Like all things in tech, it depends. I agree with you that most startups will never see data that will not fit in memory. Remember http://yourdatafitsinram.com

Like all things in tech, it depends. I agree with you that most startups will never see data that will not fit in memory. Remember http://yourdatafitsinram.com http://yourdatafitsinram.com ? Now, a data warehouse where you have a hoarde of Hadoop engineers slaving over 1000 node clusters is probably overkill unless you are a company like facebook or are in the data processing biz. However, some database management systems can be very complementary. For example, while you can do a majority of things with Postgres, some are not fun or easy to do. Have you ever set up postgis? I'd much rather make a geo index in MongoDB, do the geo queries I need and call it a day than spend a day setting up postgis. We find that MongoDB is great for providing the data our application needs at runtime. That being said, it's not as great when it comes time for us analyze it. We want SQL and all the business intelligence adapters that come with it. Yeah you could do a join with the aggregation framework in MongoDB 3.2 but it just isn't as fun.