UNCOVERING THE LAYERS
manage, secure, govern and protect
data along with tools to enable the
consumption of data by a broad set of
applications and tools. The complexity of
data is handled based on defined policies
that span across locations, hardware
infrastructures from on-premises to the
cloud to the edge and containers.
Pinakin Patel, Head of Solutions
Engineering at MapR
delivery between sources and destination
to allow enterprises to focus solely on the
use case and not the plumbing.
Beyond storage
Unlike the old world of storage that
centred around volumes, blocks, files
and more recently objects, dataware
instead presents a set of standards-
based APIs that enables enterprises to
www.intelligentdatacentres.com
The notion of abstraction is like the way in
which operating systems manage hardware
using device drivers that provide a known
set of interfaces to mask the complexity
of the underlying graphics, networking and
audio chipsets. This capability to deliver
data based on need instead of underlying
limitation is particularly useful in use cases
that may require multiple sources of data,
of differing types, that are served from
disparate sources.
For example, take a ride sharing service
such as Uber or Lyft; the service will include
both real-time streaming data from drivers
and passengers, traditional customer
information from a database and, in the
back end, the service is making lots of
analytical decisions around journey planning,
capacity and demand. Factors such as
weather, time of day and temperature can all
add into these calculations.
There may be multiple sources for these
elements and differing parsing that may
change as the application set evolves.
Hard coding these data elements into
the workflow is inefficient, especially
if the data structure, type or source
changes. Instead, in a dataware model,
the dataware abstraction layer manages
acquisition, storage, parsing and delivery
of the required data to the application and
handles any return path data capture.
If a new data type is required for the
applications, for example geographic
information system (GIS) mapping data,
the dataware can handle the management
complexity involved in its acquisition and
present the data to the application group
in the required format.
Although the term ‘dataware’ might be
new, the notion of abstraction is very
old and as more data technologies start
to coalesce around emerging standards
such as JSON, S3, Spark, Kafka and
others, the easier it becomes to add
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