A database is an organized collection of data, stored and retrieved digitally from a remote or local computer system. Databases can be huge and complex, and such databases are developed using fixed design and modeling strategies.

DBMS stands for Database Management System. DBMS is a system software accountable for the creation, retrieval, updation, and management of the database. It ensure that our data is consistent, organized, and is simply available by helping as an interface between the database and its end-users or application software.

RDBMS stands for Relational Database Management System. The major difference here, compared to DBMS, is that RDBMS supplies data in the form of a collection of tables, and relations can be cleared between the common fields of these tables. Most of the modern database management systems like MySQL, Microsoft SQL Server, Oracle, IBM DB2, and Amazon Redshift are mostly based on RDBMS.

SQL stands for Structured Query Language. It is the typical language for relational database management systems. It is particularly useful in handling organized data comprised of entities (variables) and dealings between different entities of the data.

SQL is a typical language for retrieve and manipulating structured databases. On the contrary, MySQL is a relational database management system, like as SQL Server, Oracle or IBM DB2, that is used to handle SQL databases.

A table is like an organized collection of data stored in the form of rows and columns. Columns can be mentioned as vertical and rows as horizontal. The columns in a table are known as fields while the rows can be declared to as records.

As explained on top, the difference can be broken down into three small factors –

• Clustered index changes the way records are stored in a database based on the indexed column. A non-clustered index create a divide entity within the table which references the original table.
• Clustered index is used for easy and speedy recovery of data from the database, whereas, fetching records from the non-clustered index is comparatively slower.
• In SQL, a table can have a single clustered index while it can have multiple non-clustered indexes.

Data Integrity is the promise of accuracy and constancy of data over its entire life-cycle and is a serious aspect of the design, implementation, and practice of any system which stores, processes, or retrieves data. It also defines reliability constraints to implement business rules on the data when it is entered into an application or a database.

A query is like a request for data or information from a database table or combination of tables. A database query could be moreover a select query or an action query.

SELECT operator in SQL is used to choose data from a database. The data return is stored in a result table, called the result-set.

Normalization represent the way of organizing structured data in the database proficiently. It include the creation of tables, establishing relationships between them, and major rules for those relationships. Inconsistency and redundancy can be kept back in check based on these rules, hence, adding flexibility to the database.

Denormalization is the opposite process of normalization, where the normalized schema is converted into a schema that has unneeded information. The performance is better by using redundancy and keeping the redundant data reliable. The cause for performing denormalization is the overheads produced in the query processor by an over-normalized structure.

If a table is dropped, all things linked with the tables are dropped as well. This includes – the relationships clear on the table with other tables, the integrity checks and constraints, access privileges and other grant that the table has. To generate and use the table again in its original form, all these relations, checks, constraints, privileges and relationships needed to be redefined. However, if a table is shortened, none of the above problems exist and the table retains its unique structure.

The TRUNCATE command is used to remove all the rows from the table and to free the space containing the table.

The DELETE command deletes only the rows from the table based on the state given in the where clause or deletes all the rows from the table if no condition is particularly specified. But it does not free the space contains the table.