Amazon RDS vs Amazon Redshift

• For engineers with experience managing databases, setup is simple. And for the uninitiated, the RDS console interface becomes intuitive with some practice.
• Not having the maintain the underlying infrastructure is a great benefit of using RDS. Patching and backups can be scheduled from the console and from then on are pretty much automated.
• Right-sizing the DB instance to perform optimally with an application can be a very simple procedure. If a DB instance is not struggling to keep up, the instance size can be scaled up with just a few clicks.
• Baseline configurations are generally sane for most RDS instances. This allows novice developers and engineers to get the most out of the service without being a complete database administrator.

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• Redshift is fully managed. Small teams do not have the resources to maintain a cluster. CloudWatch metrics are provided out-of-the-box, and it is easy to configure alarms.
• Redshift's console allows you to easily inspect and manage queries, and manage the performance of the cluster.
• Redshift is ubiquitous; many products (e.g., ETL services) integrate with it out-of-the-box.
• Writing .csvs to S3 and querying them through Redshift Spectrum is convenient.

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• There should be a proper listing of all parameter groups alongside the instances that they are attached to. This would help to see which instances would be affected if a parameter group is changed.
• RDS should allow SUPER privilege to the master user. A few advanced tasks(like getting a physical backup using MySQL Enterprise Backup) fail because SUPER privilege is not available for the master user.
• A few parameters are not modifiable in the parameter groups and the access to the server filesystem is not given. This should not be the case because as an advanced user, you might want to understand things a little deeper.

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• It could benefit from adding data integrity and programming tools common to other database management systems.
• Amazon Redshift is based on PostgreSQL 8.0.2. That version of PostgreSQL was released in December 2006. While PostgreSQL was much improved since then, the new features were not implemented in Redshift. Many basic features are missing from it.
• Primary keys can be declared but not enforced. Referential integrity (foreign keys) can be declared but not enforced. UNIQUE and CHECK constraints are not supported and cannot be declared.
• IDENTITY can be declared on a column, and Redshift will put unique values into it. However: IDENTITY values in the newly inserted rows won’t be incremental or sequential. To implement a sequential number, you need to write your own custom code.
• There are no stored procedures in Redshift. We are writing SQL script files, and then parsing and running them one statement at a time from a Python program. This also enabled us to implement execution-time error logging.
• In SQL scripts, to check for the row count of affected rows, a complicated join query against some system tables or views has to be executed.
• Data Control Language (DCL) does not exist. No statements like IF, WHILE, DO, RAISERROR, etc.
• On performance of views… Views do not “pass-through” a query parameter which is a potential problem for performance.
• When selecting against a view with the WHERE clause outside of the view, the inner query of the view will be executed first without consideration for the WHERE clause, and only then the WHERE clause will be applied.
• Certain clauses of SQL work many times faster than other clauses. So be careful and test your statements for performance earlier rather than later, especially if working with a large data set.
• There was a situation when DELETE FROM JOIN was unacceptably slow. Replacing JOIN with the USING clause made DELETE instantaneous.

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• Switching back to RDS from Redshift has made my BI Dashboards much more performant (though again, we're not dealing with data in the magnitudes that justify the Redshift toolset).
• It has decreased our tech debt. Engineering has been much more straight forward.
• Our uptime has been improved by removing unnecessary data migration processes.

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• Redshift has had a very positive impact on our business. It has been used to provide analytics on marketing campaigns to boost revenue.
• Redshift is instrumental in our payment collection business processes. It powers everything from who gets called to who gets sent collection emails.

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