Check out Voltdb (or Scylladb which is more different) for the changes in
architecture required to achieve those performance increases.

On Fri, Sep 2, 2016 at 7:32 PM, Andres Freund <and...@anarazel.de> wrote:

> On 2016-09-02 11:10:35 -0600, Scott Marlowe wrote:
> > On Fri, Sep 2, 2016 at 4:49 AM, dandl <da...@andl.org> wrote:
> > > Re this talk given by Michael Stonebraker:
> > >
> > > http://slideshot.epfl.ch/play/suri_stonebraker
> > >
> > >
> > >
> > > He makes the claim that in a modern ‘big iron’ RDBMS such as Oracle,
> DB2, MS
> > > SQL Server, Postgres, given enough memory that the entire database
> lives in
> > > cache, the server will spend 96% of its memory cycles on unproductive
> > > overhead. This includes buffer management, locking, latching
> (thread/CPU
> > > conflicts) and recovery (including log file reads and writes).
>
> I think those numbers are overblown, and more PR than reality.
>
> But there certainly are some things that can be made more efficient if
> you don't care about durability and replication.
>
>
> > > I wondered if there are any figures or measurements on Postgres
> performance
> > > in this ‘enough memory’ environment to support or contest this point of
> > > view?
>
> I don't think that's really answerable without individual use-cases in
> mind.  Answering that question for analytics, operational, ... workloads
> is going to look different, and the overheads are elsewhere.
>
> I personally think that each implementations restrictions are more
> likely to be an issue than anything "fundamental".
>
>
> > What limits postgresql when everything fits in memory? The fact that
> > it's designed to survive a power outage and not lose all your data.
> >
> > Stonebraker's new stuff is cool, but it is NOT designed to survive
> > total power failure.
> >
> > Two totally different design concepts. It's apples and oranges to
> compare them.
>
> I don't think they're that fundamentally different.
>
>
> Greetings,
>
> Andres Freund
>
>
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