“The RDM is semantically weak ... struggles with consistent granularity and has limitations at the property level... it has no concept of data flow ... it is an incomplete theory. Great for its time but needs something better now ... it uses ill defined and linguistically suspect labels ... it has no rules for semantic accuracy ... this just makes the RDM 1% of the truth ... the RDM should have solved this all by now ... but it has clearly not. You fail to see the reality of the failure of RDM in the real world ... this is your choice. I understand why you cling to it ... it is a most excellent theory that I respect greatly ... [but o]pen minds make progress...” 

“... the concept of a state group is indeed a missing modeling concept in relational/current data models...”

“Here two or more table[s] are related with each other. This is Database relationship. Database relationship is used a lot ... [in] relational database management systems ... shortly called RDBMS. Here is Join_data [sic] table and Interview_data table. For creating a relational database management system both of the table[s] must have a common field. Here Employee_ID is a common field ... Database relationship types: One-To-One relation, One-To-many relation, Many-to-many relation. Minimum one common field is essential in all the tables. The data type of common field and field size will be same in all the tables.”

“Traditional databases ... don't have a multi-model capability. Point is that richer data models are underused, relational data models are overused, and graph data models have so many advantages that shouldn't be ignored. Relational models, on the other hand, have wildly complex structures often with hundreds to thousands of tables. Each table then contains tens to hundreds of columns, arbitrarily constructed in each and every relational system. And just in case the situation wasn't complex enough, many of those columns are exist exclusively to manage uniqueness and provide connections to other tables. This Structure-FIrst approach produced the cascade of complexity from which we have struggled to recover ever since.”

“But if you still want to compare NOSQL databases with RDBMS, they primarily vary in
1. "normalization" where RDBMS contains normalized (upto certain degree) data and NOSQL based database contains non-normalized data;
2. RDBMS based databases are (I MUST say, generally and it isn't a criteria) fully ACID compliant while NOSQL databases are partially ACID compliant.
3. RDBMS are much slower and difficult to scale while NOSQL databases are much faster and easily scalable.
4. RDBMS normalization was very useful 50 years ago when cost of disk and memory was high, and computation power was limited. With the revolution in computing power, cheapest disk and memory availability has made RDBMS normalization a matter of joke - many people do not really understand why they need to normalize data in today's time.”

“Data modelling, star schema, snow flakes, data vault. Implementing virtual data warehouses (many stage to modify relationships). Normalisation (using a lot of surrogate keys) all for the sake of business reporting analytics. Reason a SQL DBMS approach columns rows is mandatory.”

--LinkedIn

“In our industry, there is a strong desire to put names on things. This is natural enough, given the amount of information that we have to classify and deal with in our work. To give something a name is to gain control over it, and this is not necessarily a bad thing. The problem is when the name takes the place of true understanding of the thing named. Discourse tends to be the bantering of names, without true understanding of the concepts involved.”