R and Relational Databases

#Why use R with relational database
The data to be analysed resides in a relational database & R is well known for its powerful data analysis & data visualisation capabilities.

For R data must reside in the memory therefore SQL can be used for data analysis with R as it helps in:
1. Providing concurrent access to data
2. Manipulating large dataset
3. Persistence


#RDBMS (Relational Databases)
When data is stored in RDBMS:

1. Manipulating large structured databases
Individual observations or rows can be easily changed. RDBMS servers are designed for scalability & can easily support large datasets.
2. Providing concurrent data access to multiple users.A single database could be used for generating standard summary reports using SQL & the data could also be used to perform deeper analysis using R.
3. Maintaining data consistency (data types/ schemas)
RDBMS insure data integrity, consistency & security. Any data stored in RDBMS must adhere to defined constraints & updates are wrapped within atomic units known as transactions.
Access to data can be managed using data control language statements such as the SQL GRANT or REVOKE statement.
4. Persistence (granular, secure & consistent)
Database servers can also be configured to provide data audit trail to better understand any unauthorised data access.