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实例探究 > Hazelcast IMDG at British Gas

Hazelcast IMDG at British Gas

技术
  • 分析与建模 - 实时分析
  • 平台即服务 (PaaS) - 数据管理平台
适用行业
  • 公用事业
适用功能
  • 商业运营
  • 设施管理
用例
  • 预测性维护
  • 远程控制
服务
  • 软件设计与工程服务
  • 系统集成
挑战
British Gas-funded start-up Hive needed a technology solution to store large amounts of data in memory for quick access. The company required integration with its current core backend platform and a product that could scale linearly to fit its growing needs. Ease of querying, real-time query capability, and custom queries were essential. Hive also needed to cache state information for millions of devices with simple deployment and management. After trying MongoDB and finding it inadequate for their traffic demands, Hive sought a better solution.
关于客户
British Gas, a major energy provider in the UK, has been serving homes and businesses for over 200 years. The company funds energy performance partnerships and consumer-targeted energy-efficiency initiatives. Hive, backed by British Gas, is the UK's largest IoT network, serving over 200,000 homes. Hive's system allows users to remotely control heating and hot water temperatures via mobile devices or the Web. The system includes a wireless thermostat, a hub for internet connectivity, and a receiver for executing temperature changes. Hive aims to expand into complete connected home automation solutions.
解决方案
Hive chose Hazelcast’s in-memory data grid after finding MongoDB inadequate. Hazelcast demonstrated superior performance in initial scale tests, allowing Hive to implement a cache-as-a-service layer. This eliminated bottlenecks and enabled 20,000 writes per second in a 20-node cluster with low latency. Hazelcast’s ease of management and scalability were key benefits. Hive reported success with Hazelcast, achieving desired throughput and ease of adding capacity. The company plans to continue using Hazelcast for its remote home automation products and general-purpose caching needs.
运营影响
  • Hazelcast allowed Hive to implement a cache-as-a-service layer, eliminating bottlenecks.
  • Hive achieved 20,000 writes per second in a 20-node cluster with low latency.
  • Hazelcast’s ease of management and scalability were key benefits for Hive.
数量效益
  • Hive serves over 200,000 homes with its IoT network.
  • Hive achieved 20,000 writes per second in a 20-node cluster.
  • Average latency was under 1 millisecond.

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