Ellie Mae's Adoption of Hazelcast for Enhanced Performance and Scalability
公司规模
1,000+
地区
- America
国家
- United States
产品
- Encompass
- Hazelcast High-Density Memory Store
技术栈
- .Net
- Java
- Hazelcast
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Customer Satisfaction
- Productivity Improvements
技术
- 分析与建模 - 预测分析
- 基础设施即服务 (IaaS) - 云存储服务
- 平台即服务 (PaaS) - 数据管理平台
适用行业
- 金融与保险
适用功能
- 商业运营
用例
- 预测性维护
- 过程控制与优化
- 远程资产管理
服务
- 软件设计与工程服务
- 系统集成
- 测试与认证
关于客户
Since its foundation in 1997, Ellie Mae has become the leading provider of end-to-end business automation software for the U.S. mortgage industry, facilitating the process of originating and funding mortgage loans so lenders can achieve compliance, quality, and efficiency. Ellie Mae serves banks, credit unions, and mortgage companies of all sizes, providing an all-in-one, fully integrated solution that covers the entire loan lifecycle. Ellie Mae provides one system of record so loan providers can close high-quality, compliant loans more efficiently, no matter what the industry or regulators do next. Encompass® is an end-to-end solution delivered using a software-as-a-service (SaaS) model that serves as the core operating system for mortgage originators. Encompass spans customer relationship management, loan origination, and business management. Ellie Mae also provides an integrated network that allows mortgage professionals to conduct electronic business transactions with mortgage lenders and settlement service providers who process and fund loans. According to estimates, more than 20% of all mortgage originations in the U.S. flow through the Ellie Mae network.
挑战
Before Ellie Mae adopted Hazelcast, its Encompass application was suffering from two major problems: performance and scalability. Encompass could not function within the approved service level agreements due to the disk-based access methodology of its database vendor, resulting in high latencies and lower throughput. Attempts at caching frequently used data in the Encompass application’s memory with a homegrown caching solution failed due to data inconsistency across application nodes. This internal solution was too burdensome to maintain and did not guarantee high availability, resulting in failed SLAs. Scalability was another major challenge, as Ellie Mae was expecting its business to grow by 25% to 30% every year, and its current application memory setup was not scalable, potentially resulting in significant losses.
解决方案
Ellie Mae was looking for a distributed solution that was scalable on-demand and high performance with cross-platform support, such as .Net/Java. They evaluated major solution providers, including Hazelcast, with stringent requirements around data lifetime validity, eviction, notifications, and flexible cluster-wide data consistency. From a performance point of view, Ellie Mae needed a system capable of running in a multitenant infrastructure where hundreds of client nodes could connect to a distributed server cache and handle more than 28,000 concurrent transactions. Hazelcast was chosen for its stability, performance, durability, and capabilities to scale on demand with minimum obstructions. Hazelcast replaced Ellie Mae’s homegrown caching solution, allowing the Encompass application to use ~100 GBs of data stored in Hazelcast servers. This provided super-fast access to data and increased throughput, resulting in overall increased performance. Hazelcast High-Density Memory Store addressed garbage collector-related problems by not allowing the garbage collector to run in its store, preventing application pauses and providing low latency and predictable access to data. Ellie Mae also benefited from Hazelcast’s elasticity, allowing them to scale up and down quickly and dynamically.
运营影响
数量效益
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