> Instead, NoSQL systems like HBase, Cassandra, and MongoDB became fashionable as they marketed themselves as being scalable and easier to use HBase did not -

> Instead, NoSQL systems like HBase, Cassandra, and MongoDB became fashionable as they marketed themselves as being scalable and easier to use HBase did not - the project has always been very clear that they cater towards a very specific set of use cases - fast writes with little schema constraints, fast single-key and range/fuzzy lookups, not big ETL pipelines. Even during the rise of Hadoop (everything is a file... I mean file based!) and the subsequent absorption of that into the Public Cloud vendors, SQL has always been there, just wrapped in different tools. These days, someone else hosts it and it's now called Athena instead of Hive, but fundamentally the same thing and has been the same thing. Even Apache Sparks entire Dataset/Datframe interface yields SQL-like execution plans, exposing the same functions that an RDMBS would, just in Scala/Python/R.