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Back To The Future of Real-Time Applications
Real-time systems have a long history. A new economic tipping point means it's now time to go back to the future...
For the last few decades, operations and analytics have been firmly separated in enterprise architectures, with different systems for the different needs.
This idea is far from new -- for example, here's the text from a Univac computer ad in 1956:
"...there's only one commercially available platform capable of real time performance... It's the ideal system for...simulation and on-line data reduction.
It solves complex problems from purely sensed data at speeds that are compatible with real-time control.
Because of its ability to reduce large volumes of data at tremendous speeds, the...system easily handles even the most difficult problems.
Furthermore, it offers many other outstanding characteristics, including: superb operating efficiency, large capacity, great versatility, the ability to interface with a wide variety of different types of data, and far greater reliability than any other computer of its type...."
Just like some of today's "internet of things" systems, the Univac scientific machine was designed to process information in-memory, directly from sensors (it could also access information from magnetic tape or punch cards).
Note how perfectly the ad ticks all the modern buzzword boxes, promising the 3Vs of big data (volume, variety, and velocity), along with powerful analytics and data compression.
Unfortunately for business in the 1950s, rising amounts of data and cheaper disk storage quickly upended the economics of computing -- and we have had to deal with the complexity and latency of separate operational and analytic systems ever since.
We're now seeing a new tipping point. The falling price of memory and the increased costs of complexity mean that in-memory platforms like SAP HANA are once again the simplest and cheapest way of running businesses.
The result is that although moving to HTAP entails "upheaval in the established architectures" according to Gartner, we're actually getting back to the fundamentals of what we've always wanted.
With
the
number
of
data
breaches
escalating
and
threat
landscape
fast
evolving,
Asia-Pacific
enterprises
will
have
to
think
outside
the
box
and
transform
their
cybersecurity
strategy,
...
It’s
now
data,
not
big
data,
and
the
landscape
is
no
longer
complete
without
AI.
There's
a
wave
of
consolidation
in
the
BI
space
which
raises
the
question,
will
there
be
a
new
generation
...
Famed
Yale
professor
David
Gelernter
and
investment
banker
Rob
Rosenthal
field
questions
about
Revolution
Populi,
their
startup
effort
to
build
a
blockchain-based
alternative
...
Country's
standards
council
plans
to
introduce
at
least
40
standards
to
guide
the
development
and
adoption
of
new
technologies,
including
drones,
additive
manufacturing,
and
...
Fifty
years
after
the
moon
landing,
it's
not
just
NASA
working
on
what
many
consider
the
final
frontier
for
humanity:
space
travel.
NASA,
however,
is
special,
and
one
of
the
reasons
...
Alluxio,
based
on
the
original
AMPLab
Tachyon
project,
wants
you
to
use
its
in-memory
file
system
construct
for
fast
data
access,
sharing
of
data
between
compute
frameworks,
and
...
Interoperability
and
workforce
training
to
use
more
data
in
decision-making
are
at
the
core
of
projects
underpinning
the
reform
of
the
country's
pension
system.
...
How
to
deal
with
a
breakdown
in
theoretical
support
in
machine
learning?
Researchers
from
Carnegie
Mellon
and
Facebook
describe
winning
many
hands
against
the
world’s
top
poker
...
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