Memcached and Redis: Which is the Best Option?

It's likely that you've heard of Redis or Memcached if you're considering a server-side caching solution.


Memcached and Redis are both:



● systems for in-memory noSQL key-value storing data
● Applications supplied by the major cloud service providers are accelerated by open source.
● What distinguishes them, then? In this piece, we'll specifically talk about that.

The Description of Redis


Salvatore Sanfilippo developed Redis, which stands for Remote Dictionary Server, in 2009 to increase the scalability of the web log analyzer that his Italian firm was developing. The initial draft was created in Tcl and eventually converted to C. The project only gained traction once Sanfilippo decided to make it open source.


The Description of Memcached


Brad Fitzpatrick developed Memcached a little earlier, in 2003, for his LiveJournal website. It was first created in Perl and subsequently converted to C. Some of the biggest businesses in the world use it.


Memcached vs. Redis


How Redis Saves Information


Redis supports data type operations. As a result, you can access or alter only a portion of a data object rather than having to load the full item to the application level, make the necessary changes, and then re-store the modified object. As I'll describe below, Redis employs an encapsulated version of the malloc/free memory management system, which is a more straightforward method than the Memcached Slab methodology.
Redis supports values up to 512MB and keys up to 512MB in size. This restriction applies to aggregate data types per element (Lists and Sets).


Memcached's Data Storage Method


Memcached, unlike Redis, stores strings that are indexed by a string key, hence it lacks data types. It makes use of less overhead RAM than Redis. Additionally, it is constrained by the machine's memory capacity; if it is full, it will begin to purge values in the order of least recent use. It uses the Slab allocation technique, which divides the memory space into chunks of varying sizes and stores key-value data records of the appropriate size. The memory fragmentation issue is resolved in this way. Memcached supports values up to 1MB and keys up to 250B in size.


Advantages of Data Types


Let's assume the straightforward case of storing a user session object in a cache. The string needs to be loaded, deserialized, the object field modified, serialized, and stored if we use Memcached to modify a single field in the object. The hash data type can be utilized with Redis. Each field in the hash is accessible separately, allowing any CRUD activity (create, read, update, delete) to be performed on each of them. This makes it possible to lessen the necessity of doing it at an application level. Once fewer I/O operations are required efficiency results.


How Memcached and Redis Scale


Modularity of Redis


Redis expands well horizontally since it is primarily single-threaded and has inbuilt support for clustering.


A master/slave design is used in Redis clustering. Because there are two slave nodes for every master node to provide redundancy, if the master fails, the system will immediately promote one of the slaves to become the new master. The drawback of complexity in maintenance comes with this form of scalability. Multiple nodes running simultaneously require more maintenance than a single node does.


Memcached's Scalability


Memcached's multithreading makes it simple to scale it vertically. Giving it more cores and memory is the only requirement. The use of a distributed method can also enable horizontal scaling on the client side. The drawback of this is that Redis already has it; it is more difficult to implement.


Data permanence is a key distinction to keep in mind while choosing between Redis and Memcached.


Redis is primarily an in-memory data storage, whereas Memcached is a volatile in-memory cache.


How Persistence is Achieved in Redis


Redis provides persistence in two separate methods, which is why it is referred to as a data store:


RDB snapshot: Takes a point-in-time snapshot of your whole dataset, stores it on disk, and runs it at predetermined intervals. The dataset can be restored in this manner upon starting.


All write commands executed on the Redis server are recorded in the AOF log, which is an Append Only File log. A dataset can be restored at startup by re-executing all the commands correctly. This file is also kept on disk.


Which is Superior, Memcached or Redis?


Although Redis is undoubtedly more powerful and adaptable, Memcached does perform better in some situations and is quite effective for particular tasks. It has benefits from being multi-threaded, especially when working with huge data.


Redis can speed up case scenarios by lowering network I/O counts and data sizes thanks to its data types, which support data operations. These data operations are just as taxing as getting or setting data.


Both have been utilized by Imaginary Cloud in numerous projects for various clients. Memcached is good because of its simplicity, usability, and ease of setup. Redis is also good due to the benefits of having data types.

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