Redshift is SUPER; a More Flexible Cloud Data Warehouse Design
Cloud data warehouses, such as Redshift and Snowflake, are employed to deliver massive analytical throughput, allowing fast query performance on terabytes or even petabytes of data. To accomplish this, it’s typically thought that the data is stored in tightly defined schemas to allow the underlying engines to perform at the speeds that they advertise. However, during this talk, we’ll explore one way that semi-structured data can be stored and manipulated to enable a more flexible data model while still preserving as much performance as possible.
Folks will benefit most from this talk if they have experience designing and building databases. We'll be discussing column layout, showing demonstrations of SQL, and hopping in and out of the cloud. Experience with AWS and Redshift will make the talk especially applicable, but having any database background will be a big help.
- Learn how to use the SUPER datatype within Redshift to performantly work with semi structured data
- Understand a key use case for materialized views within a cloud data warehouse
- Gain a better understanding of how cloud data warehousing differ from from more traditional database technologies