I came into a company that was attempting to use MongoDB for their soft-real time time-series data (I would consider it between low and medium scale) and it was atrocious, in too many ways.

It doesn't scale without tremendous effort and implicit schemas are a very dangerous thing to introduce into your application, they're insidious, and require enormous diligence in the application to codify the schemas (I would only feel comfortable using a loose document store with something like Haskell in which I can model the schema with strong types).

I've encountered MongoDB in three different companies / products and expended much effort to immediately move away from it in every case. In each case, the solution (which has been different each time) was far more appropriate to what was needed.

There's a sad inclination by developers to pick "one ring to rule them all" tools and MongoDB I believe even sells itself that way. It is not.

What were the more appropriate solutions?

Postgres for structured data, Riak for high-volume and flatter data, and TempoDB for high-volume time-series data.

I've been using mongo on 39M+ records (tracking financial tick data) across 73 assets (collections) and my queries take anywhere between 2-3mins depending on complexity.

You can always run db.currentOp() in the mongo shell to see what process is taking forever as well.

Let me clarify why though, there methods of optimizing a query by adding another field, but since I have to traverse my records with the sort() cursor my queries take that long.

Jesus Christ!

I remember querying databases with 100 tables and millions of records in foxpro a century ago and it took less than a second.

What has happened to the world while I was in cryogenic state? Take me back to the nitrogen pool!

I don't get this. If any relational database choked with that small number of rows, it would be thrown away immediately. That's a couple of orders of magnitude too slow.

I did, for nearly three years. MongoDB was consistently the number one reason for site downtime.

High scale public references and links to their presentations are maintained here: http://www.mongodb.com/mongodb-scale

I think scaling any system takes careful planning.

IMHO, this is an area where MongoDB has improved a lot in the past two years, especially with 3.0, but there is still a lot of work to do.

Yes. When implemented correctly Mongo can scale very well.

i think foursquare is, unless they have migrated off and did not publicized it