The basic rules of RDBMSs and SQL, which are critical for novices to comprehend, will be covered in this and subsequent articles.
RDBMS rules are designed to keep databases in relational architecture, which means that logical data structures like data tables, views, and indexes are kept distinct from physical storage structures.
Codd’s Rules:
Doctor Edgar F Codd proposed 12 regulations, but there are actually 13. From zero to twelve, the regulations are numbered. According to him, a database management system is entirely relational if it follows all twelve of his rules. Only a few databases have followed all eleven guidelines so far. His rules are called the Codd’s rules which are described below:
0. Foundation Rule:
Any relational database management system (RDBMS) that is proposed or promoted as such should be able to manage the stored data in its totality using its relational capabilities.
1. Rule of Information:
Data should be stored in the form of relations in relational databases. In relational database management systems, tables are relations. It is essential to save the value as an entity in the table cells, whether it be user-defined data or meta-data.
2. The Rule of Guaranteed Access:
The use of pointers to logically access data is strictly prohibited. Every atomic data object should be logically accessed by utilizing the name of the table, the primary key represented by a specific row value, and the column name represented by the attribute value.
3. Rule of Systematic Null Value Support:
In relational databases, null values are fully supported. They should all be regarded as missing information. Any data type is unaffected by null values. They are not to be confused with blanks, zeroes, or empty strings. Null values are often known as “inapplicable data” or “unknown information.”
4. Rule of Active and online relational Catalog:
The data about the database or the data about the data is referred to as “metadata” in the Database Management Systems terminology. ‘Data dictionary’ is the active online catalogue that stores the metadata. The so-called data dictionary is only accessible to authored users with the necessary permissions, and the query languages used to access the database should also be used to access the data in the data dictionary.
5. Rule of Comprehensive Data Sub-language
Integrity restrictions, views, data manipulations, transactions, and authorizations should all be defined in a single robust language. This criterion is broken if the database enables access to the aforementioned ones.
6. The Rule of Updating Views
The adjustments to their respective basis tables should be reflected in views, and vice versa. A view is a logical table that displays data that is constrained. Views make data readable but not editable in most cases. Data abstraction is aided by views.
7. Set level insertion, update, and deletion
The data should be retrievable, inserted, updated, and deleted in a single procedure.
8. Physical Data Independence
Physical storage and access mechanisms are logically segregated from batch and end-user processes.
9. The Rule of Logical Data Independence
Changes to the database schema can be made by batch and end-users without having to recreate the database or the applications built on it.
10. Integrity and Independence
Integrity constraints should be available in the data dictionary and stored as metadata rather than in the application code.
11. Rule of Distribution Independence
The Data Manipulation Language of the relational system should not be concerned about the physical data storage and no alterations should be required if the physical data is centralized or distributed.
12. Non-Subversion Rule.
Any row must adhere to the specified security and integrity limitations. There are no special privileges available.
Big Data and SQL 
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