  Current and future astronomical surveys are producing catalogs with millions
and billions of objects. On-line access to such big datasets for data mining
and cross-correlation is usually as highly desired as unfeasible. Providing
these capabilities is becoming critical for the Virtual Observatory framework.
In this paper we present various performance tests that show how using
Relational Database Management Systems (RDBMS) and a Zoning algorithm to
partition and parallelize the computation, we can facilitate large-scale query
and cross-match.
