Compare similar N-Dimensional vector in a database
What you're looking for is a procedure to do near-neighbor searching in a high dimensional Euclidean space, or do dimensionality reduction prior to doing such a near neighbor search. 

There are two approaches that are likely to help:


Use a native near-neighbor search procedure that works in high dimensions. Locality-sensitive hashing is a popular choice in this regard. 
Apply dimensionality reduction, and then use a technique that works for fewer dimensions. In this case, you should look at the ANN near-neighbor library, and also look into using the Johnson-Lindenstrauss transform for dimensionality reduction (or possibly even PCA to reduce dimensions). 


(warning - self promotion alert: I have a paper that describes different implementations of Johnson-Lindenstrauss and how they compare)