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.