I've started a new project using node.js and mongodb and after almost 2 days I gathered about 600k objects in MongoDB. I'm already noticing a huge (negative) impact on the performance and I'm starting to worry if I should move to another DB as long as I can, or if I should stick with Mongo and do some (more) optimizations.

Basically I'm storing coordinates like this:

```
[x1] => 687
[y1] => 167
[x2] => 686
[y2] => 167
[c] => 0
[s] => 0
[m] => 1299430700312
[_id] => MongoId Object (
    [$id] => 4d73bd2c82bb5926780001ec
)

```

Not more... and my queries look like this: 

```
{'$or': [ { x1: {'$gte' : 0, '$lt' : 1000 }, y1: {'$gte' : 0, '$lt' : 1000 } , { x2: {'$gte' : 0, '$lt' : 1000 }, y2: {'$gte' : 0, '$lt' : 1000 } } ] }

```

I've tried setting the index for each of the fields: x1,y1,y1,y1 as well as for: `{x1:1,y1:1},{x2:1,y2:1}`.
Furthermore I've also only fetched the required fields I need... but still, performing a query with a resultset of ~40k rows ends up in a runtime of 2-8secs.
Btw: performing the same query in PHP died with with a Out-of-Memory message (256MB RAM). 

The machine is a Intel(R) Core(TM) i7 CPU 920 @ 2.67GHz with 8GB of RAM, it's not the most dusty one in the rack ;)

I'm really running out of ideas and I see millions and millions of rows coming for the next weeks. As you probably noticed the rows are relatively small.
Would MySQL with partitioning perform better? Any other NoSQL DB? 

And please to trolling about "2-8secs isn't slow" - it's becoming a problem already. When a couple of uncached requests hit the machine at the same time, the load raises up to 4 and less than 10 users accessing it.