Start a data warehouse today with Redshift!
June 15, 2019

Start a data warehouse today with Redshift!

Anonymous | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source

Overall Satisfaction with Amazon Redshift

Redshift is being used by engineering for our data warehouse or data lake, if you will. It's part of our ETL pipeline, where the data is used to form dashboards and analytical queries across all of our initially segregated data. So it is kind of a source of truth linking data across the company. These dashboards are accessible across other departments in the organization. The data is consumed by everyone, not just engineers.
  • It's fast for data analytics across multiple columns.
  • Essentially, it's good for big datasets.
  • By using RedShift you're kind of married to using AWS's other services, e.g. Redash.
  • You need your data in the cloud.
  • No separate storage and computing.
  • No structured data types.
  • Doesn't scale easily.
  • Very positive for what it has done, providing a way to aggregate data sources.
  • It allows marketing to pull statistics across the consumer base that would not have been otherwise possible.
  • It allows actual analytics across the company, in an easily accessible manner.
We are currently on Redshift, because it was out before Snowflake. However, Snowflake looks promising. It's the new shiny toy that gives options that Redshift does not provide for. The big thing is that storage and compute can be scaled separately, whereas you cannot do that in Redshift. That's a big one. If you have enough data, it's worth it and should be cheaper.
It's definitely useable if you put time into it, but there are other solutions that are newer and easier to use. My example is Snowflake. I feel like they are a mature solution at this point and offer a level of usability that is not paralleled by Redshift. Even for smaller datasets, where is it more expensive, I feel like paying for ease of use is worth the cost.
Use Redshift for data warehouses, especially if your data is already in the cloud (AWS). It's great for large datasets, and fast too, even if your dataset is column heavy. It's less so for when you have a bunch of rows. All in all, it's a good starting point for any aspiring data warehouse, but there are other promising solutions too. E.g. Snowflake.