ArcObjects table views or sqlite3 in Python?

Question

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.

Answer 1

I'm pretty sure that it would be easier to use the pre-existent features of ArcGIS to do your tasks. Querying a sqlite3 database is easy, but not as easy as using the search cursor in python arc objects API.

The need for table joins can complicate the ESRI side of things. Are your "to-be joined data" stored in what DBMS?

Spatial operations will always be easier to use ESRI API. The only difference would happen if you would use something like GeoScript, that has some spatial features or other geometry framework.

Give us more information and let's see if we can help out.

Answer 2

One alternative would be an InMemoryWorkspace, which can also be used from python.

There are examples in the old esri forums.