Bridging the gap, OLTP and Real-Time Analytics in a Big Data World
Big Data is often created by high-volume feeds of incoming state that remains mutable, possibly indefinitely. It's a poor fit for traditional OLTP databases due to the volume involved and it's a poor fit for analytic databases due to the emphasis on mutable state and point queries. Both types of databases are ultimately necessary because the ideal storage layout for a given data set is determined by the queries you need to execute efficiently.
Over the past few years, several solutions have cropped up to solve this problem either by bridging specialized systems together or creating new systems that attempt to be a one-size-fits-all solution to OLTP and analytics.
This presentation will give an overview of OLTP-oriented databases (Postgres, MySQL, VoltDB), hybrid OLTP and OLAP (HBase, Cassandra, MongoDB), and OLAP (Vertica, Netezza, Hadoop), and how they can be used exclusively or together to satisfy mixed OLTP/OLAP workload at 'Big Data' scale.
Ryan Betts is CTO at VoltDB. He was one of the initial developers of VoltDB's commercial product, and values his unique opportunity to closely collaborate with customers, partners and prospects to understand their data management needs and help them to realize the business value of VoltDB and related technologies.
Prior to joining VoltDB in 2008, Ryan was a software engineer at IBM. During a four-and-a-half year tenure, he was responsible for implementing device configuration and monitoring as well as Web service management.
Before IBM, Ryan was a software engineer at Lucent Technologies for five years. In that role, he played an integral part in the implementation of an automation framework for acceptance testing of Frame Relay, ATM and IP services, as well as a high-availability upgrade capability and several internal components related to device provisioning. Ryan is an alumnus of Worcester Polytechnic Institute.