Utilitywise is a utilities broker and energy services company that bridges suppliers and consumers of power. As one of the UK’s leading independent consultancies, Utilitywise has helped over 30,000 clients become more energy efficient. By deploying the Redis Enterprise database solution, Utilitywise was able to reduce application downtime for its IoT application and additionally saw a dramatic improvement in performance. Utiltywise’s customers spend less time worrying about their utility spend and focus more on running their companies.

The Need for a Higher Performance RDBMS

The Utilitywise IoT application streams live data from buildings, enabling users to control their business energy assets from their phones. The application operates physical devices in buildings including lighting, heating, and ventilation systems. This required extremely fast data ingest as well as rapid processing of data for analytics. The application used a Microsoft SQL Server and Datastax Cassandra backend, but needed a higher performance database platform to enable easy and seamless scale.

Utilitywise chose the Redis Enterprise from Redis for its real-time data ingest, content caching, and analytics applications. Redis enterprise extends open source Redis and delivers operational benefits of stable, high performance, zero-downtime linear scaling and hassle-free true high availability with substantially lower operational costs.

Customer requirements

  • A high performance database solution to enable easy scalability for new Internet of Things (IoT) application

Redis Enterprise benefits

  • Reduced application downtime by up to 70%
  • Obtained 300% higher and more stable performance
  • Substantially reduced application latencies by 1,000x

How Redis Enterprise Plays Very Nice with Others

Since the IoT application processes mainly time-series data, Utilitywise also uses Apache Spark to analyze and spot patterns in the data which is stored in Cassandra. Redis Enterprise allows them to respond instantaneously to actions detected, so that power consumption can be controlled and managed in real time for energy savings. Other technologies used in the stack include Microsoft Azure, Apache Spark, Signal R, Cassandra, and Microsoft SQLServer.