RDBMs may not scale as well as let's say something like Cassandra, but as long as you don't need the scaling properties of Cassandra they make your life so much easier.

I have a feeling that premature scaling is a version of premature optimization. You probably don't have big data. And you probably don't need a massively scalable, distributed system. So, don't try to do it. Just don't.

"Those who refuse to study history are condemned to repeat it"

People like Jim Gray, Mike Stonebraker, et al. were/are not dummies.

"Those who ignore Codd are condemned to learn Codd, forcefully".- Codd's Law

Adapted to DBs.

The simple fact that I know the data I read from the datastore is consistent with my rules, is enough for me to stay on RDBMS. I've encountered enough bugs and failures to not trust a schema enforced in my data layer code.

Posts like this are annoying and completely stupid.

NoSQL databases encapsulates a wide variety of data stores including Key Value (Riak), BigTable (Cassandra), Document (MongoDB), Time Series (InfluxDB), In Memory Grid (Ignite) and dozens and dozens of others that blur the already grey lines. Many of which are strongly consistent (negating your consistency point). So your experience with one does not at all translate to other data stores.

The equivalent of what you're saying is "PHP sucks therefore all programming languages suck".

I think the point of the post is valid: it can be hard to work with a schemaless datastore. I think Cassandra is the only one you listed that supports type enforcements.

NoSQL != Schemaless.

That mantra hasn't been true for a number of years now. Especially since the big trend has been exposing SQL layers in front of NoSQL databases. For example Phoenix in front of HBase.

And SQL as well as all know requires data types to be usable.

Just to explain - I was going to write mongo originally but then decided to go more general. I evidentially went too general with my terminology. I've used mongo since the early days and I've also worked on projects that have used everything from neo4j and redis to oracle as the primary data store.

There are a bunch of things that made me nervous about mongo as the primary db. Data consistency was the main one and, like the author of the post - migrating away from mongo was hard almost entirely because of data inconsistency that had developed over the course of a couple of years.

Querying was also harder on an ad-hoc basis. With a relational db there are generally just a couple of recommended ways of modelling your data. But once you do that, it's easy to query after the fact. Or to add new stuff. With mongo I felt like I was constantly making a trade off that I would have to accept at querying time.

MongoDB has been able to do this (optionally) since v3.2.

Isn't it more like saying all loosely typed languages suck? Your analogy is what's really completely stupid.