We stored all of the data in the S3 bucket and would like to have it stored in a data warehouse, which is why we chose this database.
It would be very easy for us as an end-user, who would like to access the data, rather than draw it post-transformation and store it at a database level.
The TP transactions for the creation of the tables does very well.
It is quite simple to use and there are no issues with creating the tables.
The managing updates, deletes, and role-level change performance is very low. For example, while you are doing inserts, updates, deletes, and amalgamates, the performance is very, very poor.
If you want to query the database after you have a lot of terabytes of data, the load, performance-wise, is very low.
Looking at the performance of the query, querying the database, and especially with the amalgamates when it is getting updated, it is really poor.
We like this solution and have tried all of the native services; they were working quite well. The only concern about Redshift was managing the cluster, especially the EMR cluster. Our company policy was not to use EMR clusters, especially with the nodes failing. There were many instances of downtime happening. Essentially, there was too much data traffic.
The other drawback was the CDC, as we do not have any tools that can support it.
Creating the structure is easy on the DDL side, but after you create the table and you want to transform the data to store it in a database, the performance is poor.
It takes a lot of time to ingest and update the data. After you ingest the data and someone wants to fetch it in the table, it takes a lot of time performance-wise to return the results.
We have been using this solution for three months.
We are using the latest version.
There are issues with stability and it should be compared with Snowflake.
This solution is scalable. We scale up and scale down manually when we are required to, we do not have an automatic setup.
We have three or four people using this solution.
We have contacted technical support to give our opinion and recommendations or feedback and they agreed that it needs improvement.
Previously, we tried the Snowflake database, which works really well. The expectations were really good with the performance, also the DDL, DML operations on the processing of the data.
The initial setup is simple and we did not find it very complex at all.
The time it takes to deploy depends on how many tables you want to create, or how many tables will you merge the data with.
We are switching to Azure, although not because of the product or the services that we did not like. It's about AWS being competitors for logistic companies that we are working with. Also for security reasons, we do not know how secure the data is on the cloud.
If you are competitors then you don't know if the data can be accessed by your competitor, and the team can be looking at a demographic, which could impact your sales.
We have only just started using Redshift, but we are not really satisfied with it.
I would rate this solution a six out of ten.