[rarestblog]

In anyway this test won't tell you much, just how different systems behave to bigger load.

The local setup was quite usual: PostgreSQL 9.2, Mint 13, default conf in VirtualBox in iMac i5 12GB. (read: home computer, no tuning)

For me the result is that mostly RedShift is on par with local PostgreSQL, sometimes even winning for <5M rows. So with better PostgreSQL tuning you can probably stretch it, but not for as much as RedShift can do for REALLY big data.

Also the big deal was that RedShift scaled linearly.

[fusiongyro]

It scaled linearly, but also went unresponsive for five minutes. (Yeah yeah, it's a new service).

The default Postgres configuration is pretty weak. work_mem is set way to low, for instance, and that's bitten me a few times. I wouldn't say it's unrealistic--lots of people run with it that way in production and never find out how easily they could speed things up. Even me, for years.

But ultimately I'm more swayed by your interaction with it and I hate the endless benchmark tweaking that comes after every blog post about performance testing stuff. The point of this Redshift thing is hugeness first and foremost, so it's interesting.

[dragontamer]

At least on the small scale, I'd expect realistic "local" hosting to outperform any offering from Amazon.

For example, until your data scales above 20 GB, you'd be able to host it on a $5 SSD-based server from Digital Ocean. Most databases are bottlenecked by I/O. So switching to SSDs gives you the biggest performance boost.

On the high end, Amazon's offer probably will be better. (After all, the major draw to Amazon is "automatic scaling", so that you don't have to worry about Replication or other server administration duties at the high end). But considering how powerful a $5 SSD-virtual machine is today, I think a more realistic test would be with some sort of SSD-based cloud server.

[ramarnat]

Like others have mentioned, Postgres and Redshift are very different animals, Postgres is a row store and Redshift is a column store. On large data sets analytic queries that return a few columns will significantly outperform a row store DB.

We have found that Redshift is comparable to other columnar databases we work with, while we cannot publish any comparative benchmarks, we did put a blog post on what we found (link in another comment here)