Skip to main content

Memcached Vs Redis : Which one to pick ??

Memcached is a general-purpose distributed memory caching system. It is often used to speed up dynamic database-driven websites by caching data and objects in RAM to reduce the number of times an external data source (such as a database or API) must be read.
Redis is a flexible, open source and advanced key-value store. It is referred to as a “data structure server” where keys can contain strings, lists, hashes, sets and sorted sets of strings.
redis_memcached_new
The main differences between them are listed below:
Installation:
Comparing ease of Installation Redis is much easier. No dependencies required.
Memory Usage:
For simple key-value pairs memcached is more memory efficient than Redis. If you use Redis hashes, then Redis is more memory efficient.
Persistence:
If you are using Memcached then data is lost with a restart and rebuilding cache is a costly process. On the other hand, Redis can handle persistent data. By default, Redis syncs data to the disk at least every 2 seconds.
Replication:
Memcached does not supports replication. Whereas Redis supports master-slave replication. It allows slave Redis servers to be exact copies of master servers. Data from any Redis server can replicate to any number of slaves.
Storage type:
Memcached stores variables in it’s memory. It retrieve any information directly from the servers memory instead of hitting the database again. On the other hand, Redis is like a database that resides in memory. It executes (read and write) a key/value pair from its database to return the resultset and all data resides in memory.Developers are using Redis also for real-time metrics, analytics.
Read/Write Speed:
Memcached is very good to handle high traffic websites. It can read lots of information at a time and give you back at a great response time. Redis can also handle high traffic on read but also can handle heavy writes as well.
Data Structure:
Memcached uses string and integer as data structure. Everything you save can be either one or the other. With integer, the only data manipulation you can do is adding or subtracting them. If you need to save arrays or objects, you will have to serialize them first and then save them. To read them back, you will need to un-serialize.
In comparison Redis has a stronger data structures. It can handle not only strings, integer but also binary-safe strings, lists of binary-safe strings, sets of binary-safe strings and sorted sets.
Key Length:
Memcached key length has a maximum of 250 bytes, whereas Redis key length has a maximum of 2GB.
If you need advanced data structures or disk-backed persistence, you should look into Redis. On the other hand, you might want to stick to Memcached for its simplicity, reliability and speed.

Comments

Post a Comment

Popular posts from this blog

Sexy C#

Download samples   Table of Contents   1.   Introduction  2.   Background    3.   Sexy Features 3.1.   Extension Methods   3.2.   Anonymous Type   3.3.   Delegate   3.4.   Lambda Expression 3.5.   Async-Await Pair   3.6.   Generics   4.   Conclusion   1. Introduction     C#  is a very popular programming language. It is mostly popular in the .NET arena. The main reason behind that is the C# language contains so many useful features. It is actually a multi-paradigm programming language. Q.   Why do we call C# a muti-paradigm programming language? A.  Well, C# has the following characteristics:  Strongly typed   Object Oriented  Functional  Declarative Programming  Imperative Programming   Component based Programming Dynamic Programming ...
Post a Comment
Read more

Making Python Programs Blazingly Fast

Let’s look at the performance of our Python programs and see how to make them up to 30% faster! Python  haters always say, that one of the reasons they don’t want to use it, is that it’s  slow . Well, whether specific program — regardless of the programming language used — is fast or slow is very much dependent on the developer who wrote it and their skill and ability to write  optimized  and  fast  programs. So, let’s prove some people wrong and let’s see how we can improve performance of our  Python  programs and make them really fast! Timing and Profiling Before we start optimizing anything, we first need to find out which parts of our code actually slow down the whole program. Sometimes the bottleneck of the program might be obvious, but in case you don’t know where it is, then here are options you have for finding out: Note: This is the program I will be using for demonstration purposes, it computes  e  to pow...
Post a Comment
Read more

Kubernetes – init containers, CNI and more

Certain questions about Kubernetes seem to come up again and again: What’s up with this init container stuff? What’s a CNI plugin? Why is Kubernetes complaining about pods not finishing initialisation? Kubernetes is a complex system with a simple overall purpose: run user  workloads  in a way that permits the authors of the workloads to not care (much) about the messy details of the hardware underneath. The workload authors are supposed to be able to just focus on Pods and Services; in turn, Kubernetes is meant to arrange things such that workloads get mapped to Pods, Pods get deployed on Nodes, and the network in between looks flat and transparent. This is simple to state, but  extremely  complex to implement in practice. (This is an area where Kubernetes is doing a great job of making things complex for the Kubernetes implementors so that they can be easier for the users – nicely done!) Under the hood, Kubernetes is leaning heavily on a number of technologies to ma...
Post a Comment
Read more