Financial analytics platforms face unprecedented data challenges, processing millions of transactions while delivering real-time insights to traders, risk managers, and compliance teams. Open source distributed databases have emerged as the backbone of modern FinTech analytics, enabling organizations to scale cost-effectively while maintaining full control over their data architecture.
This presentation explores how open source technologies like Apache Cassandra, PostgreSQL with Citus, and ClickHouse power financial analytics through strategic sharding, replication, and consistency models. We’ll examine how leading financial institutions leverage these tools to handle 65,000+ transactions per second during peak trading periods while maintaining sub-millisecond query performance for real-time risk assessment and fraud detection.
Key topics include horizontal scaling strategies for multi-terabyte financial datasets, implementing cross-region replication for regulatory compliance, and balancing consistency requirements between transactional accuracy and analytical responsiveness. Through real-world case studies, attendees will discover how open source database architectures enable sophisticated financial analytics—from high-frequency trading algorithms to regulatory reporting pipelines—while reducing infrastructure costs and avoiding vendor lock-in.
Whether you’re building trading platforms, risk management systems, or compliance dashboards, this talk provides practical insights into architecting scalable, fault-tolerant analytics infrastructure using proven open source technologies that power today’s most demanding financial applications.