Difference Between DBMS and RDBMS ?:


SQL Definition:

SQL is referred as Structured Query Language, a standard query language certified by ANSI and ISO. SQL is used to access different databases like SQL Server, MySQL, MS Access, Sybase, Oracle, DB2, Informix and Teradata etc.

SQL is a database computer language designed for the retrieval and management of data in a relational database. This tutorial will give you a quick push towards SQL database. It covers most of the topics required for a basic understanding of SQL and to get a feel of how it works.

Mazor difference between DBMS and RDBMS:

1) DBMS applications store data as file. RDBMS applications store data in a tabular form.
2) In DBMS, data is generally stored in either a hierarchical form or a navigational form. In RDBMS, the tables have an identifier called primary key and the data values are stored in the form of tables.
3) Normalization is not present in DBMS. Normalization is present in RDBMS.
4) DBMS does not apply any security with regards to data manipulation. RDBMS defines the integrity constraint for the purpose of ACID (Atomocity, Consistency, Isolation and Durability) property.
5) DBMS uses file system to store data, so there will be no relation between the tables. in RDBMS, data values are stored in the form of tables, so a relationship between these data values will be stored in the form of a table as well.
6) DBMS has to provide some uniform methods to access the stored information. RDBMS system supports a tabular structure of the data and a relationship between them to access the stored information.
7) DBMS does not support distributed database. RDBMS supports distributed database.
8) DBMS is meant to be for small organization and deal with small data. it supports single user. RDBMS is designed to handle large amount of data. it supports multiple users.
9) Examples of DBMS are file systems, file system, XML, Windows Registry, etc. Example of RDBMS are mysql, postgre, sql server, oracle etc.
10) Data redundancy is common in this model. Keys and indexes do not allow Data redundancy.
11) Data elements need to access individually. Data can be easily accessed using SQL query. Multiple data elements can be accessed at the same time.
12) Data fetching is slower for the complex and large amount of data. Data fetching is rapid because of its relational approach.