Talk:Amazon Redshift

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Wiki Education Foundation-supported course assignment

This article was the subject of a Wiki Education Foundation-supported course assignment, between 25 August 2020 and 10 December 2020. Further details are available on the course page. Student editor(s): JSchrum1. Peer reviewers: Hbaranowski, Sxl79, Rfr5240.

Above undated message substituted from Template:Dashboard.wikiedu.org assignment by PrimeBOT (talk) 17:11, 17 January 2022 (UTC)[reply]

data warehouse?

It would be nice if this article could say more about Redshift's scaling strategies. Is it a relatively straightforward Postgres fork that handles Postgres-sized workloads? Somehow I had thought that it was petabyte but used SQL, so

   SELECT SUM(foo) ORDER BY baz ASC GROUP BY whatever;

could be spun off into map-reduce jobs on 100s of machines processing billions of records, etc. Google F1 is something like that and I thought Redshift was similar. 50.0.136.56 (talk) 05:22, 8 April 2017 (UTC)[reply]

Adding sources below: ^[1] ^[2] JSchrum1 (talk) 05:28, 21 September 2020 (UTC)[reply]

Adding the following paragraph to help answer question on how SQL commands are sped up: Redshift uses parallel-processing and compression to decrease command execution time. This allows Redshift to perform operations on billions of rows at once. This also makes Redshift useful for storing and analyzing large quantities of data from logs or live feeds through a source such as Amazon Kinesis Data Firehose. -JSchrum1 (talk) 21:31, 1 October 2020 (UTC)[reply]

References

[1] ttps://aws.amazon.com/redshift/faqs/

[2] ttps://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Welcome.html

[1]

[2]