Top Loyalty Provider Adds Customers by Performing Transactions in Real Time
产品
- BigMemory Max
技术栈
- Java
- Hibernate
实施规模
- Enterprise-wide Deployment
影响指标
- Productivity Improvements
- Customer Satisfaction
技术
- 应用基础设施与中间件 - 中间件、SDK 和库
适用行业
- 零售
适用功能
- 销售与市场营销
- 商业运营
用例
- 实时定位系统 (RTLS)
服务
- 系统集成
- 软件设计与工程服务
关于客户
The customer is a top loyalty program provider in the marketing services and loyalty industry. They communicate with retailers through a point-of-sale application that manages activities such as adding points to a customer’s account, subtracting redemptions, and presenting relevant marketing offers — all in real time while the customer waits. The company was looking to win new business from larger retailers, who required that the company commit to an aggressive end-to-end Service Level Agreement (SLA) of 500 milliseconds for every transaction.
挑战
The company, a top loyalty program provider, was facing a challenge in meeting the aggressive end-to-end Service Level Agreement (SLA) of 500 milliseconds for every transaction, as demanded by large retail prospects. The company's data center took an average of 20 percent longer than that — 600 milliseconds — just to query upwards of 32GB of customer data in a central, disk-bound database. Furthermore, Java-related garbage collection pauses caused unexpected spikes in response times that would have resulted in financial penalties for failure to meet the SLA, and in unhappy customers. In order to win new business from larger retailers, the company realized it had to move its data into fast machine memory.
解决方案
The company considered Terracotta BigMemory and Oracle Coherence as options for achieving its performance and scale targets. After a successful proof-of-concept implementation, the company chose Terracotta for its full support for the Ehcache API, better Hibernate support, simpler deployment, a smaller server footprint, and motivated, knowledgeable engineers. The company brought the first retailer into production with all 32 GB of customer information in BigMemory, and immediately experienced an 83 percent drop in data access times — from 600 to 100 milliseconds. At the same time, transaction throughput jumped by a whopping 400 percent. Garbage collection is no longer an issue, allowing the company to meet the 500 millisecond end-to-end SLA demands for the first time.
运营影响
数量效益
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