As a SQL developer, what are the differences between RDS and redshift that I'll notice?

Question

I have solid experience with redshift (primarily SQL development) since I've been migrating our objects from SQL Server to redshift for the past year. In a nutshell, I've had to take t-sql (in the form of bare sql, SPs, views and functions) and rewrite it so that it runs in redshift. Aside from a few exceptions, the SQL I write for redshift (olap) is very similar to t-sql (rdbms).

Amazon also has RDS, which is an RDBMS.

My question: from my perspective where I only write SQL, is there any significant differences (eg. not having indexes) between RDS and redshift? I don't deal with scalability, pricing, maintenance, storage or any other admin stuff. I simply open SQL Workbench/J, connect, and write sql.

Answer 1

While they both use SQL, Amazon RDS and Redshift are two very different things.

Amazon RDS is a traditional SQL database hosted on AWS. It supports IBM Db2, MariaDB, Microsoft SQL Server, MySQL, Oracle Database, and PostgreSQL. You get high availability, backups, and so on.

Amazon Redshift is its own thing. It's a column-oriented database for Big Data, Data Warehousing, Business Intelligence, and Online Analytical Processing. It began as a fork of PostgreSQL 8 and has diverged significantly since.

Because it addresses very different requirements, the specialized data storage schema and query execution engine that Amazon Redshift uses are completely different from the PostgreSQL implementation.

Column-oriented databases are structured and optimized very differently than the row-based databases you're used to. There's no secondary indexes, no table partitioning, fewer constraints, no triggers, no sequences. Queries are automatically distributed to compute nodes.

See the Amazon Redshift SQL Reference and Amazon Redshift and PostgreSQL for details.