This content originally appeared on DEV Community and was authored by Alex Rivers
Are your complex SELECT queries with multiple JOINs and GROUP BY clauses slowing down your application? If you’re frequently running expensive calculations on data that doesn’t change every second, a materialized view might be your new best friend.
What’s a Materialized View?
Think of a standard view as a saved query that runs every time you access it. It’s always fresh, but if the underlying query is slow, accessing the view will also be slow.
A materialized view, on the other hand, is like a snapshot. It executes a query and stores the results physically on disk, just like a regular table. When you query the materialized view, you’re just reading these pre-computed results, which is incredibly fast! 
When Should You Use One?
Materialized views are perfect for:
Dashboards & Reporting: When you need to display aggregated data (e.g., daily sales totals, monthly user signups) and a slight delay is acceptable.
Complex Aggregations: For queries that involve heavy calculations, multiple joins, or large datasets that are costly to run repeatedly.
Data Warehousing: Summarizing large tables into more manageable forms for analysis.
The key is that the underlying data doesn’t need to be real-time.
A Quick Example
Let’s say you have a complex query to calculate total sales per product.
1) Create the Materialized View:
You define it just like a regular table or view, using your slow query.
CREATE MATERIALIZED VIEW daily_sales_summary AS
SELECT
p.product_name,
SUM(s.quantity * s.price) AS total_revenue,
DATE(s.sale_date) AS sale_day
FROM sales s
JOIN products p ON s.product_id = p.id
GROUP BY p.product_name, sale_day;
2) Query It (The Fast Part!):
Now, querying this data is as simple and fast as selecting from a table.
SELECT * FROM daily_sales_summary WHERE sale_day = '2025-09-05';
3) Keep It Fresh:
The one catch is that the data can become stale. You need to explicitly tell PostgreSQL to update it.
REFRESH MATERIALIZED VIEW daily_sales_summary;
You can schedule this REFRESH command to run periodically (e.g., every hour or overnight) using a cron job or a tool like pg_cron.
The Trade-Offs
Stale Data: The view is only as fresh as its last REFRESH.
Storage Space: Since the results are stored on disk, it consumes storage.
Refresh Time: The refresh process itself can be resource-intensive, as it has to re-run the original complex query.
By understanding these trade-offs, you can leverage materialized views to significantly boost your database’s performance for read-heavy workloads.
This content originally appeared on DEV Community and was authored by Alex Rivers