Traditional data warehousing systems are seen as silos at the end of the data processing pipeline. Over the last years Amazon Redshift has become the largest data warehousing system in the cloud with our customers storing tremendous amounts of data in it. In the recent time, data processing for analytics started to evolve again due to readily available cost-effective storage of data in S3.
In this talk, we will share our perspective on the evolution of the cloud data warehousing system from tightly integrated storage and compute to being able to process exabytes of data every month. In addition, we will talk about the great flexibility of Redshift to elastically scale on different dimensions to cater to different needs for dynamically changing throughput and storage requirements.