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.

我想说的是，这取决于你所在的开发团队以及你的应用程序需求。

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为具有传统DB和SQL经验的开发人员提供了简单、更短的学习曲线。然而，Redis的非传统方法需要更多的努力去学习，但更大的灵活性。

如。缓存层可能在Redis中可以更好地实现。对于更多可模式的数据，MongoDB更好。[注:MongoDB和Redis在技术上都是无模式的]

如果你问我，我个人对大多数需求的选择是Redis。

最后，我希望你现在已经看到http://antirez.com/post/MongoDB-and-Redis.html

很难回答的问题——和大多数技术解决方案一样，这真的取决于你的情况，因为你没有描述你正在试图解决的问题，谁能提出解决方案呢?

您需要对它们进行测试，以确定其中哪一个满足您的需求。

也就是说，MongoDB不需要任何昂贵的硬件。与任何其他数据库解决方案一样，它需要更多的CPU和内存才能更好地工作，但肯定不是必需的——特别是对于早期开发目的。

也许这个资源可以帮助你在两者之间做出选择。 它还讨论了其他几个NoSQL数据库，并提供了一个简短的特征列表，以及对每个数据库的“我将使用它做什么”的解释。

http://kkovacs.eu/cassandra-vs-mongodb-vs-couchdb-vs-redis

我只是注意到这个问题已经很老了。不过，我认为以下方面值得补充:

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.

什么时候使用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.

何时使用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.

博士TL; -如果性能是重要的，你愿意花时间优化和组织你的数据使用Redis。 -使用MongoDB，如果你需要建立一个原型，而不用担心你的DB太多。

进一步阅读:

当使用Redis作为主要数据存储时，需要考虑一些有趣的方面

如果你的项目预算允许你有足够的RAM内存在你的环境-答案是Redis。尤其是考虑到新的Redis 3.2的集群功能。