Full text search options for MongoDB setup
There are some search capabilities in MongoDB but it is not as feature-rich as search engines.
http://www.mongodb.org/display/DOCS/Full+Text+Search+in+Mongo
We use Mongo with Solr to make content searchable. We prefer Solr because
- It is easy to configure and customize
- It has large community (This is really helpful if you are working with opensource tools)
Since we didn't work with ES i could not say much about it. You can found some discussions about Solr vs ES on the links below.
I have a professional experience with both Solr/MySQL and ElasticSearch/MongoDB.
If you are going to query a lot your search engine, you already shard your MongoDB (I mean, if you want to shard too your search engine): you should use ElasticSearch, unless what you want to do can't be done with ElasticSearch. And you should use it even if you are not going to shard.
ElasticSearch is a new project on top of Lucene that brings the sharding mechanism, from someone who is used to distributed environments and search (Shay Bannon made Compass and worked for Gigaspaces, the datagrid editor).
ElasticSearch is as easy as MongoDB to shard, I think it is even simpler and the default works great for most cases.
I don't like Solr so much.
- The query langage is not structured at all (but it's the case of plugins and Lucene, and I think you can use this unstructured query langage with ES too)
- I don't think there is a proper Solr client. Solr java client sucks, and I hearh PHP guys also complaining, while ElasticSearch Java client is very nice, much more typesafe and offers async support (nice if you use Netty for exemple). With Solr, you will do a LOT of string concatenation.
- Less easy to scale
- Not so new project, I felt the technical dept it has. ElasticSearch is born from Compass, so I guess all the technical dept has been dropped to have a fresh new approach.
Concerning data importing, I have experience with both Solr DataImportHandler and ElasticSearch rivers (CouchDB and MongoDB). What I can tell you is:
- Solr permits to do more things, but in a very unstructured XML way, and the documentation doesn't help you so much to understand what is really happing once you are out of the hello world and try to use some advanced features.
- ElasticSearch approach is more simple and also limited but has out of the box support for some technologies while DataImportHandler seems more complex-SQL friendly
- With my Solr project I had to use manual indexation for some documents, but it was mostly because of the impossibility to denormalize the needed data into a document (the Solr project uses MySQL).
There is also a new MongoDB connector for both Solr and ElasticSearch which I need to test asap :)http://blog.mongodb.org/post/29127828146/introducing-mongo-connector
So in the end, I'll definitly choose ElasticSearch, because:
- It now has a great community
- Many people I know with experience with Solr like ElasticSearch
- The client side is safer and structured, and provides async with Java Futures
- Both can probably import data from MongoDB easily with the new connector
- As far as I know, it permits to do almost everything Solr does (in my experience but I'm not a search engine expert)
- It adds sharding out of the box
- It adds percolation which can help to built realtime scalable applications (but you'll probably need an additional messaging technology)
- The source code I read has nearly no technical dept compared to Solr (at least on the client side), and it seems easy to create plugins.
In terms of MongoDB natively, no it doesn't have full text search support. You can see that it is a popular feature request:
https://jira.mongodb.org/browse/SERVER-380
From what I know of the ES river plugin for MongoDB, it tails the oplog for it's functionality. Since a sharded setup would have multiple oplogs and there would be no way to easily alter that code to connect via a mongos.
Similarly for Solr, the examples I have seen usually involve similar behavior to the ES plugin. Some more solid info here:
http://blog.knuthaugen.no/2010/04/cooking-with-mongodb-and-solr.html
I have not got any experience using one but others have made comparisons before, take a look here:
ElasticSearch, Sphinx, Lucene, Solr, Xapian. Which fits for which usage?