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实例探究 > Hazelcast IMDG Powers real-time Infrastructure for e-commerce

Hazelcast IMDG Powers real-time Infrastructure for e-commerce

技术
  • 分析与建模 - 预测分析
  • 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
  • 消费品
  • 电子商务
适用功能
  • 商业运营
  • 销售与市场营销
用例
  • 预测性维护
  • 实时定位系统 (RTLS)
  • 供应链可见性(SCV)
服务
  • 云规划/设计/实施服务
  • 软件设计与工程服务
  • 系统集成
挑战
Delivering e-commerce systems that provide competitive advantage is one of the toughest challenges facing retailers today. Flexibility and speed are the keys to building a world-beating e-commerce system. The ability to deliver a personalized shopping experience with relevant content at predictable sub-second latency is the difference between business success and failure. Customers will typically wait only 1 to 2 seconds for a page to load before moving on. Speedy response and high availability are absolute musts, and making sense of the huge volumes of data generated by customers is critical. Some of the complex business requirements driving today’s e-commerce systems include generating personalized shopping experiences in microseconds using multiple data streams, omni-channel systems that deliver a consistent shopping experience to the customer across mobile and web, and in-store, removal of data and system silos to present a single view of your data (warehousing, supply chain, social, customer), flexible datastore that allows full-scale updates to an entire product catalog in minutes rather than hours, the ability to meet peak demand workloads and then shrink systems at quieter periods to save compute costs, and dynamic pricing, comparing against competitors’ catalogs, and then adjusting pricing in real-time.
关于客户
With $18.3 billion in annual online sales, this global provider of personal computers and electronics is one of the most visited e-commerce websites in the world, second only to Amazon.com. Burst traffic during new product introductions is at an extreme scale, as are sales on Black Friday, Cyber Monday, and over the holidays. This unique combination of world-class brand experience and extreme burst performance scaling led this e-commerce giant to Hazelcast IMDG as the solution for achieving the best possible price performance for their e-commerce platform.
解决方案
Hazelcast In-Memory Data Grid provides a unique set of characteristics that make it the perfect choice when building e-commerce systems. Increasingly businesses are turning to Hazelcast when their existing systems are unable to deliver on their service-level requirements. It’s not just older technologies such as Oracle databases that are struggling to cope; newer approaches using NoSQL databases are also failing to live up to promises. Hazelcast IMDG is the perfect complement to your existing system of record, enabling the performance and scalability that beats the competition. Adding more capacity to a Hazelcast IMDG cluster is simply a case of starting another node in response to increased demand, then removing the excess node at quieter times. Hazelcast IMDG takes care of the data distribution transparently without significant impact on transaction rates, all without operator intervention. Hazelcast IMDG can store terabytes of data in memory to provide microsecond latencies while performing hundreds of thousands of transactions per second. Hazelcast IMDG includes all the features required to scale, not just locally but also across multiple data centers, while maintaining data coherence. Hazelcast does not impose strict schemas on stored data. With in-situ processing (entryProcessors) Hazelcast can process large documents and return just the data required, improving read performance. Updates to these documents can also be done in-situ, allowing just the change to be sent across the network.
运营影响
  • The customer scaled up to hundreds of nodes of open-source Hazelcast IMDG with a commercial support agreement.
  • The Hazelcast IMDG deployment changed topology to a cluster of dedicated servers with distributed clients all connecting to the dedicated cluster.
  • The customer upgraded to Hazelcast IMDG Enterprise HD to take advantage of its off-Heap memory management feature, the High-Density Memory store (HDMs).
数量效益
  • Reduced cluster sizes from hundreds down to six servers with one node on each server and two copies of that in the same cluster.
  • Each node will have 28GB cache space, so the total cache space will be 6 X 28GB = 168GB.

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