Take the 2-minute tour ×  Given a larger csv (1000+ points) with
attributes, I need to do both attrbute and spatial queries on
the data. Would it be faster to read the points into an xy
feature class, and do the spatial and data queries as table
views and feature layers, or would it be faster to read the csv
into a temporary sqlite3 database, do the data queries, then
transform the output into an xy class to do the spatial queries?
Also, would it be faster one way or the other if we also needed
to include table joins? Lastly if you have any alternate methods
please add them.  share|improve this question Apologies for the
double post... –  om_henners Jul 26 '10 at 13:05 In reply to
@George: we have a series of CSV files, some with station
locations and IDs, others with test results over time for air
quality, rainfall etc. The idea being that we aggregate and join
some of these test results to our points, and select various
points based on areas of interest. I think you're right on the
spatial query side, I'm r