Case Studies Hazelcast IMDG at British Gas

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	Hazelcast IMDG at British Gas

Hazelcast IMDG at British Gas

Technology Category	Analytics & Modeling - Real Time Analytics Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries	Utilities
Applicable Functions	Business Operation Facility Management
Use Cases	Predictive Maintenance Remote Control
Services	Software Design & Engineering Services System Integration
Challenge	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. Read More
About Customer	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. Read More
Solution	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. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Real Time Analytics

Platform as a Service (PaaS) - Data Management Platforms

Applicable Industries

Utilities

Applicable Functions

Business Operation

Facility Management

Use Cases

Predictive Maintenance

Remote Control

Services

Software Design & Engineering Services

System Integration

Challenge

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.

About Customer

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.

Solution

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.

Impact #1	Hazelcast allowed Hive to implement a cache-as-a-service layer, eliminating bottlenecks.
Impact #2	Hive achieved 20,000 writes per second in a 20-node cluster with low latency.
Impact #3	Hazelcast’s ease of management and scalability were key benefits for Hive.

Impact #1

Hazelcast allowed Hive to implement a cache-as-a-service layer, eliminating bottlenecks.

Impact #2

Hive achieved 20,000 writes per second in a 20-node cluster with low latency.

Impact #3

Hazelcast’s ease of management and scalability were key benefits for Hive.

Benefit #1	Hive serves over 200,000 homes with its IoT network.
Benefit #2	Hive achieved 20,000 writes per second in a 20-node cluster.
Benefit #3	Average latency was under 1 millisecond.

Benefit #1

Hive serves over 200,000 homes with its IoT network.

Benefit #2

Hive achieved 20,000 writes per second in a 20-node cluster.

Benefit #3

Average latency was under 1 millisecond.

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Overview

Hazelcast IMDG at British Gas

Operational Impact

Quantitative Benefit