[research data storage, efficiency, SQL database, SQLite]


In this article, we will introduce how to access data stored in SQLite in an R session. If you are not yet sure whether you need a database for your research data, you can read our article on data storage options.

What is SQLite?

SQLite is a SQL library that implements a self-contained, serverless, zero-configuration SQL database engine. It is widely used in mobile applications and embedded systems. SQLite is a good choice for research data storage because it is lightweight, fast, and easy to use. It is also open-source and free to use.

SQLite is architecturally different from traditional SQL databases, such as PostgreSQL or MySQL. For starters, it is a library that links to your application; not a standalone server that you connect to. Therefore, you don’t need to install a separate server to use SQLite. The entire database can be stored in a single file on disk which makes it easy to move the database around and share it with others, via email, flash drive, etc.

When to choose other databases over SQLite?

If your data meets one of the below conditions, then SQLite might not be the best choice for you. We recommend using a more robust database like PostgreSQL, MySQL, or MariaDB.

  • your data is already on a remote server,
  • you have loads of concurrent writers (because SQLite locks the table when writing),
  • gazillion transactions per second (for the same reason as above),
  • extremely large datasets (due to its single-file architecture)

    SQLite does not support stored procedures, triggers, or user-defined functions. In addition, since it is just a file, it doesn’t come with all security features that a server-based database would have.

How to use SQLite in R?

With the following code snippet, you can create a SQLite database in R.

# Install the RSQLite package once
install.packages('RSQLite', repos='http://cran.us.r-project.org')


# Connect to an existing SQLite database file or create a new one
con <- dbConnect(SQLite(), "mydatabase.db")

Then you can use the connection object con to interact with the database.

Below you can see how to use SQL command to create a table, insert data to it, and then query that data. Query results are returned as a dataframe in R.

# Create a table

# Insert data into the table
dbExecute(con, "INSERT INTO mytable (name, age) VALUES ('John', 30)")
dbExecute(con, "INSERT INTO mytable (name, age) VALUES ('Alice', 25)")

# Retrieve data from the table
result <- dbGetQuery(con, "SELECT * FROM mytable")

If you have your initial data as CSV file, you can simply read it into a dataframe and then save it to a SQLite table. Make sure to create a table following a code similar to above before writing the data to it.

# Connect to SQLite database
con <- dbConnect(SQLite(), "mydatabase.db")

# Read the CSV file into a dataframe
new_data <- read_csv("data.csv")

# Append data to an existing table in SQLite database
dbWriteTable(con, "mytable", new_data, append = TRUE)

Finally, don’t forget to close the connection when you are done with it.

# Close the connection

Contributed by Maliheh Mahlouji