Amazon Redshift Review
Updated April 02, 2021

Amazon Redshift Review

Arthur Zubarev | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User

Overall Satisfaction with Amazon Redshift

Amazon Redshift is a PostgreSQL based solution was seen as a drop-in replacement for several Postgres based databases (or schemas in Postgres parlance).
The eventual product: a Bill Inmon principles-based Data Warehouse served as a point or source of a single truth. It aided in decision making, historical outlooks and forecasting across various organizational verticals - the Finance, Marketing, and Medical Research. It was also possible to deliver data extracts to 3rd parties or visualize data on demand.
  • Data retrieval experience really gets improved.
  • In terms of database management, it is really a no management at all in AWS. There is no even an OS to take care or worry about.
  • Auto or on-demand scaling is nice.
  • Integrates quite well with other products within the AWS ecosystem.
  • The number of connections is too small, I think at around 50 are allowed in parallel. With some ETL and apps connecting all the time, this brings an undesired possibility to some users or tools being unable to connect.
  • Needs some tuning.
  • The logging part is almost nonexistent.
  • Can be quite costly in the long run as opposed to just RDS or on-prem/dedicated solutions.
  • Redshift as a solution is viable in case an enterprise wants a relatively uncomplicated relational data storage engine that is elastic and autonomous.
  • The costs are reasonable compared to other storage systems provided Redshift is capable to grow with your business and reduce administrative costs.
  • Redshift integrates well with many of the offerings within AWS and outside it. The programmability story is also good.
Azure SQL Database was discarded because of a less attractive licensing, costs, plus its integrates poorly with many of the Azure offerings as say Azure Data Factory - it is not a true ETL yet. Also, the rest of the tools used were of Open Source type and it did not look like a good fit for Azure.
AWS Aurora in Postgres mode could be easier to migrate, but it wasn't that much cheaper than Redshift, minus its limitations.
Snowflake looked like the most promising and yet modern data warehousing solution that is able to elastically autoscale and provision more connections than Redshift, but it wasn't in wide use and hard to experiment with (not a native AWS citizen and wasn't whitelisted in GCP back then).
Redshift won because most of the developers and analysts knew Postgres.
Redshift support is seamless. The system is MPP (distributed), so it is highly available, always backed up by AWS and you can also have read-only replicas (at a cost) which help overcome the number of connections issue.
Although, AWS looks like is not going to upgrade its storage engine to the newer version of Postgres which is a big pity.

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If the number of connections is expected to be low, but the amounts of data are large or projected to grow it is a good solutions especially if there is previous exposure to PostgreSQL. Speaking of Postgres, Redshift is based on several versions old releases of PostgreSQL so the developers would not be able to take advantage of some of the newer SQL language features. The queries need some fine-tuning still, indexing is not provided, but playing with sorting keys becomes necessary. Lastly, there is no notion of the Primary Key in Redshift so the business must be prepared to explain why duplication occurred (must be vigilant for).