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MapR Selected by KODAKOne as Underlying Data Platform for Blockchain-based Image Marketplace

SANTA CLARA, Calif.–(BUSINESS WIRE)–MapR®
Technologies, Inc.
, provider of the industry’s next generation data
platform for AI and Analytics, today announced that KODAKOne,
the blockchain-based image rights management platform, will utilize the
MapR Data Platform for a range of data services and digital asset
storage. A beta version of the KODAKOne product is due to launch in late
2018.

The KODAKOne Platform is an image protection, monetization and
distribution platform secured in blockchain. It will provide an image
marketplace where users can buy, sell and trade photos based on
licensing terms and conditions – serving as a one-stop shop for
photographers’ management, protection and distribution needs. The
platform will create an encrypted ledger of rights ownership for
photographers to protect, manage and monetize their new and archived
works – making it significantly cheaper and faster to register, move and
sell their digital images.

MapR will provide all data services for the KODAKOne Platform, offering
enterprise-ready software which can scale as required. The ability of
the MapR solution to integrate easily with micro-service based
architectures will allow KODAKOne to develop and upgrade the platform
with new applications when needed. The MapR platform will help to
support overall compliance for KODAKOne internal processing and data
access, as well as providing the requisite security features it needs to
be fully protected.

“The KODAKOne Platform has been designed to simplify the process of
protecting, distributing and licensing digital assets so that
photographers are free to concentrate on producing fantastic imagery. In
order to deliver this, it’s critical that the platform has the right
data capabilities. As the only enterprise-ready big data solution on the
market, the MapR Data Platform was the obvious choice for integration
with our solution,” Volker Brendel, CTO at KODAKOne explained.

“With MapR technology, we benefit from stability, speed, flexibility and
security whilst also reducing our platform transaction costs massively
in the short, mid and long term,” Brendel said. “The MapR solution is
able to combine different data services within a single platform,
drawing on multiple data centers and several global cloud providers to
give the KODAKOne Platform the power it needs to develop at speed and
perform as an enterprise-grade solution.”

The flexibility of the MapR Data Platform and its use of
industry-standard APIs meant that the KODAKOne Platform did not have to
be built using complex competitive tools, driving down costs and
timelines.

“The protection of digital assets has never been more necessary and it
is clear that the capabilities of the KODAKOne Platform will be highly
valuable for photographers who need to protect their imagery and
therefore their livelihoods,” said Jim Stock, VP of EMEA for MapR. “The
MapR Data Platform will provide KODAKOne with the level of data services
it needs to give end users the best possible functionality, while at the
same time allowing KODAKOne to scale securely and add new applications
as required.”

Tweet this: .@MapR Selected by @KodakOne as Underlying #Data Platform
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About MapR

MapR
Technologies
, provider of the industry’s next generation data
platform for AI and Analytics, enables enterprises to inject analytics
into their business processes to increase revenue, reduce costs, and
mitigate risks. MapR addresses the data complexities of high-scale and
mission critical distributed processing from the cloud to the edge, IoT
analytics, and container persistence. Global 2000 enterprises trust the
MapR Data Platform to help them solve their most complex AI and
analytics challenges. Amazon, Cisco, Google, Microsoft, SAP and other
leading businesses are all part of the MapR ecosystem. For more
information, visit mapr.com.

MapR is a registered trademark of MapR Technologies, Inc. in the
United States and other countries.
Other names and brands may be
the property of others.


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