Running MonetDB/XQuery on a 2.6GHz 32-bit Windows XP box with 1GB of RAM. What is the best way to organise XML in MonetDB for rapid text searching? A run down of my recent experience might help. I created a collection of around 450 documents (153MB approx.). I ran the following query from the command line: collection("papers")//p[contains(., 'wind farm')] The query time is at best 19 seconds. That's bad. (It's worse than querying a Postgres database with documents stored in the XML field type.) So to get a reference point I loaded up the 114MB XMark document and ran this query: doc("standard")//text[contains(., "yoke")] The query time varies from 2 to 4 seconds. Better, but still not great. Now, adding more RAM (and moving to 64-bit) would speed things up I hope! But hardware aside: 1. Is it better to have big documents rather than big collections? 2. Is having small collections (<10 docs) of big documents also inefficient? Ideally I need to query collections comprising several thousand documents using 'text search' predicates. Are there other, better ways to run this type of query against a MonetDB XML database? Or should I really be using some other platform for this task? Thanks in advance for any pointers. -- Roy