>a phenomenon of people finding SQL 'too complex' and moving to noSQL? Fyi... the "SQL vs noSQL" means at least 2 different ideas and some of your replies are

>a phenomenon of people finding SQL 'too complex' and moving to noSQL? Fyi... the "SQL vs noSQL" means at least 2 different ideas and some of your replies are highlighting one aspect but not the other. 1) "SQL vs noSQL" can mean "SQL syntax (e.g. joins) vs object syntax to save/retrieve documents (e.g. Javascript JSON/BSON)" . This is probably the main driver of MongoDB adoption. (They don't care about Mongodb's scaling aspect; they just like the easier syntax.) The counterpoint to this idea is that "people are using terrible db engines like MongoDB because they are unwilling to learn SQL syntax." 2) "SQL vs noSQL" can mean "OLTP RDBMS engine (e.g. MySQL/Postgre/Oracle) vs distributed db engine (e.g. Hbase/Cassandra/etc)". The counterpoint to this idea is that "people are deploying to distributed db engines when their use case actually fits in a 1-node RDBMS engine." From your wording, it looks like you're talking about #1. To that point, many programmers don't like the compexity of 10-way joins of a dozen normalized tables to reconstruct a customer data entry screen. With a document-oriented noSQL db, you just retrieve the entire denormalized "document" with no joins. However, there are tradeoffs to the "easier" noSQL engine such as performance.