Memcached vs Redis

Question

We re using a Ruby web-app with Redis server for caching  Is there a point to test Memcached instead   What will give us better performance  Any pros or cons between Redis and Memcached   Points to consider    Read write speed  Memory usage  Disk I O dumping  Scaling

User · Answer

I got the opportunity to use both memcached and redis together in the caching proxy that i have worked on , let me share you where exactly i have used what and reason behind same....

Redis >

1) Used for indexing the cache content , over the cluster . I have more than billion keys in spread over redis clusters , redis response times is quite less and stable .

2) Basically , its a key/value store , so where ever in you application you have something similar, one can use redis with bothering much.

3) Redis persistency, failover and backup (AOF ) will make your job easier .

Memcache >

1) yes , an optimized memory that can be used as cache . I used it for storing cache content getting accessed very frequently (with 50 hits/second)with size less than 1 MB .

2) I allocated only 2GB out of 16 GB for memcached that too when my single content size was >1MB .

3) As the content grows near the limits , occasionally i have observed higher response times in the stats(not the case with redis) .

If you ask for overall experience Redis is much green as it is easy to configure, much flexible with stable robust features.

Further , there is a benchmarking result available at this link , below are few higlight from same,

Hope this helps!!

User · Answer

One major difference that hasn t been pointed out here is that Memcache has an upper memory limit at all times  while Redis does not by default  but can be configured to   If you would always like to store a key value for certain amount of time  and never evict it because of low memory  you want to go with Redis  Of course  you also risk the issue of running out of memory

User · Answer

We thought of Redis as a load-takeoff for our project at work. We thought that by using a module in nginx called HttpRedis2Module or something similar we would have awesome speed but when testing with AB-test we're proven wrong.

Maybe the module was bad or our layout but it was a very simple task and it was even faster to take data with php and then stuff it into MongoDB. We're using APC as caching-system and with that php and MongoDB. It was much much faster then nginx Redis module.

My tip is to test it yourself, doing it will show you the results for your environment. We decided that using Redis was unnecessary in our project as it would not make any sense.

User · Answer

If you don t mind a crass writing style  Redis vs Memcached on the Systoilet blog is worth a read from a usability standpoint  but be sure to read the back  amp  forth in the comments before drawing any conclusions on performance  there are some methodological problems  single-threaded busy-loop tests   and Redis has made some improvements since the article was written as well    And no benchmark link is complete without confusing things a bit  so also check out some conflicting benchmarks at Dormondo s LiveJournal and the Antirez Weblog    Edit -- as Antirez points out  the Systoilet analysis is rather ill-conceived  Even beyond the single-threading shortfall  much of the performance disparity in those benchmarks can be attributed to the client libraries rather than server throughput  The benchmarks at the Antirez Weblog do indeed present a much more apples-to-apples  with the same mouth  comparison

User · Answer

Memcached is multithreaded and fast   Redis has lots of features and is very fast  but completely limited to one core as it is based on an event loop   We use both  Memcached is used for caching objects  primarily reducing read load on the databases  Redis is used for things like sorted sets which are handy for rolling up time-series data

User · Answer

Memcached will be faster if you are interested in performance, just even because Redis involves networking (TCP calls). Also internally Memcache is faster.

Redis has more features as it was mentioned by other answers.

User · Answer

Redis is better   The Pros of Redis are      It has a lot of data storage options such  as  string    sets   sorted sets    hashes    bitmaps Disk Persistence of records  Stored Procedure  LUA scripting   support Can act as a Message Broker using PUB SUB   Whereas Memcache is an in-memory key value cache type system    No support for various data type storages like lists   sets as in redis    The major con is Memcache has no disk persistence

User · Answer

Test  Run some simple benchmarks  For a long while I considered myself an old school rhino since I used mostly memcached and considered Redis the new kid   With my current company Redis was used as the main cache  When I dug into some performance stats and simply started testing  Redis was  in terms of performance  comparable or minimally slower than MySQL   Memcached  though simplistic  blew Redis out of water totally  It scaled much better    for bigger values  required change in slab size  but worked  for multiple concurrent requests   Also  memcached eviction policy is in my view  much better implemented  resulting in overall more stable average response time while handling more data than the cache can handle   Some benchmarking revealed that Redis  in our case  performs very poorly  This I believe has to do with many variables    type of hardware you run Redis on types of data you store amount of gets and sets how concurrent your app is do you need data structure storage   Personally  I don t share the view Redis authors have on concurrency and multithreading

User · Answer

Memcached is good at being a simple key value store and is good at doing key    STRING  This makes it really good for session storage   Redis is good at doing key    SOME OBJECT   It really depends on what you are going to be putting in there   My understanding is that in terms of performance they are pretty even   Also good luck finding any objective benchmarks  if you do find some kindly send them my way

User · Answer

Use Redis if

You require selectively deleting/expiring items in the cache. (You need this)
You require the ability to query keys of a particular type. eq. 'blog1:posts:*', 'blog2:categories:xyz:posts:*'. oh yeah! this is very important. Use this to invalidate certain types of cached items selectively. You can also use this to invalidate fragment cache, page cache, only AR objects of a given type, etc.
Persistence (You will need this too, unless you are okay with your cache having to warm up after every restart. Very essential for objects that seldom change)

Use memcached if

Memcached gives you headached!
umm... clustering? meh. if you gonna go that far, use Varnish and Redis for caching fragments and AR Objects.

From my experience I've had much better stability with Redis than Memcached

User · Answer

Summary  TL DR  Updated June 3rd  2017 Redis is more powerful  more popular  and better supported than memcached  Memcached can only do a small fraction of the things Redis can do  Redis is better even where their features overlap  For anything new  use Redis  Memcached vs Redis  Direct Comparison Both tools are powerful  fast  in-memory data stores that are useful as a cache  Both can help speed up your application by caching database results  HTML fragments  or anything else that might be expensive to generate  Points to Consider When used for the same thing  here is how they compare using the original question s  quot Points to Consider quot    Read write speed  Both are extremely fast  Benchmarks vary by workload  versions  and many other factors but generally show redis to be as fast or almost as fast as memcached  I recommend redis  but not because memcached is slow  It s not  Memory usage  Redis is better   memcached  You specify the cache size and as you insert items the daemon quickly grows to a little more than this size  There is never really a way to reclaim any of that space  short of restarting memcached  All your keys could be expired  you could flush the database  and it would still use the full chunk of RAM you configured it with  redis  Setting a max size is up to you  Redis will never use more than it has to and will give you back memory it is no longer using  I stored 100 000  2KB strings   200MB  of random sentences into both  Memcached RAM usage grew to  225MB  Redis RAM usage grew to  228MB  After flushing both  redis dropped to  29MB and memcached stayed at  225MB  They are similarly efficient in how they store data  but only one is capable of reclaiming it    Disk I O dumping  A clear win for redis since it does this by default and has very configurable persistence  Memcached has no mechanisms for dumping to disk without 3rd party tools  Scaling  Both give you tons of headroom before you need more than a single instance as a cache  Redis includes tools to help you go beyond that while memcached does not   memcached Memcached is a simple volatile cache server  It allows you to store key value pairs where the value is limited to being a string up to 1MB  It s good at this  but that s all it does  You can access those values by their key at extremely high speed  often saturating available network or even memory bandwidth  When you restart memcached your data is gone  This is fine for a cache  You shouldn t store anything important there  If you need high performance or high availability there are 3rd party tools  products  and services available  redis Redis can do the same jobs as memcached can  and can do them better  Redis can act as a cache as well  It can store key value pairs too  In redis they can even be up to 512MB  You can turn off persistence and it will happily lose your data on restart too  If you want your cache to survive restarts it lets you do that as well  In fact  that s the default  It s super fast too  often limited by network or memory bandwidth  If one instance of redis memcached isn t enough performance for your workload  redis is the clear choice  Redis includes cluster support and comes with high availability tools  redis-sentinel  right  quot in the box quot   Over the past few years redis has also emerged as the clear leader in 3rd party tooling  Companies like Redis Labs  Amazon  and others offer many useful redis tools and services  The ecosystem around redis is much larger  The number of large scale deployments is now likely greater than for memcached  The Redis Superset Redis is more than a cache  It is an in-memory data structure server  Below you will find a quick overview of things Redis can do beyond being a simple key value cache like memcached  Most of redis  features are things memcached cannot do  Documentation Redis is better documented than memcached  While this can be subjective  it seems to be more and more true all the time  redis io is a fantastic easily navigated resource  It lets you try redis in the browser and even gives you live interactive examples with each command in the docs  There are now 2x as many stackoverflow results for redis as memcached  2x as many Google results  More readily accessible examples in more languages  More active development  More active client development  These measurements might not mean much individually  but in combination they paint a clear picture that support and documentation for redis is greater and much more up-to-date  Persistence By default redis persists your data to disk using a mechanism called snapshotting  If you have enough RAM available it s able to write all of your data to disk with almost no performance degradation  It s almost free  In snapshot mode there is a chance that a sudden crash could result in a small amount of lost data  If you absolutely need to make sure no data is ever lost  don t worry  redis has your back there too with AOF  Append Only File  mode  In this persistence mode data can be synced to disk as it is written  This can reduce maximum write throughput to however fast your disk can write  but should still be quite fast  There are many configuration options to fine tune persistence if you need  but the defaults are very sensible  These options make it easy to setup redis as a safe  redundant place to store data  It is a real database  Many Data Types Memcached is limited to strings  but Redis is a data structure server that can serve up many different data types  It also provides the commands you need to make the most of those data types  Strings  commands  Simple text or binary values that can be up to 512MB in size  This is the only data type redis and memcached share  though memcached strings are limited to 1MB  Redis gives you more tools for leveraging this datatype by offering commands for bitwise operations  bit-level manipulation  floating point increment decrement support  range queries  and multi-key operations  Memcached doesn t support any of that  Strings are useful for all sorts of use cases  which is why memcached is fairly useful with this data type alone  Hashes  commands  Hashes are sort of like a key value store within a key value store  They map between string fields and string values  Field- gt value maps using a hash are slightly more space efficient than key- gt value maps using regular strings  Hashes are useful as a namespace  or when you want to logically group many keys  With a hash you can grab all the members efficiently  expire all the members together  delete all the members together  etc  Great for any use case where you have several key value pairs that need to grouped  One example use of a hash is for storing user profiles between applications  A redis hash stored with the user ID as the key will allow you to store as many bits of data about a user as needed while keeping them stored under a single key  The advantage of using a hash instead of serializing the profile into a string is that you can have different applications read write different fields within the user profile without having to worry about one app overriding changes made by others  which can happen if you serialize stale data   Lists  commands  Redis lists are ordered collections of strings  They are optimized for inserting  reading  or removing values from the top or bottom  aka  left or right  of the list  Redis provides many commands for leveraging lists  including commands to push pop items  push pop between lists  truncate lists  perform range queries  etc  Lists make great durable  atomic  queues  These work great for job queues  logs  buffers  and many other use cases  Sets  commands  Sets are unordered collections of unique values  They are optimized to let you quickly check if a value is in the set  quickly add remove values  and to measure overlap with other sets  These are great for things like access control lists  unique visitor trackers  and many other things  Most programming languages have something similar  usually called a Set   This is like that  only distributed  Redis provides several commands to manage sets  Obvious ones like adding  removing  and checking the set are present  So are less obvious commands like popping reading a random item and commands for performing unions and intersections with other sets  Sorted Sets  commands  Sorted Sets are also collections of unique values  These ones  as the name implies  are ordered  They are ordered by a score  then lexicographically  This data type is optimized for quick lookups by score  Getting the highest  lowest  or any range of values in between is extremely fast  If you add users to a sorted set along with their high score  you have yourself a perfect leader-board  As new high scores come in  just add them to the set again with their high score and it will re-order your leader-board  Also great for keeping track of the last time users visited and who is active in your application  Storing values with the same score causes them to be ordered lexicographically  think alphabetically   This can be useful for things like auto-complete features  Many of the sorted set commands are similar to commands for sets  sometimes with an additional score parameter  Also included are commands for managing scores and querying by score  Geo Redis has several commands for storing  retrieving  and measuring geographic data  This includes radius queries and measuring distances between points  Technically geographic data in redis is stored within sorted sets  so this isn t a truly separate data type  It is more of an extension on top of sorted sets  Bitmap and HyperLogLog Like geo  these aren t completely separate data types  These are commands that allow you to treat string data as if it s either a bitmap or a hyperloglog  Bitmaps are what the bit-level operators I referenced under Strings are for  This data type was the basic building block for reddit s recent collaborative art project  r Place  HyperLogLog allows you to use a constant extremely small amount of space to count almost unlimited unique values with shocking accuracy  Using only  16KB you could efficiently count the number of unique visitors to your site  even if that number is in the millions  Transactions and Atomicity Commands in redis are atomic  meaning you can be sure that as soon as you write a value to redis that value is visible to all clients connected to redis  There is no wait for that value to propagate  Technically memcached is atomic as well  but with redis adding all this functionality beyond memcached it is worth noting and somewhat impressive that all these additional data types and features are also atomic  While not quite the same as transactions in relational databases  redis also has transactions that use  quot optimistic locking quot   WATCH MULTI EXEC   Pipelining Redis provides a feature called  pipelining   If you have many redis commands you want to execute you can use pipelining to send them to redis all-at-once instead of one-at-a-time  Normally when you execute a command to either redis or memcached  each command is a separate request response cycle  With pipelining  redis can buffer several commands and execute them all at once  responding with all of the responses to all of your commands in a single reply  This can allow you to achieve even greater throughput on bulk importing or other actions that involve lots of commands  Pub Sub Redis has commands dedicated to pub sub functionality  allowing redis to act as a high speed message broadcaster  This allows a single client to publish messages to many other clients connected to a channel  Redis does pub sub as well as almost any tool  Dedicated message brokers like RabbitMQ may have advantages in certain areas  but the fact that the same server can also give you persistent durable queues and other data structures your pub sub workloads likely need  Redis will often prove to be the best and most simple tool for the job  Lua Scripting You can kind of think of lua scripts like redis s own SQL or stored procedures  It s both more and less than that  but the analogy mostly works  Maybe you have complex calculations you want redis to perform  Maybe you can t afford to have your transactions roll back and need guarantees every step of a complex process will happen atomically  These problems and many more can be solved with lua scripting  The entire script is executed atomically  so if you can fit your logic into a lua script you can often avoid messing with optimistic locking transactions  Scaling As mentioned above  redis includes built in support for clustering and is bundled with its own high availability tool called redis-sentinel  Conclusion Without hesitation I would recommend redis over memcached for any new projects  or existing projects that don t already use memcached  The above may sound like I don t like memcached  On the contrary  it is a powerful  simple  stable  mature  and hardened tool  There are even some use cases where it s a little faster than redis  I love memcached  I just don t think it makes much sense for future development  Redis does everything memcached does  often better  Any performance advantage for memcached is minor and workload specific  There are also workloads for which redis will be faster  and many more workloads that redis can do which memcached simply can t  The tiny performance differences seem minor in the face of the giant gulf in functionality and the fact that both tools are so fast and efficient they may very well be the last piece of your infrastructure you ll ever have to worry about scaling  There is only one scenario where memcached makes more sense  where memcached is already in use as a cache  If you are already caching with memcached then keep using it  if it meets your needs  It is likely not worth the effort to move to redis and if you are going to use redis just for caching it may not offer enough benefit to be worth your time  If memcached isn t meeting your needs  then you should probably move to redis  This is true whether you need to scale beyond memcached or you need additional functionality

User · Answer

The biggest remaining reason is specialization.

Redis can do a lot of different things and one side effect of that is developers may start using a lot of those different feature sets on the same instance. If you're using the LRU feature of Redis for a cache along side hard data storage that is NOT LRU it's entirely possible to run out of memory.

If you're going to setup a dedicated Redis instance to be used ONLY as an LRU instance to avoid that particular scenario then there's not really any compelling reason to use Redis over Memcached.

If you need a reliable "never goes down" LRU cache...Memcached will fit the bill since it's impossible for it to run out of memory by design and the specialize functionality prevents developers from trying to make it so something that could endanger that. Simple separation of concerns.

User · Answer

A very simple test to set and get 100k unique keys and values against redis-2.2.2 and memcached. Both are running on linux VM(CentOS) and my client code(pasted below) runs on windows desktop.

Redis

Time taken to store 100000 values is = 18954ms
Time taken to load 100000 values is = 18328ms

Memcached

Time taken to store 100000 values is = 797ms
Time taken to retrieve 100000 values is = 38984ms

Jedis jed = new Jedis("localhost", 6379);
int count = 100000;
long startTime = System.currentTimeMillis();
for (int i=0; i<count; i++) {
  jed.set("u112-"+i, "v51"+i);
}
long endTime = System.currentTimeMillis();
System.out.println("Time taken to store "+ count + " values is ="+(endTime-startTime)+"ms");

startTime = System.currentTimeMillis();
for (int i=0; i<count; i++) {
  client.get("u112-"+i);
}
endTime = System.currentTimeMillis();
System.out.println("Time taken to retrieve "+ count + " values is ="+(endTime-startTime)+"ms");

User · Answer

It would not be wrong  if we say that redis is combination of  cache   data structure  while memcached is just a cache

User · Answer

Another bonus is that it can be very clear how memcache is going to behave in a caching scenario, while redis is generally used as a persistent datastore, though it can be configured to behave just like memcached aka evicting Least Recently Used items when it reaches max capacity.

Some apps I've worked on use both just to make it clear how we intend the data to behave - stuff in memcache, we write code to handle the cases where it isn't there - stuff in redis, we rely on it being there.

Other than that Redis is generally regarded as superior for most use cases being more feature-rich and thus flexible.

User · Answer

This is too long to be posted as a comment to already accepted answer  so I put it as a separate answer  One thing also to consider is whether you expect to have a hard upper memory limit on your cache instance   Since redis is an nosql database with tons of features and caching is only one option it can be used for  it allocates memory as it needs it      the more objects you put in it  the more memory it uses  The maxmemory option does not strictly enforces upper memory limit usage  As you work with cache  keys are evicted and expired  chances are your keys are not all the same size  so internal memory fragmentation occurs   By default redis uses jemalloc memory allocator  which tries its best to be both memory-compact and fast  but it is a general purpose memory allocator and it cannot keep up with lots of allocations and object purging occuring at a high rate  Because of this  on some load patterns redis process can apparently leak memory because of internal fragmentation  For example  if you have a server with 7 Gb RAM and you want to use redis as non-persistent LRU cache  you may find that redis process with maxmemory set to 5Gb over time would use more and more memory  eventually hitting total RAM limit until out-of-memory killer interferes   memcached is a better fit to scenario described above  as it manages its memory in a completely different way  memcached allocates one big chunk of memory      everything it will ever need      and then manages this memory by itself  using its own implemented slab allocator  Moreover  memcached tries hard to keep internal fragmentation low  as it actually uses per-slab LRU algorithm  when LRU evictions are done with object size considered   With that said  memcached still has a strong position in environments  where memory usage has to be enforced and or be predictable  We ve tried to use latest stable redis  2 8 19  as a drop-in non-persistent LRU-based memcached replacement in workload of 10-15k op s  and it leaked memory A LOT  the same workload was crashing Amazon s ElastiCache redis instances in a day or so because of the same reasons

User · Answer

Here is the really great article differences provided by Amazon  Redis is a clear winner comparing with memcached    Only one plus point for Memcached It is multithreaded and fast  Redis has lots of great features and is very fast  but limited to one core   Great points about Redis  which are not supported in Memcached   Snapshots - User can take a snapshot of Redis cache and persist on    secondary storage any point of time     Inbuilt support for many data structures like Set  Map  SortedSet  List  BitMaps etc  Support for Lua scripting in redis

[caching] Memcached vs. Redis?

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