When to Redis? When to MongoDB? [closed]

Question

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

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

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.

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

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.

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.