Using MongoDB on Django for real-time search?

I'm working on a project that is quite search-oriented. Basically, users will add content to the site, and this content should be immediately available in the search results. The project is still in development.

Up until now, I've been using Haystack with Xapian. One thing I'm worried about is the performance of the website once a lot of content is available. Indexing will have to occur very f开发者_JS百科requently if I want to emulate real-time search.

I was reading up on MongoDB recently. I haven't found a satisfying answer to my question, but I have the feeling that MongoDB might be of help for the real-time search indexing issue I expect to encounter. Is this correct? In other words, would the search functionality available in MongoDB be more suited for a real-time search function?

The content that will be available on the site is large unstructured text (including HTML) and related data (prices, tags, datetime info).

Thanks in advance,

Laundro

I don't know much about MongoDB, but I'm using with great success Sphinx Search - simple, powerful and very fast tool for full text indexing&search. It also provides Python wrapper out-of-the-box.

It would be easier to pick it up if Haystack provided bindings for it, unfortunately Sphinx bindings are still on a wish list. Nevertheless, setting Spinx up is so quick (I did it in a few hours, for existing in-production Django-based CRM), that maybe you can give it a try before switching to a more generic solution.

MongoDB is not really a "dedicated full text search engine". Based on their full text search docs you can only create a array of tags that duplicates the string data or other columns, which with many elements (hundreds or thousands) can make inserts very expensive.

Agree with Tomasz, Sphinx Search can be used for what you need. Real time indexes if you want it to be really real time or Delta indexes if several seconds of delay are acceptable.