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Company: Bouygues Telecom
Industry: Telecommunications
Functional Use Case: Time Series

Bouygues Telecom faced several problems with its existing relational database management solution, which threatened its ability to provide a high level of customer data consistency and an optimal user experience. The challenges they faced included:

  1. Risk of data loss and service interruption: A site failure could result in a loss of access to customer data, leading to service interruptions and negative consequences for the company.
  2. Concerns about data consistency: Bouygues Telecom was uncertain if their relational database could meet their availability requirements. They were also concerned about the consistency of data in NoSQL databases and its implications for customers.

Apache Cassandra helped Bouygues Telecom address these issues in the following ways:

  1. High availability without compromising data quality: The team found that they could guarantee very high availability without having to accept outdated information, ensuring network performance and customer satisfaction.
  2. Detection and correction of data inconsistencies: Cassandra allowed them to query the database in various ways, enabling them to detect and correct inconsistencies.
  3. Scalability: The solution is easily scalable, allowing Bouygues Telecom to handle larger data volumes and, in the long run, manage 1.5 billion transactions per day.
  4. Continuous availability and data consistency: The infrastructure enabled continuous availability across three sites, adapting the level of transactional risk according to each use case. Even in case of a site loss, consistency could be maintained, preventing service disruptions.
Stack Includes: Datastax Enterprise, Grafana, Elasticsearch, Prometheus, React

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