On Wed, May 30, 2018 at 9:26 PM Robert Haas <robertmhaas@gmail.com> wrote:
> The FDW approach, of which I have been a supporter for some years now,
> is really aiming at a different target, which is to allow efficient
> analytics queries across a multi-node cluster. I think we're getting
> pretty close to being able to do that -- IMHO, the last fundamental
> building block that we need is asynchronous execution, which Andres is
> working on. After that, it's a matter of adding other features that
> people want (like cross-node MVCC) and improving the plans for queries
> that still don't perform well (like joins that involve redistributing
> one of the tables involved).
FWIW, Distributed analytical queries is the right market to be in.
This is the field in which I work, and this is where the action is at.
I am very, very, sure about this. My view is that many of the
existing solutions to this problem (in particular hadoop class
soltuions) have major architectural downsides that make them
inappropriate in use cases that postgres really shines at; direct
hookups to low latency applications for example. postgres is
fundamentally a more capable 'node' with its multiple man-millennia of
engineering behind it. Unlimited vertical scaling (RAC etc) is
interesting too, but this is not the way the market is moving as
hardware advancements have reduced or eliminated the need for that in
many spheres.
The direction of the project is sound and we are on the cusp of the
point where multiple independent coalescing features (FDW, logical
replication, parallel query, executor enhancements) will open new
scaling avenues that will not require trading off the many other
benefits of SQL that competing contemporary solutions might. The
broader development market is starting to realize this and that is a
major driver of the recent upswing in popularity. This is benefiting
me tremendously personally due to having gone 'all-in' with postgres
almost 20 years ago :-D. (Time sure flies) These are truly
wonderful times for the community.
merlin