The question I have is schema updates. The biggest pain I have had with things like Mongo is dealing with old data records.<p>Use case example for Uber:<p>1. In 2011, a driver joined. They made a bunch of trips<p>2. In 2012, Uber added more detail about the trip. Information not collected for the 2011 trips.<p>3. And so on, each year there are &#x27;just a few changes&#x27;<p>Given the above:<p>In 2016, Uber want to run a query to reward all drivers based on some piece of information that was only present in 2014 on.<p>At this point the historical trip information from 2011 is in a significantly different format than in 2016.<p>In a RDB, at least the old columns are there - or if the db was migrated to a new schema ( a pain ) the issue of the missing fields was addressed.<p>But dealing with data in old formats was an Uber pain. And the lack of visibility into <i>just</i> knowing the schema used to generate that JSON object is a PITA.<p>God forbid if you had <i>new</i> code that never even knew about the old 2011 format.<p>Lastly, what happens if a bug slips through and some JSON field is missing, has odd spelling ( capitalization wrong ), etc.<p>I would love to hear about how old data is handled in schemaless.<p>My experience with MongoDB was less than pleasant.