Memcached or Redis? Which one to Choose? It’s a difficult decision for a developer to select between the two types of cache systems. In this article you will learn about the benefits of each along with similarities and reasons to choose any of them.
If you need better performance of your application then fast caching is the very first step. The next thing that comes to mind is Redis or Memcached. Memcache is considered an efficient choice.
There are many similarities as well as differences between the both types of cache engines.
Redis is new but more adaptable. Hence, it’s often a matter of preference.Memcached is a general-purpose distributed memory-caching system whereas Redis is an in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
Similarities between Redis and Memcache:
They both work as in-memory key value data stores. These both caches engines belong to NoSQL data management solution. They store data in RAM, hence it acts as a powerful caching layer. If we see performance of both cache engines then they are quite identical in terms of latency and throughput.
They both are open source projects. Memcached was developed by Brad Fitzpatrick in 2003 which was actually intended to be used for a livejournal website.. Originally it was implemented in Perl but it has been rewritten in C and is available in public domain. Stability and new features addition is the focus of new development in memcached.
Redis was developed in 2009 by Salvatore.sanfilippo. Redis is often referred to as “Memcached on steroids”.
Many features in Redis were developed in the inspiration of Memcache but now Redis is more features enriched than memcache. Also,it’s more popular and flexible than memcached.
These both cache engines are being used by many companies in crucial production environments. Memcached and Redis both support clients libraries. They are provided to developers with many packages.
Redis and memcached are very simple and effective. Many developers say it’s easy to start working in any type of these caches. It takes couples of minutes only to start working on an application. Hence, you may increase performance dramatically by little time and effort.
When Memcached is Good To Use?
Memcached is used when caching for small and static data is required. For example: HTML Code Fragments. Its internal memory management is not upto the level as compared to Redis. Memcached consumes low memory as compared to its counterpart for metadata.
Strings is considered as the ideal data type for storing data which is read only because strings don’t need further process and strings is the only supported data type in memcached.
Large data sets require more space for storage as they involve serialized data. Redis reduce serialization overhead as data structures in redis may save any aspect of data
Memcached provides another benefit over readis in terms of scaling. Memcached can be scaled up providing more computational resources. Clustering is a complex but very effective scaling solution.
When Redis is Good To Use
Redis cache is preferred due to its data structures. Redis may help you in gaining power and efficiency.
Redis has more points in favor to be preferred for cache management. Data eviction is a process in which caches delete old data to make space for new data. Memcached data eviction process uses a least recently used data.
AI has also helped in developing algorithms combined with deep learning. Redis uses a very efficient approach to memory management and for data eviction. Redis cache supports active as well as lazy eviction technoceques. In this way, data is evicted only when more space is required.
Redis provides more flexibility with respect to caching objects. Memcached has key names limitations to 250 bytes and supports plain strings only. Redis supports key names and values upto 512MB each as they are considered as binary safe.
Redis supports 5 data structures hence providing a world of possibilities to application developers by intelligent caching and data manipulation.
Data Persistence With Redis:
Redis data structures may help in optimization of several tasks not only during caching but whenever you require data to be persistent and available. For instance, Developers may utilize Redis for storing object fields and values rather than storing objects as serialized strings. Hence they may be managed by using a single key.
Redis hash helps developers to avoid string fetching, deserialization of objects, replacing of entire string in cache. Hence, it will cause lower resource consumption and better performance.
In addition to this, Redis caches offers many datasets like sorted sets, hyperloglogs, bitmaps and lists which could be helpful in implementing complex scenarios.
Redis can be manipulated by the server directly because data stored in it is not opaque. There are 150+ commands available in redis for data processing operations and embedding logic in data stores.
The built in commands and user scripts provide flexibility of tackling data processing tasks. It doesn’t involve data shipment across the network for processing.
Redis offers tunable data persistence features for bootstrapping cache usually carried out after a planned shutdown or unplanned failure.
Usually data in cache is considered as volatile and transient. Persistent data is very valuable in terms of caching scenarios. Cache data is valuable as it is available for loading as restart occurs and it may require shorter cache warmup . Also it reduces the load included in recalculating repopulating cache contents from primary data stores.
Redis in Memory Data Replication:
Redis may replicate data which is being managed. This replication may be carried out for implementing a cache setup which can afford failures and uninterrupted service to the application.
It provides a solution which guarantees cached content and service availability. Redis also provides certain metrics and commands which may help in monitoring and tracking usage as well as unusual behaviour.
Redis provides real time statistics , display of excited commands, listing and details of client connections.
Developers often use redis as a first responder database for analyzing and processing high velocity data and provide feedback to the user as the secondary database maintains record of data. In this way Redis is ideal for analytics use cases.
Both types of cache engines have many common benefits but Redis caches wins more votes in terms of compatibility and flexibility.