Converging Operational & Data Warehousing Workloads in One Distributed System
Trading systems are faster and generating larger volumes of distributed data. This data complexity hinders timely insights on global risk as well as portfolio management.
This session will discuss the latest innovation in data management, and how utilizing a distributed and scalable converged database can optimize transactional and analytical workloads.
We will discuss the technical impact of real-time data pipelines and scalable SQL in a distributed computing platform that is designed for addressing challenging financial application scenarios.
We will include live demos of large scale data (several billion rows) that is processing on Volume Weighted Average Price (VWAP) and real-time image recognition.
Nikita Shamgunov is CEO and co-founder of MemSQL, the real-time data warehouse you can run anywhere.
Prior to co-founding MemSQL, Nikita worked on core infrastructure systems at Facebook. He has also served as a senior database engineer at Microsoft SQL Server for more than half a decade. Nikita holds a bachelor's, master's and doctorate in computer science, has been awarded several patents and was a world medalist in ACM programming contests.