Question 1

How do I connect to a PostgreSQL database using DBI in R?

Accepted Answer

First install the RPostgres backend, then use dbConnect(RPostgres::Postgres(), ...) with your database credentials. DBI provides the generic dbConnect function, but you need the specific backend for PostgreSQL to establish the connection.

Question 2

What's the difference between DBI and dplyr for database work?

Accepted Answer

DBI is a low-level interface for direct SQL operations and connection management, while dplyr is a higher-level grammar for data manipulation that can use DBI backends. DBI offers more control over raw queries, but dplyr provides a more intuitive syntax for complex data transformations.

Question 3

Does DBI support NoSQL databases like MongoDB?

Accepted Answer

No, DBI is specifically designed for relational database management systems (RDBMS). For NoSQL databases, you need to use other R packages like mongolite or sparklyr, which are built for those systems.

Question 4

How to handle transactions with DBI?

Accepted Answer

Use dbBegin to start a transaction, dbCommit to save changes, and dbRollback to revert, but note that transaction support is optional and depends on the backend implementation—some databases may not fully support it.

Question 5

What backends are available for DBI and how do I choose?

Accepted Answer

Common backends include RSQLite for SQLite, RPostgres for PostgreSQL, RMariaDB for MySQL/MariaDB, and odbc for ODBC databases. Choose based on your database system; each backend is optimized for performance and features specific to that DBMS.

Question 6

Is DBI compatible with Shiny apps for real-time data?

Accepted Answer

Yes, DBI can be used in Shiny apps to connect to databases dynamically, but you must manage connections carefully to avoid leaks—typically by opening and closing connections within reactive contexts or using connection pooling.

DBI

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