Designing a real-time data platform for the “Internet of Energy”
公司规模
1,000+
地区
- Pacific
国家
- Australia
产品
- Future Grid Platform (FGP)
- Hazelcast IMDG
- Apache Cassandra
技术栈
- In-Memory Data Grid (IMDG)
- Distributed Database
- Real-Time Data Aggregation
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
- 应用基础设施与中间件 - 数据交换与集成
- 平台即服务 (PaaS) - 数据管理平台
适用行业
- 公用事业
适用功能
- 设施管理
- 质量保证
用例
- 能源管理系统
- 机器状态监测
- 预测性维护
- 实时定位系统 (RTLS)
服务
- 软件设计与工程服务
- 系统集成
关于客户
Future Grid is a company that empowers data-rich enterprises to gain insights and control their future through its operational intelligence real-time data platform, the Future Grid Platform (FGP). The platform analyzes hundreds of millions of data points in real-time, enabling actions that reduce operational costs and increase revenue. It provides continuous, real-time complex event processing, real-time data aggregations, rich modeling tools, and contextual awareness. Future Grid works with several Australian utility companies to automate the processing of sensor and smart meter data across energy networks, handling approximately 3 billion data points daily.
挑战
Future Grid faced the challenge of processing extreme volumes of data in real-time for Australian utility companies. Traditional relational databases were inadequate for handling the 3 billion data points collected daily, leading to inefficiencies and high costs. The need for a real-time data aggregation solution was critical to enable complex, real-time decisions and overcome issues related to data volume, speed, reliability, resilience, and license costs.
解决方案
Future Grid built its platform using Hazelcast IMDG, an in-memory data grid designed for high availability and scalability. Hazelcast IMDG helps manage data and distribute processing using in-memory storage and parallel execution, providing significant speed and scale improvements. Future Grid integrated Hazelcast IMDG with Apache Cassandra, a distributed database for managing large amounts of structured data. This combination allowed Future Grid to overcome the limitations of traditional databases, providing continuous availability, linear scale performance, and operational simplicity. The integration enabled Future Grid to deliver real-time data processing and visualization, solving many challenges faced by the energy sector.
运营影响
数量效益
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