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How to Use Materialized Views in PostgreSQL?

If you’re using PostgreSQL and looking to speed up your queries, especially the long ones, materialized views may be just what you need!

Unlike standard views that simply re-runs the query each and every time you call it, materialized views actually store the results on disk. So, when you query a materialized view you’re simply pulling up a previously saved result set much quicker! This can be really useful for things like dashboards, reports, or anything where performance is important and you’re not constantly changing your data.

What are Materialized Views?

Think about it this way, you’ve executed a complex query like maybe you joined 5 tables, filtered some data, sorted, etc. Instead of performing that work every time you need it, PostgreSQL can persist the output into a table-like object that’s a materialized view.

There isn’t any magic, when the data updates in the tables your materialized view isn’t automatically up-to-date. You’ll need to refresh it when your underlying data changes; for most reporting and analytic tasks that trade-off is worth it.

Why Materialized Views?

From my experience, materialized views are advantageous in these situations:

  • Heavy Queries & Faster Reads: If you are running a heavy query repeatedly, materialized views will decrease load times.
  • Great For Dashboards and Reports: Dashboards and reports almost always need aggregated data or historical data, so materialized views are a great fit.
  • Less Load on the DB: It won’t take as long to compute each time you want to query your data, so your database won’t have to process everything each time.

Steps to Create a Materialized View

Creating a materialized view in PostgreSQL is very simple and easy. It can be done with a few simple steps by running the following command!

CREATE MATERIALIZED VIEW view_name AS
SELECT column1, column2, .
FROM table_name
WHERE conditions

For instance let’s say,

CREATE MATERIALIZED VIEW employee_salaries AS
SELECT employee_id, SUM(salary) AS total FROM employees

GROUP BY employee_id

This query creates a materialized view of employee_salaries, which stores the total salary for each employee.

Refreshing Materialized Views

Materialized views contain data physically, thus, data in the underlying tables is used to create or populate the materialized views. That data in the materialized views will never automatically refresh/update when underlying tables are modified.

REFRESH MATERIALIZED VIEW view_name

To avoid locking and allow for concurrent use, use the CONCURRENTLY keyword:

REFRESH MATERIALIZED VIEW CONCURRENTLY view

Note: A materialized view should have a unique index to use CONCURRENTLY.

Dropping Materialized View

To drop a materialized view, use the command DROP MATERIALIZED VIEW:

DROP MATERIALIZED VIEW view_name;

You can specify the IF EXISTS clause to avoid an error in case the view does not exist:

DROP MATERIALIZED VIEW if exists view_name

Benefits of Materialized Views

Some of the top benefits of materialized view!

  • Improved performance: Speeds up complex queries by maintaining results in physical stores.
  • Less Computation: Saves CPU time for repeated queries.
  • Indexing: Materialized views can be indexed for performance improvement

Limitations of Materialized Views

Manual Refresh: Data can get outdated if it is not updated periodically.
Storage costs: Materialized views occupy physical disk space.
Concurrency Issues: Lock the view while refreshing it without using Concurrently.

Best Practices for Utilizing Materialized Views

Improve query performance through the use of indexes for materialized views.

Schedule Refreshs: Utilize cron jobs or the built-in job scheduler in PostgreSQL to automate the refresh process.
Monitor performance: Regularly monitor query performance and revise strategies.
Minimize Locking: Use refresh materialized view concurrently to minimize locking.

Conclusion

Materialized views are a powerful query performance optimization tool in PostgreSQL, particularly when dealing with complex data aggregations. By physically materializing the results, they greatly reduce query execution times. However, good refresh strategy management and indexing are necessary in order to guarantee performance and data consistency.

Leverage materialized views to increase your PostgreSQL applications’ speed while keeping the highest level of precision and efficiency.

Frequently Asked Questions

Do materialized views get automatically refreshed?
No, PostgreSQL materialized views must be refreshed manually. The process can be automated by using scheduled jobs.

Can data in a materialized view be updated?
No, the data cannot be refreshed. The view should be refreshed to get the latest data from the underlying tables.

Explain the basic difference between a regular and a materialized view?
In a simple way, a regular view does not physically store data and always shows the most recent data while a materialized view stores the results of a query on disk and must be refreshed manually.

June 5, 2025