Case Studies > Ellie Mae's Adoption of Hazelcast for Enhanced Performance and Scalability

Ellie Mae's Adoption of Hazelcast for Enhanced Performance and Scalability

Company Size
1,000+
Region
  • America
Country
  • United States
Product
  • Encompass
  • Hazelcast High-Density Memory Store
Tech Stack
  • .Net
  • Java
  • Hazelcast
Implementation Scale
  • Enterprise-wide Deployment
Impact Metrics
  • Cost Savings
  • Customer Satisfaction
  • Productivity Improvements
Technology Category
  • Analytics & Modeling - Predictive Analytics
  • Infrastructure as a Service (IaaS) - Cloud Storage Services
  • Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
  • Finance & Insurance
Applicable Functions
  • Business Operation
Use Cases
  • Predictive Maintenance
  • Process Control & Optimization
  • Remote Asset Management
Services
  • Software Design & Engineering Services
  • System Integration
  • Testing & Certification
About The Customer
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.
The Challenge
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.
The Solution
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.
Operational Impact
  • Hazelcast provided Ellie Mae with a seamless replacement for their homegrown caching solution, requiring no significant architectural changes to the application.
  • The new architecture allowed Ellie Mae’s Encompass application to store ~100 GBs of data in Hazelcast servers, providing super-fast access to data and increased throughput.
  • Hazelcast High-Density Memory Store addressed garbage collector-related problems, preventing application pauses and providing low latency and predictable access to data.
  • Ellie Mae experienced fine-grain control over transactional consistency of data using Hazelcast lock APIs and Hazelcast Backups for high availability.
  • Extensive testing ensured data consistency and availability, with Hazelcast passing extreme stress tests and evolving into a mature and stable offering.
Quantitative Benefit
  • Average TPS per client = 4500
  • Average TPS across 8 nodes cluster = 31,500
  • Average latency < 2 milliseconds
  • Towards the end of benchmarking, the application delivered a TPS of 45,000 with a latency of < 2 milliseconds.
  • High-Density Memory Store resulted in ultra-low CPU usage and less than 3 GB of heap consumption on each server node.

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