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Drivy Trusts Redis Enterprise as the Database for Real-Time Analytics & Fraud Detection
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
- 汽车
- 运输
适用功能
- 商业运营
- 销售与市场营销
用例
- 欺诈识别
- 实时定位系统 (RTLS)
服务
- 云规划/设计/实施服务
- 系统集成
挑战
Drivy is a small but quickly-growing business. Drivy plans on expanding to other European countries, starting with the U.K. Drivy has had over 1.4 million Rental days logged and nearly 1 million users ever since the platform was created on 2010. With this uptick in growth and a relatively small operational team, Drivy needed to scale its mobile and web app seamlessly without sacrificing performance. Here are a few other challenges that led Drivy to evaluate and ultimately select Redis Enterprise: Values Redis Enterprise’s ability to provide: High availability persistence, auto-failover, cross-zone / multi-region / multi-datacenter in-memory replication Seamless scaling & clustering Stable, high performance
关于客户
Drivy provides peer-to-peer car rental services in Europe through an online platform. Based out of Paris, it connects individuals or legal entities who would like access to a vehicle for a short rental period with available cars (no driver included). Drivy is seeing an increasing user count and chose Redis Enterprise to tackle its scaling needs.
解决方案
Drivy uses several application components featured in Redis for its mobile and web apps. Drivy now holds information for 36,000 cars in its platform and this number is steadily increasing. As their user base and list of rentals grow, so does the need for a scalable database management tool that wouldn’t lose out on performance; customers expect quick turnaround on available rental cars and accurate profile information. The key features and functionalities of Redis Enterprise that Drivy uses: Uses Redis Enterprise for the following: User session store Job & queue management Scalability tier / content caching Throttling, Feature Flipper, Autocomplete, Locking, Short-Term Analytics Logging, light KV store Is using Redis Enterprise in the following solutions: E-commerce Fraud detection Analytics
运营影响
数量效益
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