[kleebeesh]

Some storage options are: - Store many vectors in a single HDF5 or LMDB file. - Store single vectors in many small binary files (e.g. using numpy save() function).

To look up neighbors you might: - Compute neighbors exhaustively (e.g. using Scipy distance functions). - Use an Approximate Nearest Neighbors approach like one of the ones benchmarked here (https://github.com/erikbern/ann-benchmarks). These can be much faster than exhaustively computing neighbors, at the cost of some accuracy and having to periodically re-build an index.