Google BigQuery is a serverless, scalable, and cost effective cloud data warehouse. Having evolved from internal Google infrastructure (Dremel), BigQuery is unique in a number of dimensions. In this talk, we provide a look at some of the key architectural aspects of BigQuery and how it provides a true serverless and multi-tenant warehousing solution to customers. We then provide an overview of recent features such as BQML and the embedded BI engine that build on these architectural foundations that allow BigQuery to provide a unique data warehousing solution to customers.

Important: Food or drinks will not be permitted in the room during the talk.

Bio:
Dr. Justin Levandoski works on BigQuery, Google Cloud's native data warehouse. Prior to Google, he was a principal engineer at Amazon Web Services (AWS), where he worked on Amazon Aurora, a cloud-native operational database system. Before that, he was a member of the database group at Microsoft Research, where he worked on main-memory databases, database support for new hardware platforms, transaction processing, and cloud computing. His research was commercialized in a number of Microsoft products, including the SQL Server Hekaton main-memory database engine, Azure CosmosDB, and bing. He was an associate editor for IEEE TKDE and has served as area chair for SIGMOD 2019, SIGMOD 2016 and ICDE 2016.

More Info: https://www.pdl.cmu.edu/SDI/index.shtml