6
The Document base unit of storage resembles
in an RDBMS.
Rows
Columns
Answers
Answer:
One option is RDBMS is like an Excel Sheet — you categorise data in the form of tables. You can form relationships between the tables.
A query questions the database, which gives you a relevant answer in return. This querying language is SQL or Structured Query Language.
For example,
select * from Employee_Data;
selects all the Employee Data from the Employee_Data table.
Relational databases follow a schema, a detailed blueprint of how your tables work.
You use Amazon, Facebook and so many networking applications. They release updates, add new functionalities and even extra modules. So how does one change the schema each time? Isn’t it time consuming for such huge companies to devote their time and labour to changing the schema?
This is where SQL could not work.
The Cons of RDBMS
Relational databases aren’t as bad as people portray these days. They are still in use by plenty of organisations. The introduction of NoSQL into the picture is to fill up the spaces where RDBMS can’t be of use anymore.
I am going to show you examples so that you have a clear understanding.
1. RDBMS can not handle ‘Data Variety’.
The amount of unstructured data continues to increase yearly and managing it is hard. RDBMS can’t force all types of data under a unified schema of tables.
Data Silos are also a problem for developers.
According to Tech Target, a data silo is a repository of data that remains under the control of one department. It is isolated from the rest of the organisation.
This means that when more silos exist for the same data, their contents are likely to differ. It creates confusion on which repository represents the most up-to-date version.
The increase of data from the year 2013 to 2020 is visible in the image below.
About 44 Zeta bytes of data will be generated in the year 2020.
Handling such diverse data which aren’t related to each other could be much harder in RDBMS.
Source
Example: It is difficult to store the details of a patient, who has varying body conditions. Categorisation of such diverse data is difficult in RDBMS.
2. Difficult to change tables and relationships.
Alteration of the relationships between tables or addition of a new table could affect the existing relations. This means changing the schema.
Change of the schema would be like eliminating the existing one and devising a new schema.
Addition of a new functionality would need all the elements to support the new structure. Change is inevitable.
Example: Each extra column needs all the prior rows to have values for that column. Whereas in Cassandra (a NoSQL database), you can add a column to specific row partitions.