Re: Hardware/OS recommendations for large databases (

For data warehousing its pretty well open and shut. To use all cpus and io channels on each query you will need mpp.

Has anyone done the math.on the original post? 5TB takes how long to scan once? If you want to wait less than a couple of days just for a seq scan, you'd better be in the multi-gb per second range.

- Luke
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-----Original Message-----
From: pgsql-performance-owner(at)postgresql(dot)org <pgsql-performance-owner(at)postgresql(dot)org>
To: pgsql-performance(at)postgresql(dot)org <pgsql-performance(at)postgresql(dot)org>
Sent: Sat Nov 26 13:51:18 2005
Subject: Re: [PERFORM] Hardware/OS recommendations for large databases (

>Another thought - I priced out a maxed out machine with 16 cores and
>128GB of RAM and 1.5TB of usable disk - $71,000.
>
>You could instead buy 8 machines that total 16 cores, 128GB RAM and 28TB
>of disk for $48,000, and it would be 16 times faster in scan rate, which
>is the most important factor for large databases. The size would be 16
>rack units instead of 5, and you'd have to add a GigE switch for $1500.
>
>Scan rate for above SMP: 200MB/s
>
>Scan rate for above cluster: 3,200Mb/s
>
>You could even go dual core and double the memory on the cluster and
>you'd about match the price of the "god box".
>
>- Luke

Luke, I assume you are talking about useing the Greenplum MPP for this
(otherwise I don't know how you are combining all the different systems).

If you are, then you are overlooking one very significant factor, the cost
of the MPP software, at $10/cpu the cluster has an extra $160K in software
costs, which is double the hardware costs.

if money is no object then go for it, but if it is then you comparison
would be (ignoring software maintinance costs) the 16 core 128G ram system
vs ~3xsmall systems totaling 6 cores and 48G ram.

yes if scan speed is the bottleneck you still win with the small systems,
but for most other uses the large system would win easily. and in any case
it's not the open and shut case that you keep presenting it as.

David Lang

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