Hazelcast IMDG accelerates Financial Market Data access For Investment Banking
公司规模
1,000+
地区
- Pacific
国家
- Australia
产品
- Hazelcast IMDG
- Redis
- Coherence
- Terracotta
技术栈
- Java
- Scala
- Node.js
- Python
- .NET
- C++
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Customer Satisfaction
- Productivity Improvements
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
- 应用基础设施与中间件 - 数据库管理和存储
适用行业
- 金融与保险
适用功能
- 商业运营
用例
- 预测性维护
- 实时定位系统 (RTLS)
- 远程资产管理
服务
- 软件设计与工程服务
- 系统集成
关于客户
National Australia Bank (NAB) is one of the largest financial institutions in Australia, providing a wide range of banking and financial services. NAB was looking for a replacement for their existing Ehcache-based solution to cache session objects for their API gateway. The existing solution was neither scalable nor capable of providing stable uptime. All digital channels, from mobile to Internet Banking, as well as other groups, access backend systems through this API gateway. The gateway provides security, threat perception, and transformation. NAB evaluated Hazelcast IMDG and Redis, ultimately choosing Hazelcast IMDG for its elasticity, scalability, and highly available distributed solution. NAB has two Hazelcast clusters across two data centers, kept in sync using WAN Replication from Hazelcast IMDG Enterprise.
挑战
Market Data systems in investment banking require the ability to onboard new data feeds quickly and efficiently. Traditional relational databases and NoSQL solutions often fall short due to their reliance on disk-based storage, leading to poor application query performance and unacceptable online customer experiences. Integrating multiple market data feeds without impacting existing throughput is critical, but schema changes in RDBMS can introduce narrow maintenance windows and system impacts. Additionally, trading desk systems demand low latency access to data, which is often measured in microseconds. The complexity and high cost of maintaining these data feeds can stifle innovation and lead to duplication of efforts across multiple development teams.
解决方案
Hazelcast IMDG was chosen as the ideal solution for NAB's needs. Hazelcast uses a single standard Java API and provides native language clients for Java, Scala, Node.js, Python, .NET, and C++, as well as an Open Client network Protocol for building any other native language client needed. Hazelcast is a schema-less in-memory data store, approximately 1,000 times faster than RDBMS, achieving query and update times measured in microseconds for high volumes of data. This allows for the quick and easy integration of multiple market data feeds without impacting existing throughput. Hazelcast's unique in-memory management drastically narrows latency volatility to levels unachievable with NoSQL and RDBMS systems. With Hazelcast IMDG, ROI can be achieved through reduced data integration effort, maximization of economies of scale in terms of memory utilization, and ongoing operational costs, both in terms of hardware and software.
运营影响
数量效益
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
相关案例.
Case Study
Real-time In-vehicle Monitoring
The telematic solution provides this vital premium-adjusting information. The solution also helps detect and deter vehicle or trailer theft – as soon as a theft occurs, monitoring personnel can alert the appropriate authorities, providing an exact location.“With more and more insurance companies and major fleet operators interested in monitoring driver behaviour on the grounds of road safety, efficient logistics and costs, the market for this type of device and associated e-business services is growing rapidly within Italy and the rest of Europe,” says Franco.“The insurance companies are especially interested in the pay-per-use and pay-as-you-drive applications while other organisations employ the technology for road user charging.”“One million vehicles in Italy currently carry such devices and forecasts indicate that the European market will increase tenfold by 2014.However, for our technology to work effectively, we needed a highly reliable wireless data network to carry the information between the vehicles and monitoring stations.”
Case Study
Safety First with Folksam
The competitiveness of the car insurance market is driving UBI growth as a means for insurance companies to differentiate their customer propositions as well as improving operational efficiency. An insurance model - usage-based insurance ("UBI") - offers possibilities for insurers to do more efficient market segmentation and accurate risk assessment and pricing. Insurers require an IoT solution for the purpose of data collection and performance analysis
Case Study
Smooth Transition to Energy Savings
The building was equipped with four end-of-life Trane water cooled chillers, located in the basement. Johnson Controls installed four York water cooled centrifugal chillers with unit mounted variable speed drives and a total installed cooling capacity of 6,8 MW. Each chiller has a capacity of 1,6 MW (variable to 1.9MW depending upon condenser water temperatures). Johnson Controls needed to design the equipment in such way that it would fit the dimensional constraints of the existing plant area and plant access route but also the specific performance requirements of the client. Morgan Stanley required the chiller plant to match the building load profile, turn down to match the low load requirement when needed and provide an improvement in the Energy Efficiency Ratio across the entire operating range. Other requirements were a reduction in the chiller noise level to improve the working environment in the plant room and a wide operating envelope coupled with intelligent controls to allow possible variation in both flow rate and temperature. The latter was needed to leverage increased capacity from a reduced number of machines during the different installation phases and allow future enhancement to a variable primary flow system.
Case Study
Automated Pallet Labeling Solution for SPR Packaging
SPR Packaging, an American supplier of packaging solutions, was in search of an automated pallet labeling solution that could meet their immediate and future needs. They aimed to equip their lines with automatic printer applicators, but also required a solution that could interface with their accounting software. The challenge was to find a system that could read a 2D code on pallets at the stretch wrapper, track the pallet, and flag any pallets with unread barcodes for inspection. The pallets could be single or double stacked, and the system needed to be able to differentiate between the two. SPR Packaging sought a system integrator with extensive experience in advanced printing and tracking solutions to provide a complete traceability system.
Case Study
Transforming insurance pricing while improving driver safety
The Internet of Things (IoT) is revolutionizing the car insurance industry on a scale not seen since the introduction of the car itself. For decades, premiums have been calculated using proxy-based risk assessment models and historical data. Today, a growing number of innovative companies such as Quebec-based Industrielle Alliance are moving to usage-based insurance (UBI) models, driven by the advancement of telematics technologies and smart tracking devices.
Case Study
MasterCard Improves Customer Experience Through Self-Service Data Prep
Derek Madison, Leader of Business Financial Support at MasterCard, oversees the validation of transactions and cash between two systems, whether they’re MasterCard owned or not. He was charged with identifying new ways to increase efficiency and improve MasterCard processes. At the outset, the 13-person team had to manually reconcile system interfaces using reports that resided on the company’s mainframe. Their first order of business each day was to print 20-30 individual, multi-page reports. Using a ruler to keep their place within each report, they would then hand-key the relevant data, line by line, into Excel for validation. “We’re talking about a task that took 40-80 hours each week,” recalls Madison, “As a growing company with rapidly expanding product offerings, we had to find a better way to prepare this data for analysis.”
