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Comment by srjk | Hacker News Reader

On that note, would you mind talking about what you use to store the data, efficiently query it etc?

I am in the nascent phases of developing a location based app, but have gotten stuck in trying to figure out a good way to store the data. Currently cassandra is the top contender.

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Check out this code for searching locally with mongo. It doesn't get simpler. Straight from geosay.com

class GeosayController < ApplicationController

  def api

    expires_in 1.minutes, :public => true

    results = Tweet.near(params[:lat].to_f,params[:lon].to_f)

    render :json => results
  end

end

....

class Tweet

  include MongoMapper::Document

  def self.near(lat, lon)

    self.all( :latlong  => {'$near'  => [lat, lon]}, :limit => 30) 

  end

end

We chose mongodb after reading this page http://www.mongodb.org/display/DOCS/Geospatial+Indexing

Before then we were looking at Postgres for its geo stuff and things like cassandra also.

as someone building a location based service, why not just store the lat/long in a table column and query for < >? Is it that much more efficient to use a specialized product?

Our understanding is mongodb should scale to tens of millions of rows better than a SQL database (which would be a nice problem to have)

Once we made the decision to use mongodb, it made sense to use the built in near functionality, rather than roll it ourselves.

Indeed. I am using Django to build my app and a mysql db with 2 float fields for lat/long. GeoDjango and GIS extensions for mysql seemed like over kill, plus I don't really know what I am doing but it seems to work. Django doesn't have very good support for mongo. Well, the django orm.

To be honest I can see absolutely no reason why you can't use floats as you describe and < , >. Depending on what you are doing it may be a little tricky due to lat/longs being angular values, but over small distances I think this can be largely ignored. (In geosay we have some front end code that sorts out the niceties of the angular stuff)

We use mongodb as the backend datastore. It has built in location searching which so far has worked really well.

thanks for both your replies.

I have used (and liked) mongodb in the past. Horizontal scalability is important and mongo doesn't have a stable release with sharding. Also, this page http://www.mongodb.org/display/DOCS/Sharding+Upgrading+from+... seems empty.

But, the ease of use is really tempting :)

According to http://www.mongodb.org/display/DOCS/Sharding production ready sharding should be available this month.

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