Very good, but requires engg tuning
December 19, 2022
Very good, but requires engg tuning
Score 7 out of 10
Vetted Review
Verified User
Overall Satisfaction with Amazon Redshift
I use it as the data warehouse of our clients. I use it to build data transformations of user activity logs to ML features. I use the sql workbench to explore datasets and understand data schemas. Post that, I generally connect to the warehouse either through dbt or from jupyter notebooks.
Pros
- Seamlessly integrates with the data in s3
- Workbench provides useful way to query the tables within aws console
- Postgres flavor of sql gives powerful capabilities such as window functions
Cons
- Json support in sql is very limited.
- Array type columns are missing. They are by default converted to strings
- Sql workbench often goes unresponsive. I have to reload for the queries to run
- A search option in the sql workbench would be great, which let's users search the whole db for a match on columns, tables etc
- Central data store
- Gels well with aws ecosystem
- Data connectors
- Provides as the compute engine for the data transformations, helping the analytics stack
- Helps ML Products
Biggest advantage of Amazon Redshift is it's part of the aws ecosystem. When tuned well it is also very cheap compared to something like Snowflake. And compared to spark or databricks, Amazon Redshift is a solid warehouse that's well suited for tabular data. We use it for user logs, which is a very common usecase.
Do you think Amazon Redshift delivers good value for the price?
Yes
Are you happy with Amazon Redshift's feature set?
No
Did Amazon Redshift live up to sales and marketing promises?
I wasn't involved with the selection/purchase process
Did implementation of Amazon Redshift go as expected?
I wasn't involved with the implementation phase
Would you buy Amazon Redshift again?
No
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