Talks
Bulk data processing and PostgreSQL thingy
Conference (INTERMEDIATE level)
Room E
This talk dives into the real-world challenges of handling large-scale data processing in a banking environment, with a focus on PostgreSQL, Hibernate, and data persistence best practices. We’ll explore methods for managing high-throughput systems, where performance and reliability are paramount.

Key topics include Hibernate's StatelessSession for batch processing, Chronicle API integration to tackle long-running transactions. We’ll also discuss strategies for batch identifier generation and streaming large datasets efficiently, drawing on lessons learned from building data integration solutions for financial products. We will cover about pitfalls about fetching as well.

Attendees will come away with practical tips on reducing database load, improving data consistency, and scaling PostgreSQL-backed systems. Whether you’re handling high volumes of data, designing scalable architecture, or looking to deepen your database knowledge, this session offers insights that can be applied directly to your projects.
Yingkun Bai
Swissquote S.A.
Yingkun is a Senior Software Engineer with extensive expertise in data integration, high-performance systems, and database optimization for large-scale data processing in the banking sector.

Currently, Yingkun leads a team responsible for integrating provider data and managing the company’s universe of tradable products, where they implement advanced techniques to ensure efficient data processing and delivery. A passionate advocate for best practices in Data Persistence technologies and system architecture.

Yingkun's recent work includes utilizing the Chronicle API to overcome long-running transaction challenges in PostgreSQL and sharing insights on handling large-scale data transformations. She is excited to bring practical tips and lessons learned from real-world applications to the conference audience, helping others optimize and scale their own systems.