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From YouTube: It is time to talk about DataMesh
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A
large
number
of
cross
service
queries
when
linking
data,
because
network
and
surface
pressure,
direct
access
to
the
databases
of
other
surfaces
can
solve
some
of
the
former
problems,
but
the
anti-pathogen
approach
will
still
cause
huge
pressure
on
the
databases
mixing.
The
two
methods
will
match
up
the
system:
data
management
logic,
in
addition
to
being
unable
to
control
the
data,
access
path
and
security
system
performance
will
still
be
a
big
problem.
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Such
solutions
are
s
etl
data,
virtualization
data,
warehouse
or
data
lake
have
do,
for
example,
centralized
data
platform
and
data
processing
architecture
will
lead
to
following
drawbacks
data
supply
pipeline
scheduling.
Flexibility
is
limited,
cross
region
crosses
side,
cross
cloud
network
bandwidth,
waste,
low
throughput
and
high
latency.
The
performance
banter
net
force
on
the
data
processing.
Node
data
transformation
easily
performed
too
early,
resulting
in
data
unable
to
be
processed
in
parallel
and
efficiently
cached.
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The
data
is
sent
and
processed
on
a
flat
rate.
There
is
no
momentary
performance
impact,
read
data
source
once
for
many
profession,
you
can
provide
data
to
many
services
without
re-querying
the
data
source.
Even
for
new
services
supported
by
cage
mechanism.
Multiple
applications
can
be
supplied
at
the
same
time
without
impacting
source
high
throughput.