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Re: PostgreSQL and Ultrasparc T1

From: "Scott Marlowe" <smarlowe(at)g2switchworks(dot)com>
To: "Juan Casero" <caseroj(at)comcast(dot)net>,<pgsql-performance(at)postgresql(dot)org>
Subject: Re: PostgreSQL and Ultrasparc T1
Date: 2005-12-19 06:25:18
Message-ID: BB4329D6F8E32046ACFC6631ACA3E7BA18FC4B@koolancexeon.g2switchworks.com (view raw or flat)
Thread:
Lists: pgsql-performance
From: pgsql-performance-owner(at)postgresql(dot)org on behalf of Juan Casero

QUOTE:

Hi -


Can anyone tell me how well PostgreSQL 8.x performs on the new Sun Ultrasparc
T1 processor and architecture on Solaris 10?   I have a custom built retail
sales reporting that I developed using PostgreSQL 7.48 and PHP on a Fedora
Core 3 intel box.  I want to scale this application upwards to handle a
database that might grow to a 100 GB.  Our company is green mission conscious
now so I was hoping I could use that to convince management to consider a Sun
Ultrasparc T1 or T2 system provided that if I can get the best performance
out of it on PostgreSQL. 

ENDQUOTE:

Well, generally, AMD 64 bit is going to be a better value for your dollar, and run faster than most Sparc based machines.

Also, PostgreSQL is generally faster under either BSD or Linux than under Solaris on the same box.  This might or might not hold as you crank up the numbers of CPUs.

PostgreSQL runs one process for connection.  So, to use extra CPUs, you really need to have >1 connection running against the database.  

Mostly, databases tend to be either I/O bound, until you give them a lot of I/O, then they'll be CPU bound.

After that lots of memory, THEN more CPUs.  Two CPUs is always useful, as one can be servicing the OS and another the database.  But unless you're gonna have lots of users hooked up, more than 2 to 4 CPUs is usually a waste.

So, I'd recommend a dual core or dual dual core (i.e. 4 cores) AMD64 system with 2 or more gigs ram, and at least a pair of fast drives in a mirror with a hardare RAID controller with battery backed cache.  If you'll be trundling through all 100 gigs of your data set regularly, then get all the memory you can put in a machine at a reasonable cost before buying lots of CPUs.

But without knowing what you're gonna be doing we can't really make solid recommendations...

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