Download PDF
Delivering Financial Market Data On-Demand with Redis Labs Enterprise Cluster (RLEC)
Technology Category
- Application Infrastructure & Middleware - Data Exchange & Integration
- Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
- Finance & Insurance
- Software
Applicable Functions
- Business Operation
Use Cases
- Predictive Maintenance
- Real-Time Location System (RTLS)
Services
- Software Design & Engineering Services
- System Integration
The Challenge
Qin Yu, Director of Engineering at Xignite.com, was faced with the pressures of delivering a technology architecture that could handle the massive volume of financial market data with sub-millisecond latencies. A thorough understanding of databases and their best use cases was required to curate the best technology solution for Xignite. Open Source Redis was an obvious choice for any data that required fast access, as well as complex computations via in-memory analytics. Qin chose Redis for its versatile data structures, commands and Lua scripting support, which made it the simplest, fastest way to crunch the data delivered by Xignite. But outages had the potential to wreak havoc and could cost the company dearly. As Xignite’s client base grew, it was more important than ever to reduce downtime. Qin had to find a way to reliably scale the business’ usage of Redis while mitigating the risk of downtime or data loss.
About The Customer
Based in the Silicon Valley, Xignite was recently named one of the ten coolest brands in banking. Xignite’s clients include more than 1,000 financial services, media and software companies from disruptive fintech firms, such as Betterment, FutureAdvisor, Motif Investing, Personal Capital, Robinhood, StockTwits, Wealthfront and Yodlee, to leading financial institutions, exchanges and market data vendors including, NASDAQ OMX, SIX Financial Information and BMO. Xignite, Inc. provides cloud-based financial market data APIs to help emerging companies and established enterprises deliver real-time and reference financial market data to their digital assets, such as websites and apps. Redis is a critical technology layer for Xignite, powering high volume market data delivery with extremely low latencies. Xignite used Redis Labs Enterprise Cluster (RLEC) to enhance the availability of its Redis datasets with real-time auto-failover. RLEC also minimized the company’s operational costs through automated scaling and more efficient use of its hardware.
The Solution
Open Source Redis is used at Xignite, in particular to power its market data cloud platform with lightning fast access to requested market data, for complex computations close to the data with Lua scripts, and for powering publisher/subscriber interfaces. Redis needed to be always on and always available. Xignite evaluated several options to avoid downtime, including open source Redis and alternate Redis services, before testing Redis Labs. With these other approaches, the team found that downtime often required time and effort to resolve, but more importantly, loss of service to clients for up to an hour could really impact their business. On testing Redis Labs Enterprise Cluster (RLEC), they found it could help them scale their Redis easily on the same server or to multiple instances without performance impact or downtime. Not only could RLEC provide real-time, instantaneous failover, it did so while continuing to support all Redis commands and functionality such as key expiration. Qin said, “We ran RLEC in house, installed it, tried it, and the auto-failover just worked!” While other services failed to shield Xignite from downtime, Redis Labs easily provides scalability and automatic failover. Also, when using replication with alternate services, Xignite found that it no longer had access to all Redis functionality. Other services were also quite expensive and inefficient in their usage of server capacity. RLEC empowered Xignite to meet its customers’ needs and freed them from the operational costs associated with managing its vital Redis datasets.
Operational Impact
Quantitative Benefit
Related Case Studies.
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.”
