DM Jul-Aug 2021

TECHNOLOGY: STORAGE Dm
"WHILE BOTH OBJECT STORAGE AND DFS ARE WELL-SUITED FOR STORING SUBSTANTIAL VOLUMES OF
UNSTRUCTURED DATA, THEY SUIT DIFFERENT USE CASES. AS OBJECT STORAGE EXPOSES A REST API, IT IS ONLY
SUITABLE FOR APPLICATIONS THAT ARE SPECIFICALLY INTENDED TO INTERACT WITH THIS TYPE OF STORAGE. IN
CONTRAST, DFS EXPOSE A TRADITIONAL FILESYSTEM API WHICH IS SUITABLE FOR ANY APPLICATION, INCLUDING
LEGACY APPLICATIONS THAT WORK OVER A HIERARCHICAL FILESYSTEM. DFS PROVIDE A DEEPER AND MORE
GENERAL-PURPOSE INTERFACE TO APPLICATIONS, ALLOWING THEM TO PERFORM CERTAIN ACTIVITIES THAT ARE
NOT SUITABLE FOR OBJECT STORAGE."
huge files and is less expensive per
gigabyte than DFS.
IT teams considering implementing a
DFS for their unstructured data must
decide between two different types:
clustered or federated.
CAP THEOREM
As mentioned above, DFS might
support strong or eventual consistency.
This is where computer science theory
comes in, as a distributed data store
can have no more than two out of
three properties according to CAP
theorem. These three properties are:
Consistency: Every read receives the
most recent write or an error
Availability: Every request receives a
(non-error) response - without the
guarantee that it contains the most
recent write
Partition tolerance: The system
continues to operate despite an
arbitrary number of messages being
dropped (or delayed) by the
network between nodes
As a result, there are two types of DFS
currently available:
CLUSTERED DFS
Clustered DFS are made up of a closely
connected cluster of nodes. They focus
strictly on data consistency and are
especially suitable for large-scale
computing use cases at the enterprise
core, such as big data analytics, highperformance
computing, or databases.
The consistency and availability
aspects of CAP theorem are the subject
of clustered DFS. But strong
consistency assurances do not come
cheap. They impose significant
constraints on system operation and
performance, especially when nodes
are separated by high latency or
unreliable connections.
FEDERATED DFS
The goal of federated DFS is to make
data available over long distances
while maintaining partition tolerance.
Federated DFS are well-suited for
weakly linked edge-to-cloud use cases,
including unstructured data storage
and management for remote and
branch offices. Federated DFS focus on
the availability and partition tolerance
properties of the CAP theorem, rather
than the strict consistency guarantee.
In federated DFS, read and write
operations on an open file are routed
to a locally cached copy. When a
modified file is closed, the modified
sections are copied back to a central
file server from the edge. Update
conflicts may arise, and are resolved
automatically. It could be claimed that
federated DFS combines the semantics
of a file system with the eventual
consistency model of object storage. In
this way federated DFS are optimised
for use cases including archiving,
backup, media libraries, mobile data
access, content distribution to edge
locations, content ingestion from edge
to cloud, remote and branch office
storage, and hybrid cloud storage.
Both clustered and federated DFS
have applications in the enterprise. To
reap the full benefits of a DFS, IT
teams must be familiar with how
clustered and federated DFS differ in
order to choose the option most
suited to their application
requirements.
The market is undergoing a
significant shift towards DFS and
object storage, at the same time as
organisations are looking for more
efficient methods to not only cope
with but thrive from the explosion of
unstructured data. The optimal
decision, whether object storage,
clustered or federated DFS, or a
combination, lies in careful
consideration of the organisations'
requirements and use cases.
More info: www.ctera.com
www.document-manager.com
July/August 2021
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