Scaled Risk embeds an event-driven framework that enables real-time capabilities as defined for financial applications. This paper explains how Scaled Risk leverages HBase to implement a fault-tolerant real-time bus with best performance and reliability.
The paper also explains why Kafka, which was considered as a good candidate for Scaled Risk’s internal bus, was finally retained only as an external component. Kafka has introduced a new approach for real-time and streaming data processing in the Hadoop ecosystem. Explaining Kafka is thus a good starting point for explaining the issue of Real-time data processing in financial applications.
IntoductionWhat is Kafka - Kafka innovations - Kafka in Hadoop worldScaled Risk internal real-time data processing - Business requirements for real-time processing - Scaled Risk real-time internal bus - Scaled Risk external data processing
About Scaled RiskScaled Risk develops, markets and supports a wide range of software to financial institutions. These next-generation solutions based on Big Data technologies cover all cases of application of Risk Management and Front Offices, position calculation, Trade Analytics and real-time fraud detection.