In database management systems (DBMSs) such as SQLite, indexes can be used to optimize the performance of queries, especially for larger datasets where querying can become time-consuming. An index allows the database to locate rows more quickly without scanning every row in a table.

This article explains how to create an index in SQLite, along with a simple example.

What is an Index?

An index is a data structure that enhances the speed of data retrieval operations on a table. Indexes work by storing sorted values of one or more columns, making it faster to find rows matching specific conditions.

However, while indexes speed up SELECT queries, they also add overhead to INSERT, UPDATE, and DELETE operations due to the need to maintain the index.

Syntax for Creating an Index

Creating an index in SQLite is straightforward. The general syntax is:

CREATE INDEX index_name ON table_name (column1, column2, ...);

• index_name: The name you want to assign to the index.
• table_name: The name of the table where the index will be created.
• column1, column2, …: The columns that will be indexed.

There are more options than list here, but that’s the basic syntax (see the SQLite documentation for the full syntax).

Example: Creating a Basic Index

Let’s start with a basic example. Suppose you have a table called employees with the following schema:

CREATE TABLE employees (
    employee_id INTEGER PRIMARY KEY,
    first_name TEXT,
    last_name TEXT,
    department_id INTEGER,
    salary REAL
);

If you frequently search for employees by last_name, you can create an index on that column to speed up those queries.

CREATE INDEX idx_employees_last_name ON employees (last_name);

Now, when you run a query that filters by last_name, SQLite can use the idx_employees_last_name index to locate records faster.

Query Example Using the Index

Here’s a sample query that can benefit from the index:

SELECT * FROM employees 
WHERE last_name = 'Griffin';

With the index, SQLite doesn’t have to perform a full table scan; it can use the idx_employees_last_name index to quickly find rows where last_name is “Griffin.”

Creating a Multi-Column Index

Sometimes, you may want to search based on multiple columns. In such cases, you can create a multi-column index. For example, let’s say you often query employees by department_id and last_name:

CREATE INDEX idx_employees_dept_last ON employees (department_id, last_name);

This multi-column index helps speed up queries that use both department_id and last_name in the WHERE clause:

SELECT * FROM employees 
WHERE department_id = 2 
AND last_name = 'Griffin';

When to Create an Index

Indexes can improve performance in many scenarios but should be used judiciously. While they can speed up queries, they can also slow down update operations. Here are some cases where an index is typically beneficial:

• Frequent Searches: Columns that are often used in WHERE clauses, especially with equality or range conditions.
• Join Operations: Columns used as foreign keys in joins benefit from indexing.
• Sorting and Ordering: Columns frequently involved in ORDER BY clauses or used in aggregate functions (like MIN() or MAX()) often benefit from an index.

Limitations and Considerations

While indexes can enhance query performance, they also have some drawbacks:

• Storage Space: Indexes consume additional disk space.
• Maintenance Overhead: INSERT, UPDATE, and DELETE operations become slower (because indexes need to be updated whenever the underlying tables are updated).
• Diminishing Returns: Too many indexes on a table can result in diminishing performance benefits, so choose wisely which columns to index.

Deleting an Index

If you need to remove an index, you can use the DROP INDEX statement. For example:

DROP INDEX idx_employees_last_name;

This command deletes the idx_employees_last_name index from the employees table.