Amazon Redshift is a fast, fully managed, large-scale data warehouse solution that makes it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools. In this talk we are going to dive into Redshift’s architecture and talk about how we leverage fleet telemetry in order to prioritize the whole development process and to make Redshift achieve top of the line performance at any data scale and concurrency. For that, we are going to focus on two recently released features of Amazon Redshift: Redshift Spectrum enables running Redshift SQL queries against very large volumes of data in Amazon S3, often achieving higher performance than when processing data from local attached disks, while Redshift Concurrency Scaling adds in seconds transient capacity to running Redshift clusters to elastically handle heavy demand from concurrent users and queries.

Bio:
Ippokratis Pandis is a Senior Principal Engineer at Amazon Web Services, currently working on Amazon Redshift. Redshift is Amazon's fully managed, petabyte-scale data warehouse service. Ippokratis is the architect of the Redshift Spectrum and Redshift Concurrency Scaling features. Previously, Ippokratis has held positions as software engineer at Cloudera where he worked on the Impala SQL-on-Hadoop query engine, and as member of the research staff at the IBM Almaden Research Center. Ippokratis received his PhD from the ECE department at Carnegie Mellon University. He has served as PC chair of CloudDM 2016, DaMoN 2015 and DaMoN 2014 and he is currently the PC chair of HPTS 2019.