Cesare Pautasso and Guy Pardon propose a way of implementing transactions over HTTP using REST and the Try-Confirm/Cancel protocol.
Michael Stonebraker compares how RDBMS, NoSQL and NewSQL support today’s big data transaction processing needs. He also introduces VoltDB, an in-memory NewSQL database.
Dave Farley and Martin Thompson discuss solutions for doing low-latency high throughput transactions based on the Disruptor concurrency pattern.
John Hugg discusses high volume transaction processing applications with high and low frequency profiles, and how VoltDB can be used for that purpose.
Richard Kreuter and Kyle Banker on how to avoid classical RDBMS transactional systems by using compensation mechanisms, transactional messaging or transactional procedures.
Cyprien Noel discusses distributed transactional memories along with ObjectFabric, a Java server based on eXtensible Software Transactional Memory, an OS library for concurrent and distributed apps.
Jags Ramnaraya presents SQLFire and how SQL can be used for modern data stores backing online highly scalable applications by using a different consistency model and sharing nothing persistence.
Martin Thompson and Michael Barker talk about building a HPC financial system handling over 100K tps at less than 1ms latency by having a new approach to infrastructure and software.
Bill Burke shows how to use REST to create interfaces to middleware services – messaging, transactions, workflow, security – in order to have RESTful enterprise SOA implementations.
Justin Sheehy explains the principles behind concurrent distributed systems: no global state, no ACID but rather BASE, no RPC but protocols over APIs, prepare for failure, degradation, measurement.
Gregor Hohpe of Google discusses software as connecting services and components, describes the constraints of connected systems design, and presents common design patterns to solve those constraints.
Our application runs over 10,000 sustained transactions per second with a rich model. The key? Modeling state transitions explicitly.