Real-time Trade Data Processing and Machine Learning at Giga-Scale with Hazelcast and FINOS Perspective

Explore cutting-edge solutions for real-time trade data processing and machine learning at giga-scale in this informative conference talk. Discover how Hazelcast, an open-source real-time data platform, can process billions of events per second with modest compute resources, and learn about the FINOS Perspective framework for real-time data visualization. Gain insights into architecting and building high-performance data processing applications that scale linearly, combining streaming trade data with reference and contextual data while supporting machine learning. Understand how unifying data-in-motion and data-at-rest with real-time ML opens new use-cases across front and back office operations. Follow along as the speakers demonstrate an end-to-end framework and example Trade application built on Hazelcast, and learn how to leverage SQL for querying Kafka topics and key-value data on in-memory data stores. Access to the GitHub sample application shown is provided for attendees to further explore and implement these innovative technologies in their own projects.