Utilitywise Increases Performance of IoT Application Using Redise Pack
公司规模
1,000+
地区
- Europe
国家
- United Kingdom
产品
- Redise Pack
- Microsoft SQL Server
- Datastax Cassandra
- Apache Spark
技术栈
- Microsoft SQL Server
- Datastax Cassandra
- Apache Spark
- Microsoft Azure
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Customer Satisfaction
- Productivity Improvements
技术
- 分析与建模 - 实时分析
- 网络与连接 - 低功耗广域网
- 平台即服务 (PaaS) - 数据管理平台
适用行业
- 建筑物
- 公用事业
适用功能
- 商业运营
- 设施管理
用例
- 建筑能源管理
- 预测性维护
- 远程资产管理
服务
- 软件设计与工程服务
- 系统集成
关于客户
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.
挑战
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.
解决方案
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.
运营影响
数量效益
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