Which NoSQL database for extremely high volumes of data_问答_开发者

I'm looking at NoSQL for extremely high volumes of data. We're storing cached versions of web page text in MySQL at the moment, but it seems like the database will get huge very quickly.

My requirements are:

Durability, must not lose data on flushes/writes

开发者_JS百科

Very fast read, reasonably fast write
Fully consistent replication
Preferably, in-memory plus an eventual disk write

I'm looking at: MongoDB, Redis, Raik, and Cassandra right now.

Which best fits my requirements?

I have experience with Redis and MongoDB, but would not recommend either for your use case. Redis is awesome in every regard, but since it's RAM-only and has no clustering features (yet, they are in development), it doesn't scale very well. MongoDB I wouldn't ever use again for anything that needs anything but a small replica set.

Basically, MongoDB is immature and completely unsuitable for any kind of high volume, high performance requirements. It has a global write lock which is held during disk flushes, which means that performance can vary wildly depending on what you do. In practice it makes updates that grow documents impossible, and you need to be very careful with deletes, too. Speaking of deletes, they fragment the database severely, so if you do a lot of deletes your performance is going to suffer.

Sharding in 1.8.0 through 1.8.1 was a disaster. There were complete show stopper bugs that should never have made it into a stable release. Configuration wasn't flushed properly and it was very easy to get your database into a bad state so that chunks never moved off of the primary shard. 1.8.2 solves most of them and seems more stable, but I don't trust the sharding implementation one bit. Add to this that sharding is hard even when everything works, it's not always easy to select a natural shard key, and if you don't sharding will cause you much grief.

MongoDB is really easy to work with and the feature set is really nice. The documentation, the drivers and the community are all great. MongoDB works super as a replacement for MySQL, but don't use it for anything that needs to scale out.

We're currently looking at moving to Cassandra. I find the dynamo model (e.g. no master nodes; write and read anywhere; simply add nodes to grow the cluster) compelling and the features are more or less right for us. The data model is schema less just like MongoDB, although a little more limited (you can choose between one or two level hashes, basically). I'm sure the community is good once you get into it, but so far I find it hard to find good information on how to solve common problems, and the documentation is lacking. Most of the information you find on blogs is a year old, and a lot of things have happened since then (0.7 and 0.8 seem to be really significant updates both, but most things you find are about 0.6). The drivers are also not very mature or well documented, from what I've seen so far, and everyone seems to be squabbling about whether Thrift, Avro or CQL is what should be used (and that has changed from 0.6 to 0.7 to 0.8).

Riak is interesting, for the same reasons as Cassandra, but for us a pure key-value-store is not enough, we need to be able to update without first doing a read. With Riak this isn't possible since the values are just blobs. This sounds like it wouldn't be an issue for you though.

HBase is another contender. It seems like a pain to set up and run because of the many different pieces, ZooKeeper, HDFS, etc. But the data model is similar to Cassandra (columnar, i.e. one level hashes), which works well for us, but may not be important for you. It seems tried and true, but as with MongoDB you have to watch out for sharding issues, you must put some thought into your keys or you get into trouble.

There is also CouchDB, Project Voldemort and countless other possible choices. I think that if you are serious about "extremely high volumes of data" then it's between Cassandra, Riak and HBase. Strike Riak if pure key-value-storage isn't enough. Depending on what you mean by "fully consistent replication" then Cassandra and Riak are out, because there is a possibility (not necessarily big, and tunable) of reading a stale value.

In the end you obviously have to try it out on your particular use case, so all you really should take home from this answer is: don't bother with MongoDB.

Store the cached versions in MemCache instead of MySQL. It will eliminate most writes. Writing to MySQL is bad, because it kills the query cache. When you cache the pages in MemCache, you will have far less writes to the database, and you'll have less reading pressure too. You can cache the result of complex queries, or cache entire pages as you like.

Maybe it won't be as fast as Cassandra, but it will give you an enormous boost compared to your current situation with only MySQL. And you won't have to rewrite your entire application.

memcachedb - memcached protocol, BDB storage, replication etc
Handlersocket - MySql InnoDB plugin.
Oracle memcached InnoDB plugin

RavenDB can store up to 16TB of data per node, and you can have several nodes per machine acting as one database using its built-in sharding support. Thats as huge as it gets.

Durability, fastness, replication is all there, and running in memory is supported too (but not recommended if you want to scale to 16TB per node).

For extremely high volume data, it's clear that Cassandra and hadoop/hbase are far superior than all others for this task. Cassandra proved itself on large clusters like 400 nodes. rdms dbs cannot scale easily, also mongo has some problems when node counts start to increase http://www.nosqlbenchmarking.com/2011/05/paper-on-elasticity-and-scalability-for-acm-socc-2011/

Serdar