This quick-and-dirty approach may save you some grief: Divide the surface of the earth into 1 degree boxes. You will then have a 180x360 element array and you will only need to search a small number of boxes, including the box containing the new point and all the boxes immediately around it for which one of the corners is within the user-specified distance. You will find that there are some tricks you can use to quickly figure out what boxes to use without considering them all. Just don't forget latitude and longitude wrap-around.
If your "only" have millions of points, and they aren't clustered into hot-spots, that might get you through.
A theoretically superior way: You could map each point into three dimensional space and then store them in an octree, which would let you quickly find nearby points to within an arbitrary distance. Of course, the distance in three-dimensional space will be slightly different than the great-circle distance on the globe, so you will have to calculate a conversion factor. That should be simple, though. You don't mention an implementation language, but there is almost certainly going to be a well-tested octree implementation for any language you are working in. If you don't mind inserting the third-party code, this solution is the way to go.