1 00:00:06,964 --> 00:00:10,089 - Alright so let's talk about Amazon Redshift. 2 00:00:10,089 --> 00:00:14,256 Amazon Redshift is Amazon's petabyte scale data warehouse. 3 00:00:16,824 --> 00:00:19,184 Just like RDS, it's fully managed. 4 00:00:19,184 --> 00:00:22,517 It is based on a fork of Postgres 8.0.2. 5 00:00:25,845 --> 00:00:28,892 Very much so as a result, it is SQL compliant 6 00:00:28,892 --> 00:00:31,469 so you can connect to your Redshift cluster 7 00:00:31,469 --> 00:00:34,389 with all of the drivers that you're used to using. 8 00:00:34,389 --> 00:00:36,964 JDBC and ODBC drivers. 9 00:00:36,964 --> 00:00:41,102 And run SQL queries that you have been running in Postgres. 10 00:00:41,102 --> 00:00:42,352 Now under the hood, 11 00:00:42,352 --> 00:00:44,895 Redshift is a clustered service 12 00:00:44,895 --> 00:00:47,131 so it makes use of multiple nodes. 13 00:00:47,131 --> 00:00:49,705 You get to choose how many nodes you want 14 00:00:49,705 --> 00:00:52,533 and based on those number of nodes 15 00:00:52,533 --> 00:00:55,806 will also determine the amount of storage 16 00:00:55,806 --> 00:00:57,910 that your cluster will receive. 17 00:00:57,910 --> 00:01:01,181 And Redshift uses some really interesting technologies 18 00:01:01,181 --> 00:01:02,570 developed by Amazon 19 00:01:02,570 --> 00:01:06,737 to run these queries in parallel across those nodes 20 00:01:07,710 --> 00:01:10,372 across very large data sets. 21 00:01:10,372 --> 00:01:14,372 So these are ideal for OLAP and BI applications. 22 00:01:16,006 --> 00:01:20,852 Amazon Redshift fulfills a really interesting place 23 00:01:20,852 --> 00:01:22,504 within Amazon Web Services 24 00:01:22,504 --> 00:01:25,708 providing analytics and business intelligence 25 00:01:25,708 --> 00:01:28,452 at a vast amount of scale. 26 00:01:28,452 --> 00:01:32,012 So again, Amazon Redshift fully managed, just like RDS, 27 00:01:32,012 --> 00:01:35,512 and it is a petabyte scale data warehouse.