DataCore
Parallel I/O technology seems like a kind of magic, and too good to be true…
but you only need to try it once to understand that it is real and has the
potential to save you loads of money!
Benchmarks
Vs Real world
Frankly, I was skeptical at
first and I totally underestimated this technology. The benchmark posted a while ago was
incredibly good (too good to be true?!). And even though this one wasn’t false,
sometimes you can just work around some limits of the benchmarking suite and
build specific and unrealistic configurations to get numbers that look very
good, but that are hard to reproduce in real world scenarios.
When I
was briefed by DataCore they convinced me not with sterile benchmarks, but with
real workload testing! In fact, I was particularly impressed by a set of
amazing demos I had the chance to watch where a Windows database server,
equipped with Parallel I/O Technology, was able to process data dozens of times
faster than the same server without DataCore’s software… and the same happened
with a cloud VM instance (which is theoretically the same, since this is a
software technology, but is much more important than you think… especially if
you look at how much money you could save by adopting it).
Yes,
dozens of times faster!
I know it seems ridiculous, but
it isn’t. DataCore Parallel Server is a very simple piece of software that
changes the way IO operations are performed. It takes advantage of the large
number of CPU cores and RAM available on a server and allows to organize all
the IOs in a parallel fashion, instead of serial, allowing to achieve
microsecond level latency and, consequently, a very large number of IOPs.
This
kind of performance allows to build smaller clusters or get results much faster
with the same amount of nodes… and without changing the software stack or
adding expensive in-memory options to your DB. It is ideal for Big Data
Analytics use cases, but there are also other scenarios where this technology can
be of great benefit!
Just
software
I don’t
want to downplay DataCore’s work by saying “just software”, quite the contrary
indeed! The fact that we are talking about a relatively simple piece of
software makes it applicable not only to your physical server but also to a VM
or, better, a cloud VM.
If you
look at cloud VM prices, you’ll realise that it is much better to run a job in
a small set of large-CPU large-memory VMs than in a large amount of SSD-based
VMs for example… and this simply means that you can spend less to do more,
faster. And, again, when it comes to Big Data Analytics this is a great result,
isn’t it?
Closing
the circle
DataCore is one of those
companies that has been successful and profitable for years. Last year, with
the introduction of Parallel I/O they demonstrated their capability of still
being able to innovate and bring value to their customers. Now, thanks to an
evolution of Parallel I/O, they are entering in a totally new market, with a
solution that can easily enable end users to save loads of money and get faster
results. It’s not magic of course, just a much better way to use the resources
available in modern servers.
Parallel
Server is perfect for Big Data Analytics, makes it available to a larger
audience, and I’m sure we will see other interesting use cases for this
solution over time…
