below are some practices to follow:

a) Try to group related data with a data structure instead of keeping your data in plenty of specific string values. Hashes can be effective and lower memory usage. They also provide the added value to retrieve some of the components to improve the readability of your code.

b) If applicable, use reply on lists rather than sets. In case you don’t need the set’s properties for making sure about the individuality or checking membership, a roster will take less space and operate as inserts quicker.

c) In terms of both, basic operations complications and memory consumption, defined sets are considered to be the most costly data system. Try to use hashes if you are only up to scores and its partner does not matter.

3. Do not count on KEYS, rather rely on SCAN

The SCAN starts with Redis v2.8, enabling you to acquire keys via a cursor in the keyspace. This is not like the behavior of the KEYS command that gives back all matching elements. It is in fact, considered dicey in production as it may prevent your Redis database and also deplete its RAM resources. With SCAN, you can inspect data without stopping your server or counting on a slave.

4. Keep a log of the stretch of your key names

In contrast with the above point, key names require memory too so you should keep short and easy to remember names. This can become a problem with datasets that contain millions and trillions of keys. However, large keys are attached with any hashtable at a cost.

5. Use of Server-Side Lua Scripts

Once you realize Redis’s potential to handle Lua scripts, you will be navigating familiar ground. Lua provides you with your creativity to code that operates within the Redis server as it is one of the easiest languages to pick up. If applied perfectly, Lua can make all the difference in the world based on resource consumption and performance. Scripts can execute logic close to the information instead of bringing data that decrease unnecessary transmission of data and network latency.

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