Apache Ignite as a Hybrid Transactional-Analytical Processing Solution at a Large Investment Bank
Today, at BNP Paribas, our Apache Ignite cluster is running successfully in production and is being used globally across all divisions of our corporate investment bank. Ignite uses 600 CPU cores and 9 TBs of RAM to handle a steadily increasing number of users, multiple complex hybrid transactional-analytical operations, and events that come from various data sources. In this session, we share our experience in designing, building, and optimizing a hybrid transactional-analytical processing (HTAP) solution that is powered by Ignite and that enables BNP Paribas to make key business decisions in real time. We cover the following: - The reasons that we chose Apache Ignite as a data analysis tool - Best practices and tradeoffs for designing an HTAP solution that analyzes multidimensional historical and real-time datasets - Tips and tricks for using Ignite compute, SQL, key-value, and streaming APIs to implement complex algorithms and operations, including trading strategies - Optimization tactics for Ignite clusters with native persistence
I am a software engineer with over 15 years of experience, a technologist and entrepreneur. Over the past few years, I focused mainly on the finance industry, working on data analytics and distributed computing softwares.