  We report the results of a study to compare the performance of two common
database indexing methods, HTM and HEALPix, on Solaris and Windows database
servers installed with PostgreSQL, and a Windows Server installed with MS SQL
Server. The indexing was applied to the 2MASS All-Sky Catalog and to the Hubble
Source Catalog, which approximate the diversity of catalogs common in
astronomy. On each server, the study compared indexing performance by
submitting 1 million queries at each index level with random sky positions and
random cone search radius, which was computed on a logarithmic scale between 1
arcsec and 1 degree, and measuring the time to complete the query and write the
output. These simulated queries, intended to model realistic use patterns, were
run in a uniform way on many combinations of indexing method and indexing
depth. The query times in all simulations are strongly I/O-bound and are linear
with number of records returned for large numbers of sources. There are,
however, considerable differences between simulations, which reveal that
hardware I/O throughput is a more important factor in managing the performance
of a DBMS than the choice of indexing scheme. The choice of index itself is
relatively unimportant: for comparable index levels, the performance is
consistent within the scatter of the timings. At small index levels (large
cells; e.g. level 4; cell size 3.7 deg), there is large scatter in the timings
because of wide variations in the number of sources found in the cells. At
larger index levels, performance improves and scatter decreases, but the
improvement at level 8 (14 arcmin) and higher is masked to some extent in the
timing scatter caused by the range of query sizes. At very high levels (20;
0.0004 arsec), the granularity of the cells becomes so high that a large number
of extraneous empty cells begin to degrade performance.
