I had a similiar experience myself actually. You should actually check out the R language if youre interested in scientific computing. Speaking of the python communittee i watched many videos from djangocon this year and was really impressed by the openness of the leaders of the project. Also django i think is rally starting to gain more momentum. Alot of very cool things going on with the framework and communitee..

From the article:

"I’ve already used Ruby at work to dramatically speed up some of our vaccine screens—for processing and summarizing data—but I’ve always had to pipe my numbers into R for statistics and graphing. Because unfortunately, despite all the hubbub around Ruby, no one is crunching numbers with it! I’m sick of R, though, and I want a complete solution for my numbers needs."

Postgis is far from perfect and in actuality is more geared towards geographical survey types of applications then location based. They used cassandra at least for some of their architecture which personally i think was the right way to go. The problem is that theres really not enough demand for these types of applications yet plus they really didnt offer a strong enough platform.

I was just looking into the geolocation issue myself recently. Looked at simplegeo but decided against it. The question really is what is your app going to do. The difficulty really with geolocation these days isnt the lack of data points rather its figuring out the needs of your application and whether or not these services will fit into that. In reality even with these services location based apps are still a pain to develop.

Ive been working with python/django for about 6 months now so i wouldnt call myself an expert but i understand where youre coming from and im willing to help you out. How best to contact you?

Thanks, mark@theopenalgorithm.com, send your profile links.

In a basic application yes this is true. But if you have a large cluster and data is spread out it becomes more difficult not to mention time consuming to run that query. With redis and other nosql solutions they are designed with this in mind so they are much faster and easier.

Tumblr is using scala? Any idea for what? I know ideeli was using jruby. Did they start using scala as well?

Tumblr is doing their new backend services in scala, they are starting to ramp up hiring, they want to do a lot of stuff like twitter so your seeing them do a lot of hbase also. Ideeli told me they were considering using it for backend services. Obviously I was interviewing lately so I got to hear all the recent gossip ;)

In my original title i had added for a small applicaiton but then i decided i was curious to see about using for something beyond just something simple. But you are right about the querying. I was thinking of it more in comparison to membase and memcache.

Are there any hidden reasons you could think of not to?

I've read that persistence/virtual memory is quite slow (as of at least a few months ago). If your application can stand losing some of its data every once in a while, redis could be a good option.

As far as I know there have been improvements in the virtual memory field. However it is not recommended to use redis if the data you want to store in it exceeds the amount of ram in your server.

Virtual memory support is being dropped from redis in versions after 2.4, so you should definitely avoid using it.

thanks for keeping me updated about redis :)

I guess what im wondering is more about the scalability of it. I know that Mongodb could essentially be used as the only datastore however it apparently has some issues currently with scalability.

So, your app is unlikely to be as popular as foursquare, for instance, at least right now, and they seem fine and happy with MongoDB. You might recall the issues they had with it a while back, but those have all been fixed as far as I'm aware. 10gen is really quite impressive when it comes to support, etc.

But, the real question is, why do you think a SQL database will not be scalable to begin with? I'm going to say that well over 75% of the top sites, use a SQL database.

Mongo 1.8 fixed a lot of the scalability issues. +1 to Mongo as an alternative to SQL. Redis is great for a simple app but I wouldn't want to scale it to handle everything for a large site.

I didnt know that the issues in Mongo were fixed. I figured they would be eventually though.

This is a good point. My thoughts have been that if the product uses cutting edge technologies people might be more open to doing the work or helping out for a lesser charge. Hence why i use django as well as redis and mongodb and android.