Uri Cohen discusses several types of queues with their pros and cons used in financial and trading industries for highly parallelized data processing.
Frank Tarsillo , John Davies, Jon Vernon and Ari Zilka (moderator) discuss the technologies and architectures used these days to manage large amounts of sensitive data in top financial institutions.
James Spooner discusses the need to make good use of the underlying silicon using Dataflow computing and parallelism to improve throughput and latency for optimized data processing performance.
Andrew Stewart investigates the causes for so many bad models, especially in the financial sector, created by various teams including Agile ones.
Hanno Klein explains how AMQP is used by Deutsche Börse and where it fits within their strategy.
John Davies addresses some of the difficulties dealing with FIX, FpML, SWIFT and integration in financial services software industry, challenging some of the canonical models existing today.
Jonathan Felch discusses Groovy, its major features, using it in a financial project, the benefit of using dynamic and meta-programming features together, ending with what is not so great in Groovy.
Eoin Woods explains how Barclays Global Investors (BGI) designed Apex to meet the challenges it faces and the Java technologies which were chosen for an architecture with variations on standard J2EE.
Our application runs over 10,000 sustained transactions per second with a rich model. The key? Modeling state transitions explicitly.