When to Redis When to MongoDB

Question

What I want is not a comparison between Redis and MongoDB  I know they are different  the performance and the API is totally different   Redis is very fast  but the API is very  atomic   MongoDB will eat more resources  but the API is very very easy to use  and I am very happy with it   They re both awesome  and I want to use Redis in deployment as much as I can  but it is hard to code  I want to use MongoDB in development as much as I can  but it needs an expensive machine   So what do you think about the use of both of them  When to pick Redis  When to pick MongoDB

User · Answer

Difficult question to answer - as with most technology solutions, it really depends on your situation and since you have not described the problem you are trying to solve, how can anyone propose a solution?

You need to test them both to see which of them satisfied your needs.

With that said, MongoDB does not require any expensive hardware. Like any other database solution, it will work better with more CPU and memory but is certainly not a requirement - especially for early development purposes.

User · Answer

Maybe this resource is useful helping decide between both  It also discusses several other NoSQL databases  and offers a short list of characteristics  along with a  what I would use it for  explanation for each of them   http   kkovacs eu cassandra-vs-mongodb-vs-couchdb-vs-redis

User · Answer

If your project budged allows you to have enough RAM memory on your environment - answer is Redis  Especially taking in account new Redis 3 2 with cluster functionality

User · Answer

All of the answers  at the time of this writing  assume each of Redis  MongoDB  and perhaps an SQL-based relational database are essentially the same tool    store data    They don t consider data models at all   MongoDB   Complex Data  MongoDB is a document store   To compare with an SQL-driven relational database   relational databases simplify to indexed CSV files  each file being a table  document stores simplify to indexed JSON files  each file being a document  with multiple files grouped together   JSON files are similar in structure to XML and YAML files  and to dictionaries as in Python  so think of your data in that sort of hierarchy   When indexing  the structure is the key   A document contains named keys  which contain either further documents  arrays  or scalar values   Consider the below document        id   0x194f38dc491a    Name    John Smith     PhoneNumber      Home   555 999-1234       Work   555 999-9876       Mobile   555 634-5789    Accounts      -  379-1111      -  379-2574      -  414-6731      The above document has a key  PhoneNumber Mobile  which has value 555 634-5789   You can search through a collection of documents where the key  PhoneNumber Mobile  has some value  they re indexed   It also has an array of Accounts which hold multiple indexes   It is possible to query for a document where Accounts contains exactly some subset of values  all of some subset of values  or any of some subset of values   That means you can search for Accounts     379-1111    379-2574   and not find the above  you can search for Accounts includes   379-1111   and find the above document  and you can search for Accounts includes any of   974-3785   414-6731   and find the above and whatever document includes account  974-3785   if any   Documents go as deep as you want   PhoneNumber Mobile could hold an array  or even a sub-document  PhoneNumber Mobile Work and PhoneNumber Mobile Personal    If your data is highly structured  documents are a large step up from relational databases   If your data is mostly flat  relational  and rigidly structured  you re better off with a relational database   Again  the big sign is whether your data models best to a collection of interrelated CSV files or a collection of XML JSON YAML files   For most projects  you ll have to compromise  accepting a minor work-around in some small areas where either SQL or Document Stores don t fit  for some large  complex projects storing a broad spread of data  many columns  rows are irrelevant   it will make sense to store some data in one model and other data in another model   Facebook uses both SQL and a graph database  where data is put into nodes  and nodes are connected to other nodes   Craigslist used to use MySQL and MongoDB  but had been looking into moving entirely onto MongoDB   These are places where the span and relationship of the data faces significant handicaps if put under one model   Redis   Key-Value  Redis is  most basically  a key-value store   Redis lets you give it a key and look up a single value   Redis itself can store strings  lists  hashes  and a few other things  however  it only looks up by name   Cache invalidation is one of computer science s hard problems  the other is naming things   That means you ll use Redis when you want to avoid hundreds of excess look-ups to a back-end  but you ll have to figure out when you need a new look-up   The most obvious case of invalidation is update on write   if you read user Simon lingots   NOTFOUND  you might SELECT Lingots FROM Store s INNER JOIN UserProfile u ON s UserID   u UserID WHERE u Username   Simon and store the result  100  as SET user Simon lingots   100   Then when you award Simon 5 lingots  you read user Simon lingots   100  SET user Simon lingots   105  and UPDATE Store s INNER JOIN UserProfile u ON s UserID   u UserID SET s Lingots   105 WHERE u Username   Simon   Now you have 105 in your database and in Redis  and can get user Simon lingots without querying the database   The second case is updating dependent information   Let s say you generate chunks of a page and cache their output   The header shows the player s experience  level  and amount of money  the player s Profile page has a block that shows their statistics  and so forth   The player gains some experience   Well  now you have several templates Header Simon  templates StatsBox Simon  templates GrowthGraph Simon  and so forth fields where you ve cached the output of a half-dozen database queries run through a template engine   Normally  when you display these pages  you say    t   GetStringFromRedis  templates StatsBox      playerName   if   t    null       t   BuildTemplate  StatsBox tmpl                        GetStatsFromDatabase  playerName      SetStringInRedis  Templates StatsBox      playerName   t     print  t    Because you just updated the results of GetStatsFromDatabase  Simon    you have to drop templates   Simon out of your key-value cache   When you try to render any of these templates  your application will churn away fetching data from your database  PostgreSQL  MongoDB  and inserting it into your template  then it will store the result in Redis and  hopefully  not bother making database queries and rendering templates the next time it displays that block of output   Redis also lets you do publisher-subscribe message queues and such   That s another topic entirely   Point here is Redis is a key-value cache  which differs from a relational database or a document store   Conclusion  Pick your tools based on your needs   The largest need is usually data model  as that determines how complex and error-prone your code is   Specialized applications will lean on performance  places where you write everything in a mixture of C and Assembly  most applications will just handle the generalized case and use a caching system such as Redis or Memcached  which is a lot faster than either a high-performance SQL database or a document store

User · Answer

And you should use neither if you have plenty of RAM  Redis and MongoDB come to the price of a general purpose tool  This introduce a lot of overhead   There was the saying that Redis is 10 times faster than Mongo  That might not be that true anymore  MongoDB  if i remember correctly  claimed to beat memcache for storing and caching documents as long as the memory configurations are the same   Anyhow  Redis good  MongoDB is good  If you care about substructures and need aggregation go for MongoDB  If storing keys and values is your main concern its all about Redis   or any other key value store

User · Answer

I just noticed that this question is quite old  Nevertheless  I consider the following aspects to be worth adding    Use MongoDB if you don t know yet how you re going to query your data   MongoDB is suited for Hackathons  startups or every time you don t know how you ll query the data you inserted  MongoDB does not make any assumptions on your underlying schema  While MongoDB is schemaless and non-relational  this does not mean that there is no schema at all  It simply means that your schema needs to be defined in your app  e g  using Mongoose   Besides that  MongoDB is great for prototyping or trying things out  Its performance is not that great and can t be compared to Redis  Use Redis in order to speed up your existing application   Redis can be easily integrated as a LRU cache  It is very uncommon to use Redis as a standalone database system  some people prefer referring to it as a  key-value -store   Websites like Craigslist use Redis next to their primary database  Antirez  developer of Redis  demonstrated using Lamernews that it is indeed possible to use Redis as a stand alone database system  Redis does not make any assumptions based on your data   Redis provides a bunch of useful data structures  e g  Sets  Hashes  Lists   but you have to explicitly define how you want to store you data  To put it in a nutshell  Redis and MongoDB can be used in order to achieve similar things  Redis is simply faster  but not suited for prototyping  That s one use case where you would typically prefer MongoDB  Besides that  Redis is really flexible  The underlying data structures it provides are the building blocks of high-performance DB systems    When to use Redis    Caching  Caching using MongoDB simply doesn t make a lot of sense  It would be too slow  If you have enough time to think about your DB design   You can t simply throw in your documents into Redis  You have to think of the way you in which you want to store and organize your data  One example are hashes in Redis  They are quite different from  traditional   nested objects  which means you ll have to rethink the way you store nested documents  One solution would be to store a reference inside the hash to another hash  something like key   id of second hash    Another idea would be to store it as JSON  which seems counter-intuitive to most people with a  SQL-background  If you need really high performance   Beating the performance Redis provides is nearly impossible  Imagine you database being as fast as your cache  That s what it feels like using Redis as a real database  If you don t care that much about scaling   Scaling Redis is not as hard as it used to be  For instance  you could use a kind of proxy server in order to distribute the data among multiple Redis instances  Master-slave replication is not that complicated  but distributing you keys among multiple Redis-instances needs to be done on the application site  e g  using a hash-function  Modulo etc    Scaling MongoDB by comparison is much simpler    When to use MongoDB   Prototyping  Startups  Hackathons  MongoDB is perfectly suited for rapid prototyping  Nevertheless  performance isn t that good  Also keep in mind that you ll most likely have to define some sort of schema in your application  When you need to change your schema quickly   Because there is no schema  Altering tables in traditional  relational DBMS is painfully expensive and slow  MongoDB solves this problem by not making a lot of assumptions on your underlying data  Nevertheless  it tries to optimize as far as possible without requiring you to define a schema    TL DR - Use Redis if performance is important and you are willing to spend time optimizing and organizing your data  - Use MongoDB if you need to build a prototype without worrying too much about your DB   Further reading    Interesting aspects to consider when using Redis as a primary data store

User · Answer

Redis and MongoDB are both non-relational databases but they re of different categories   Redis is a Key Value database  and it s using In-memory storage which makes it super fast  It s a good candidate for caching stuff and temporary data storage in memory  and as the most of cloud platforms  such as Azure AWS  support it  it s memory usage is scalable But if you re gonna use it on your machines with limited resources  consider it s memory usage    MongoDB on the other hand  is a document database  It s a good option for keeping large texts  images  videos  etc and almost anything you do with databases except transactions For example if you wanna develop a blog or social network  MongoDB is a proper choice  It s scalable with scale-out strategy  It uses disk as storage media  so data would be persisted

User · Answer

Redis is an in memory data store  that can persist it s state to disk  to enable recovery after restart   However  being an in-memory data store means the size of the data store  on a single node  cannot exceed the total memory space on the system  physical RAM   swap space   In reality  it will be much less that this  as Redis is sharing that space with many other processes on the system  and if it exhausts the system memory space it will likely be killed off by the operating system    Mongo is a disk based data store  that is most efficient when it s working set fits within physical RAM  like all software   Being a disk based data means there are no intrinsic limits on the size of a Mongo database  however configuration options  available disk space  and other concerns may mean that databases sizes over a certain limit may become impractical or inefficient   Both Redis and Mongo can be clustered for high availability  backup and to increase the overall size of the datastore

User · Answer

Redis  Let   s say you   ve written a site in php  for whatever reason  it becomes popular and it   s ahead of its time or has porno on it  You realize this php is so freaking slow   I   m gonna lose my fans because they simply won   t wait 10 seconds for a page   You have a sudden realization that a web page has a constant url  it never changes  whoa   a primary key if you will  and then you recall that memory is fast while disk is slow and php is even slower     Then you fashion a storage mechanism using memory and this URL that you call a  key  while the webpage content you decide to call the  value   That   s all you have - key and content  You call it  meme cache   You like Richard Dawkins because he s awesome  You cache your html like squirrels cache their nuts  You don   t need to rewrite your crap php code  You are happy  Then you see that others have done it -- but you choose Redis because the other one has confusing images of cats  some with fangs    Mongo  You   ve written a site  Heck you   ve written many  and in any language  You realize that much of your time is spent writing those stinking SQL clauses  You   re not a dba  yet there you are  writing stupid sql statements    not just one but freaking everywhere   select this  select that   But in particular you remember the irritating WHERE clause  Where lastname equals  thornton  and movie equals  bad santa    Urgh  You think   why don   t those dbas just do their job and give me some stored procedures   Then you forget some minor field like middlename and then you have to drop the table  export all 10G of big data and create another with this new field  and import the data -- and that goes on 10 times during the next 14 days as you keep on remembering crap like salutation  title  plus adding a foreign key with addresses  Then you figure that lastname should be lastName  Almost one change a day  Then you say darnit  I have to get on and write a web site system  never mind this data model bs  So you google   I hate writing SQL  please no SQL  make it stop  but up pops  nosql  and then you read some stuff and it says it just dumps data without any schema  You remember last week s fiasco dropping more tables and smile  Then you choose mongo because some big guys like  airbud  the apt rental site uses it  Sweet  No more data model changes because you have a model you just keep on changing

User · Answer

I would say  it depends on kind of dev team you are and your application needs   For example  if you require a lot of querying  that mostly means it would be more work for your developers to use Redis  where your data might be stored in variety of specialized data structures  customized for each type of object for efficiency  In MongoDB the same queries might be easier because the structure is more consistent across your data  On the other hand  in Redis  sheer speed of the response to those queries is the payoff for the extra work of dealing with the variety of structures your data might be stored with    MongoDB offers simplicity  much shorter learning curve for developers with traditional DB and SQL experience  However  Redis s non-traditional approach requires more effort to learn  but greater flexibility   Eg  A cache layer can probably be better implemented in Redis  For more schema-able data  MongoDB is better    Note  both MongoDB and Redis are technically schemaless   If you ask me  my personal choice is Redis for most requirements   Lastly  I hope by now you have seen http   antirez com post MongoDB-and-Redis html

[architecture] When to Redis? When to MongoDB?

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