Functionality and benefits of data caching in Redis

Functionality and benefits of data caching in Redis

Redis is one of the most popular NoSQL databases known for its high performance and many uses.

Learn about the functionality and benefits of data caching in Redis from OneCloudPlanet. Fast access, improved performance and reduced database load. Our experts will help you configure Redis for optimal caching and performance, and provide sample code to help you implement and run data caching in Redis.

The specifics of Redis

Why has this resident database management system become so popular and continues to be actively developed? Because she:

• It has a high speed of operation thanks to data storage in RAM (in-memory), which provides instant access to data;
• Easily scalable horizontally and can accommodate up to 1,000 nodes in practice;
• Redis clusters support master-slave replication and are fault-tolerant. In case of loss of communication with the master node, the cluster automatically promotes one of its replicas to the master, and rebuilds the failed node;
• It has a large user community and a variety of documentation, which makes it an attractive choice for developers;
• Easier to maintain compared to counterparts such as Memcached or Tarantool, while having similar functionality and even surpassing them in some aspects.

Redis is an excellent solution for caching and storing session information, for example to save user routes or contacts during online shopping. In addition, Redis can be used to work with counters and metrics, and it also provides various key deletion strategies.

Unlike other popular in-memory databases, such as Memcached, Redis has the ability to work with structured data. It supports five data types and provides several extensions, each of which provides different operations:

• String — for storing any values ​​up to 512 MB;
• Hash — for storing objects in the form of a hash table;
• List – for saving an ordered list of string values;
• Set — saving a list of unique string values;
• Sorted set — for storing a sorted list;
• A Bitmap is a set of bitwise operations that can be performed on a string of data in Redis. This data type allows efficient manipulation of bits, such as setting, resetting, or checking the value of a particular bit in a string;
• HyperLogLog is a probabilistic data structure used to count the number of unique elements in a dataset. It allows you to get an approximate power value without having to store the elements themselves. This is especially useful for counting unique users, website visitors, or other similar metrics.

Redis provides extensive data handling and caching capabilities, making it an attractive choice for developers looking for an efficient and flexible solution for managing their data.

In addition, it provides the ability to periodically write data to disk. Although this does not guarantee complete protection against data loss, this option increases the reliability of the system.

Redis is a single-threaded database where commands are processed sequentially rather than in parallel. That is why it is often used to build queuing systems.

In this case, Redis acts as an intermediate link between the web server (provider) and the application (consumer). For example, using the List data type, you can unload the server and write data to a queue from which it will be removed by the consumer. The LPUSH and RPUSH commands in Redis implement the functionality of adding new values ​​to the beginning or end of the queue.

Redis and block storage

This database management system and Block Storage can interact in various business-productive scenarios. Here are some ways they can be used together:

• Data storage: Redis typically runs in memory to ensure fast and responsive performance. However, to ensure data retention, block storage can be used to store data in long-term storage. This can be useful for data recovery after restarts or crashes;
• Data Backup: Allows you to create data backups. You can configure the management system to regularly back up data to Block Storage to ensure its security and restoreability;
• Memory expansion: If you have memory limitations, you can use this option as an extended data storage. In this case, part of the data will be stored in Redis RAM, and the rest of the data will be stored in block storage and loaded as needed;
• Storing Blocks and Files on Block Storage Using References in Redis: Can be used to store references to files or blobs (Binary Large Objects) that are actually stored on Block Storage. This allows efficient management of large files or volumes of data, freeing up Redis memory for other operations.

It's important to note that the ways Redis and Block Storage interact may depend on your infrastructure, settings, and application requirements. It is recommended that you do additional research and refer to the Redis and OneCloudPlanet block storage documentation for more detailed information and quality setup and integration guides.

An insider's look at caching in Redis

The cache is an intermediary between the storage and the data requested by the client. Proper configuration and use of the cache can reduce the load on the database server.

Caching in Redis works primarily as an auxiliary database or cache server that interacts with relational databases such as PostgreSQL. Using Redis in conjunction with the main database allows fast loading and updating of small objects and prevents the loss of important data.

When a request is received from a user, Redis checks for the value of the corresponding key. If there is a value, this resident database management system returns the response to the user directly, bypassing the underlying database. If the value is missing, Redis tells the underlying database to remember the key-value relationship for this request.

The effect of its use is especially noticeable in highly loaded systems, when groups of data are requested very often. At low load, such as 100 users per hour, caching may not be of much benefit.

In addition, Redis is not only a cache server, but also provides the ability to work with data structures. It can be used to create lists, hash tables, ordered sets, and provides a simple way to work with these structures, which greatly simplifies development.

Redis: example code and its execution

To use Redis with Python 3, you must install the Redis library and then include it using the import statement. A OneCloudPlanet expert provides an example of a connection, however, the specific implementation of a connection to Redis may depend on the programming language and libraries used. Here is an example of a simple implementation of a connection to Redis in Python using the `redis` library:
 

import redis

# We establish a connection with Redis
r = redis.Redis(host='localhost', port=6379, db=0)

# An example of operations with Redis
r.set('mykey', 'Hello Redis!')  # We set the value of the key
value = r.get('mykey')  # We get the value of the key
print(value)  # We output the value of the key

# We close the connection
r.close()

In this example, we use the `redis` library to connect to the Redis server, set the value of the `'mykey'` key, get the key value, and display it. Then we close the connection to Redis. Note that the `host` and `port` parameters must match the configuration of your Redis server.

Note that this example provides a basis for connecting to Redis and performing basic operations, but a real application may require more functionality and error handling.

In real projects, it is recommended to wrap this construct in a try-except block to handle possible exceptions.

Hence

Using Redis in a cloud platform is of great importance for effective data management and application performance improvement. Redis has powerful capabilities for caching, storing session information, working with counters and metrics, and also supports various key deletion strategies. It allows developers to build fast, responsive and scalable applications.

OneCloudPlanet offers consumers to use Cloud Instances for their needs. We provide high availability, flexibility and scalability of resources, allowing customers to configure their IT infrastructure as efficiently as possible.

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