1 or 2 servers for large DB scenario.

Hi,

I'd appreciate some assistance in working through what would be the
optimal configuration for the following situation.

We currently have one large DB (~1.2TB on disk), that essentially
consists of 1 table with somewhere in the order of 500 million rows ,
this database has daily inserts as well as being used for some semi-
data mining type operations, so there are a fairly large number of
indices on the table. The hardware storing this DB (a software RAID6)
array seems to be very IO bound for writes and this is restricting our
insert performance to ~50TPS.

As we need to achieve significantly faster insert performance I have
been considering splitting the table into 'new' and 'old' data,
making inserts into the 'new' table (which will also help as there are
really 1 insert, an update and some selects involved in populating the
table), then moving the data over to the 'old' DB on a periodic
basis. There would be new hardware involved, I'm thinking of HW RAID
10 to improve the write performance.

The question really is, is it best to use two separate servers and
databases (and have to come up with some copy process to move data
from one to another), or to just add the faster storage hardware to
the existing server and create a new tablespace for the 'new data'
table on that hardware. Doing this would enable us to potentially
move data more easily from new to old (we can't use partitioning
because there is some logic involved in when things would need to be
moved to 'old'). Are there any global resources that make just adding
the faster storage to the existing box a bad idea (the wal_log springs
to mind - although that could be moved too), that would make adding an
additional server instead a better idea?

Also are there any settings that might boost our TPS on the existing
hardware (sync=off isn't an option.. (-: ). I have already
significantly increased the various buffers, but this was mainly to
improve select performance?

Verson of Postgresql is 8.2.3.

Thanks,

David.