Amazon Redshift: a fast, scalable and easy to use data warehouse service
February 06, 2018
Amazon Redshift: a fast, scalable and easy to use data warehouse service
Score 9 out of 10
Vetted Review
Verified User
Overall Satisfaction with Amazon Redshift
We use Amazon Redshift as our data warehouse. We store our most used datasets on Redshift. Some of the data transformations are also made on Redshift but we try to avoid to do the heavy transformation there. Our dashboarding tool sits on top of Redshift and runs queries on every dashboard load. Analysts are using Redshift all day as the main source of data. Data savvy engineers and product managers have read access.
- It is easy to use. SQL is one of the easiest languages to learn.
- Fast. Especially if you use an SSD cluster.
- Scalable. If you need more space for your data or want faster results you can add more nodes.
- It is PostgreSQL. I miss some commands and procedural features.
- It is perfect for analytics purposes, but not fast enough for web apps.
- Too expensive for ETL processing.
- Amazon Redshift is our main data source. We use it for almost every analysis we made. These analyses are driving our decisions and strategy.
- Prezi is a data-driven company. Every decision we make is based on an analyses or a dashboard using datasets on Redshift.
Prezi is using AWS so Amazon Redshift was the obvious choice. It is fast, scalable and easy to use. Supplemented with Spark and Hive I'm completely satisfied using Redhsift. Sometimes I miss commands I used earlier on MS and Oracle SQL and the lack of procedural features is also negative.