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Utilitywise Increases Performance of IoT Application Using Redise Pack
Technology Category
- Platform as a Service (PaaS) - Data Management Platforms
- Analytics & Modeling - Real Time Analytics
Applicable Industries
- Utilities
- Buildings
Applicable Functions
- Facility Management
- Business Operation
Use Cases
- Building Energy Management
- Predictive Maintenance
- Remote Asset Management
Services
- System Integration
- Software Design & Engineering Services
The Challenge
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. The Utilitywise IoT application requires extremely fast data ingest as well as rapid processing of data for analytics. The application uses a Microsoft SQL Server and Datastax Cassandra backend, but needed a higher performance database technology to enable it to easily scale.
About The Customer
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 is now helping over 30,000 clients become more energy efficient. By streamlining all procurement processes and the delivery of energy services, Utilitywise’s customers can spend less time worrying about their utility spend and focus on running their companies.
The Solution
Utilitywise chose the Redise Pack solution from Redis Labs for its real-time data ingest, content caching, and analytics applications. Redise Pack 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. The Redise Pack solution is enabling Utilitywise to create a high performance caching layer for the IoT application. It also helped them process streaming data from SignalR on MS Azure with the extremely low latencies they needed. By moving to Redise Pack, Utilitywise was able to cut the latencies on their IoT application from seconds to milliseconds.
Operational Impact
Quantitative Benefit
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