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A materialized view is a database object that contains the results of a query. It’s similar to a regular view, except that the data is physically stored. This is good because it makes it faster to retrieve data, which helps for stuff like complex queries. This guide walks you through how to create one in MySQL.

What is a materialized view?

Full disclosure: MySQL doesn’t natively support materialized views. However, you can simulate one using a combination of a regular view and a physical table. You have to create a table to store the query result and then periodically refresh that table to keep the data up to date.

Create a base table and view

Step 1: Create a base table

Start by creating a base table that will store the materialized data. This table’s structure should match the result of the query you intend to materialize.

CREATE TABLE materialized_view_table (
    -- Define columns here
);

Step 2: Create a view

Next, create a view that defines the query you want to materialize.

CREATE VIEW my_view AS
SELECT
    -- Define your query here
;

Populate the materialized view

Refresh the materialized view

Since MySQL doesn’t automatically refresh materialized views, you need to implement a mechanism to periodically update the base table with the latest data.

TRUNCATE TABLE materialized_view_table;

INSERT INTO materialized_view_table
SELECT * FROM my_view;

You can automate this process using events or triggers.

Query the materialized view

To retrieve data, simply query the base table.

SELECT * FROM materialized_view_table;

The advantage of this approach is that it’s faster to retrieve data than if you just queried the view directly.

Managing updates

To keep the materialized view up-to-date, consider implementing a scheduled job that runs the refresh query at regular intervals. You can do this with MySQL events or external schedulers.


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Written by

Robert Cooper avatar

Robert Cooper

Senior Engineer at Basedash

Robert Cooper is a senior engineer at Basedash who builds full-stack product systems across SQL data infrastructure, APIs, and frontend architecture. His work focuses on application performance, developer velocity, and reliable self-hosted workflows that make data operations easier for teams at scale.

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