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Ryan Betts, Sr. Software Engineer, Volt DB

 Ryan  Betts

Ryan Betts is a Senior Software Engineer at VoltDB, Inc., where he has played a key role in the development of VoltDB’s core technologies including distributed transaction management, fault tolerance, cluster management and RESTful APIs. Previously, Ryan was a software engineer at IBM (via acquisition of DataPower) and Lucent Technologies (via acquisition of Ascend). He also earned a BS in Mathematics from Worcester Polytechnic Institute.

Presentation: "New-age Transactional Systems - Not Your Grandpa's OLTP"

Time: Wednesday 10:35 - 11:35

Location: Concordia

Abstract:

Most developers are familiar with the special requirements of high volume OLTP applications such as airline reservation systems and capital market ("tick") feeds - systems that process massive amounts of real-time data with "high 9s" availability and ACID-level consistency. Such extreme requirements demand highly specialized data infrastructures costing many millions of dollars.

Fueled by mobile computing, online gaming and interactive web applications, a new class of transactional systems is emerging. These systems have many characteristics of their traditional OLTP counterparts, including the need for guaranteed transactional consistency, but there are also important differences:

  • Time-to-implementation. Most new transactional systems must be built, tested and deployed in less than six months.
  • Deployed to cloud. Cloud deployments are increasingly common for all classes of new applications, and transactional systems are no exception.
  • Low cost profile. New transactional applications must be brought online at a fraction of the cost of traditional OLTP solutions.

In this presentation, we will discuss real-world applications of high volume transaction processing. We'll explore high- and low-frequency transaction profiles, as well as the need for real-time analytics. Importantly, we'll also discuss how high volume transactional solutions like VoltDB can be integrated into existing data infrastructures.