WRT exposing Postgres, you're right that you can't simply expose a database and then expect the DB to scale under random selects, inserts, etc. (RAC is another matter I guess.)

However, as I said in the first comment to the blog post, if you define an interface using stored procedures (a pattern familiar to many Oracle DBAs), then PL/Proxy (http://pgfoundry.org/projects/plproxy/) lets you do hash-based partitioning in a way that's more or less transparent to the end-user of a DB, again assuming that it has a defined interface. The PL/Proxy installs form a 'bus' between the DB and the user.

Self-promotion: I'm currently working on hacking PL/Proxy into something that can be used to auto-scale a Postgres cluster on-demand, which has interfaces as a pre-requisite, along with some other things. The end-goal is to do exactly what you say: to scale-out Postgres like any other internet service on an ideal horizontal. Link: http://code.google.com/p/hotrepart

(Hum, I'm gonna get accused of spamming for repeating myself so often :-)

While Skype's PL/Proxy is a great way to make PostgreSQL more scalable, it doesn't do much to refute the basic argument that SQL databases aren't scalable since the SQL it helps you scale is limited to short RPC style operations.

That's a good point, and it brings to light an unspoken assumption underlying my post, which is that the use-case is a web-based, read-heavy OLTP-style system. If you were thinking of things like OLAP and data warehousing, then I'd agree with you absolutely.

However, under my re-qualified assertion :-) for large, complicated commits, the logic would either have to be at the database level for it to be in the same transaction, or a solution using temporary tables could be put together for more convoluted calls.

Neither of these are elegant, I'll grant you, but the two basic approaches - longer transactions over logic closely coupled to the datastore, or staged writes - are what most DBAs on high-end databases end up doing anyway, and would probably be reproduced in some form or another in any ACID system, no? Either way you'd still have a database that scales.

For what it's worth, you can most definitely do that with Oracle. I can't speak to Postgres scalability, but it is my DB of preference. (I guess it might have something to do with the fact it's as close to Oracle as you're going to get in Open Source).

We design apps to treat the datasource as a network service, and have no problems load balancing DB connections across our database cluster, and adding new DB nodes as required.

The biggest problem I've seen is the relative lack of support for Oracle in something like Rails, or non-Oracle app servers in general. I've had to custom write some connection pool failure detection for a few apps to deal with cluster failure (something that comes out of the box with the Oracle app server, but we wanted to use JBoss and GlassFish), so while it's not perfect, it's most definitely doable.

Just because his particular architecture or offering doesn't fit well with typical database deployment architectures, doesn't mean that "SQL doesn't scale".

Maintaining connections in the face of failure is a relatively little concern, what I perceive as the big problem here is having the database handle an arbitrary application with zero application-specific administration.

Google's datastore promises that if you write your app for their platform and it works on the small scale, it will scale out without problems. Datastore latency is constant regardless of how many records you have there. How will you scale a join between two tables, each being partitioned between multiple different servers, transparently for the app?