“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.”

“A relational database stores information in a structured format called a schema. This schema is defined according the rules of database normalization. These rules are meant to ensure the integrity of the data. The schema for a database is broken up into the objects such as tables and constraints. Tables hold your data and are broken down into rows. each row represents a single entity such as a person and has columns which define the attributes of the entity such as age. Constraints define limitations around the data. For example a check constraint might limit the range of valid dates in a datetime column. From there queries can be run to extract data from the database. These queries will often join multiple tables to pull data from them.”

“RDBMS stands for Relational Database Management System. RDBMS is the basis for SQL, and for all modern database systems like MS SQL Server, IBM DB2, Oracle, MySQL, and Microsoft Access. RDBMS store the data into collection of tables, which might be related by common fields (database table columns). RDBMS also provide relational operators to manipulate the data stored into the database tables. An important feature of RDBMS is that a single database can be spread across several tables. This differs from flat-file databases, in which each database is self-contained in a single table. The most popular data model in DBMS is the Relational Model. It is more scientific a model than others. This model is based on first-order predicate logic and defines a table as an n-ary relation. The main highlights of this model are:

• Data is stored in tables called relations.
• Relations can be normalized.
• In normalized relations, values saved are atomic values.
• Each row in a relation contains a unique value.
• Each column in a relation contains values from a same domain.”

“There is a lot of confusion when it comes to designing tables in SQL Server around whether to pluralize names or not. How do you choose whether to pluralize or not? If we want to store a list of people and their details do we use "Person", "Persons", "People" or "Peoples"? Some people will use "People" and some will use "Person", other persons or people would go for "Peoples" or "Persons". The defined standard is to go for non-plural because in a table we are storing a set of an entity and we name the table as the entity so if we want to store one or more people in a single entity or table, we store it or them in the “Person” table. If we stick to this then it makes other situations simpler and stops us having to think about how to pluralize a word, I have for example seen hierarchy pluralized as "hierarcys" [sic].

If we look at Relational Model of Data Large Shared Data Banks by none other than "E. F. Codd" who basically invented the relational database, the examples he gives are singular (supplier and component). If we then look at the ISO standard for naming things (11179-5: Naming and identification principles), this also says that singular names should be used "Nouns are used in singular form only".

For new projects or where you can easily change the name of entities then I would say you must use singular names, for older projects you’ll need to be a bit more pragmatic!”

--The.AgileSQL.Club

“...the theoretical awesomeness of relational algebra is kinda hard to intuitively relate back to your payroll or audit-log tables - the real power is the computed join ... it lets you dynamically fetch sets of data in the exact format that you need ... with any group of tables in the dataset. Unlike other data models, where the things you can fetch are typically fixed when you define your elements, and where relationships between data - if any - are statically defined in advance ... joins let you specify the relationships between objects (rows and tables in SQL-based relational databases) ... create queries and run them on your data without needing to write a lot of extra code beyond the SQL itself. This Ad Hoc Query capability ends up being hugely valuable when doing "secondary" business tasks in a big data world such as doing reporting and analytics, and is often hugely difficult to do in non-relational environments without a lot of extra code and often a specialized reporting schema.”

“Relational theory as applied to databases is that all data is connected to each other, keyed to each piece ... And with a SQL query [you can] create anything that can exist, as output.”

“...main so called power of RDBMs lies within ACID compliance. A transaction in a RDB is Atomic, Consistent, isolated, durable ... makes a database useful, unique, or I suppose powerful ... let's say you update or insert some new record, right in the middle power goes out, due to ACID compliance your transaction will not go through ... either the operation will complete or fail, nothing in between. [And RDBMSs are] tried, tested and true for almost 50 years.”