I’m genuinely happy with Redshift for data warehousing purposes. For this I mean not-transactional data store. I don’t want to use the term OLTP or OLAP as it puts it in a purist’s camp. Sometimes I store 3NF normalized data and many times a flattened denormalized very large fact table and often times a model similar to star schema. I don’t have to worry about building indexes anymore, which was a real chore with row-store databases like Oracle, MySQL, SQL Server, or PostgreSql. MPP column-store databases have really been a game-changer for the enterprise. We’re talking billions of rows of data easily handled in the query plan.
I have always been a huge fan of Redshift, which extends to Anurag Gupta and the team that delivered it. Redshift has always struck me as one of the real breakthrough products the history of analytic databases. It collapsed deploying data warehouses from months to about 20 minutes.
It's great to see the current team is on the move again, as the original ParAccel architecture did not scale very well. There was an excellent talk on Redshift in Andy Pavlo's Vaccination Database Tech Talks, 2nd Dose. [0] It's by Ippokratis Pandis and worth a view. It covers a lot of the recent improvements, which are likely to disappoint the many critics who have counted Redshift out. (Prematurely in my opinion.)
