Press release

Bouygues Telecom Achieves Zero Downtime by Replacing Relational Database With DataStax

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DataStax,
the leading provider of the active everywhere hybrid cloud database
built on Apache Cassandra™, today announced that Bouygues Telecom, a
French mobile phone, internet service provider, and IPTV company, is
using DataStax
Enterprise
to improve the availability, scalability, and consistency
of its network.

Click
to Tweet:
After learning its relational #database couldn’t keep
its network running, @bouyguestelecom implemented @DataStax & now
experiences zero #downtime and plans to scale to 1.5 billion
transactions per day https://bit.ly/2OO7Xrj

Bouygues Telecom has more than 16.4 million mobile phone customers and
provides 4G service to more than 97% of the French population. The
company was struggling with the data quality and availability of its
provisioning system, which keeps its networks running, and needed to
replace its relational database with something far more powerful and
flexible.

With DataStax, a globally distributed and scalable intelligent database,
Bouygues Telecom avoided having to use obsolete or outdated data and was
able to guarantee very high network availability without compromising
data quality.

“We were able to start working off clean and consistent data without
having to worry about downtime,” said Louis Le Compagnon, Head of the
Development Center and Shared Architecture within the Networks
Department of Bouygues Telecom. “That is a huge advantage and step
forward.”

“We’re honored to be able to help a company of Bouygues Telecom’s size
and importance maintain a complicated network and improve service for
its customers,” said DataStax CMO Cate Lochead. “With our help, Bouygues
Telecom is keeping millions of people consistently and seamlessly
connected to their essential communications tools.”

DataStax allows querying of the database in several ways, making it
possible to detect and correct inconsistencies. The solution is also
easily scalable and Bouygues Telecom hopes to eventually use it to
handle 1.5 billion transactions per day. Another advantage of DataStax:
the high level of security within the cluster, which allows native
encryption—an extremely valuable function in the context of the General
Data Protection Regulation (GDPR) and the sensitive customer data that
telecom operators sometimes handle.

“Today, we have an infrastructure that allows us to ensure continuous
availability on our three websites,” Le Compagnon continued. “If all the
nodes integrate all the data, all are not systematically used and we
adapt the level of transactional risk according to each case of use. If
a site is lost, consistency can be maintained. For example, we lost four
nodes in pre-production, but we did not suffer any loss of service.”

Click
here
to learn more about how Bouygues Telecom is using DataStax.

Learn more:

To learn more about DataStax and DataStax Enterprise, please join
DataStax at DataStax Accelerate, the world’s premier Apache
Cassandra™ conference, May 21-23, 2019, in the Washington D.C. area. To
register, please visit: www.datastax.com/accelerate

About DataStax

DataStax delivers the always-on, active everywhere distributed hybrid
cloud database built on Apache Cassandra™. The foundation for
personalized, real-time applications at scale, DataStax Enterprise makes
it easy for enterprises to exploit hybrid and multi-cloud environments
via a seamless data layer that eliminates the issues that typically come
with deploying applications across multiple on-premises data centers
and/or multiple public clouds.

Our product also gives businesses full data visibility, portability, and
control, allowing them to retain strategic ownership of their most
valuable asset in a hybrid/multi cloud world. We help many of the
world’s leading brands across industries transform their businesses
through an enterprise data layer that eliminates data silos and cloud
vendor lock-in while powering modern, mission-critical applications. For
more information, visit www.DataStax.com
and follow us on Twitter @DataStax.

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