| Don't worry too much about this tweet, my guess is that the author wanted to express a strong opinion to provoke a reaction form a certain audience. Once you reach a large scale, relational databases start being a problem for availability and replication of data across different availability zones. Operations become complicated (you have replication chains, master/slave setups, etc.) If your data is relatively simple and doesn't require a lot of relations and foreign keys, then something like Cassandra can save a lot of headaches. Btw, a common trick to make a relational database perform at scale by limiting joins is to "flatten data", i.e. replicate data across different tables to avoid joining them. Finally, don't let yourself be fooled by anyone who claims they know "the better option." There is no better option. There is only a better option for a particular use case you're looking at, given the specific constraints at hands. That's what engineering is about, including software engineering. If you want to learn more about designing storage systems by constraints, I recommend that you read the 2007 Dynamo paper from Amazon, and in particular section 2.3 "Design Considerations". Below is a link, you can easily find a PDF online if you need. https://www.allthingsdistributed.com/2007/10/amazons_dynamo.... |