Real-Time Financial Data Architecture: Building Resilient Pipelines for High-Frequency Markets

About the Session

In today's financial markets, where milliseconds determine competitive advantage, traditional data architectures struggle to keep pace. This session presents a battle-tested framework for building resilient, high-performance data pipelines capable of processing hundreds of thousands of transactions per second with minimal latency. I'll showcase how our implementation unified diverse trading platform data through canonical schemas, while our enrichment layer seamlessly integrated multiple reference data streams to provide crucial contextual information. Our strategic approach to data storage using sharded Oracle databases dramatically improved query performance across complex financial datasets. The architecture's intelligent auto-scaling capabilities maintain consistent performance during market volatility, automatically adjusting resources during transaction volume spikes. Performance metrics demonstrate the system's exceptional throughput capacity and ability to handle unpredictable market surges without degradation. Results from our implementation include: exponential increases in transaction processing capacity, virtual elimination of unplanned downtime, significantly reduced per-transaction costs, and operational recovery times improved from hours to minutes. This practical session walks through the complete pipeline lifecycle—from initial data ingestion through enrichment and storage to analytical consumption—offering valuable insights for engineers and architects building high-performance financial data systems that must balance real-time processing with unpredictable market workloads.

Speaker

Anandan Dhanaraj

Vice President of Software Development at BNY Mellon