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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.
The
company
set
to
be
privatized
is
looking
to
increase
revenue
and
attractiveness
to
investors
by
selling
public
data
processing
to
technology
startups
like
Uber.
...
Salesforce
has
a
blueprint
for
tailoring
its
platform
to
industry
specific
use
cases
and
is
using
it
with
the
launch
of
clouds
targeting
manufacturing
and
CPG
companies.
...
Lyft's
"Amundsen"
metadata
system
is
an
example
of
how
knowledge
graphs
are
spreading
throughout
companies
with
grass-roots
projects.
It's
all
part
of
winning
hearts
and
minds,
...
The
Gap
as
it
is
known
today
will
split
brands
such
as
Gap,
Banana
Republic
and
Athleta
and
Old
Navy
for
better
focus.
Executives
outlined
their
data
strategies
in
an
analyst
meeting.
...
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