My startup has a fast nearest neighbor engine that allows to have far matches: http://simmachines.com/Products/r01.html
We hope to be the "berkeley DB" of the big data era.
Feedback would be greatly appreciated!
My main piece of feedback is that explicitly comparing your product to a database engine that people love to hate is probably not a great way to market it. Lots of us have horrible memories of badly-corrupted Berkeley DB databases.
To add, these types of algorithms have been around for a couple decades in literature. There are reasons they are not commonly used. The concept is fine n the abstract but an implementation that does not break on real-world data sets is very difficult.
