SQL Views Explained: Normal Views vs Materialized Views

When deciding between a normal view and a materialized view, it’s essential to weigh the trade-offs between query performance and data freshness. Each option has its strengths and is suited for specific use cases. Let’s break it down:

🔍 When to Use a Normal View

Normal views are essentially saved SQL queries that dynamically fetch data from the underlying tables whenever they are queried. They are ideal in scenarios where data freshness is critical and storage efficiency is a priority.

✅ Data Must Always Be Fresh

Normal views always reflect the latest state of the underlying tables. This makes them perfect for real-time dashboards or reports where having up-to-date data is non-negotiable.

✅ Query Performance is Acceptable

If the underlying tables are small, well-indexed, or the queries are not computationally expensive, normal views work well without introducing performance bottlenecks.

✅ Storage Efficiency

Since normal views don’t persist data, they don’t consume additional storage. They only store the SQL definition, making them lightweight and efficient.

✅ Simplicity

Normal views are straightforward to create and maintain. They don’t require additional logic for refreshing or managing cached data.

Example Use Case: Displaying the most recent 10 transactions for a user, where the data must always reflect the latest state.

⚡ When to Use a Materialized View

Materialized views, on the other hand, store the results of a query physically on disk. They are designed for scenarios where query performance is paramount, and slight data staleness is acceptable.

✅ Critical Query Performance

Materialized views precompute and cache the results of complex queries, such as those involving heavy joins, aggregations, or analytics. This significantly improves performance for frequent reads.

✅ Tolerance for Slightly Stale Data

If the underlying data doesn’t change frequently or if a delay in data updates is acceptable, materialized views are a great choice. They trade off real-time freshness for speed.

✅ Offloading Computation

By precomputing and storing results, materialized views reduce the computational load on the database during query execution. This is especially useful for resource-intensive queries.

Example Use Case: Generating a monthly sales summary per region, where the data only needs to be updated once a month.

📌 Key Trade-Offs

Here’s a quick comparison to help you decide:

⏱️ Refreshing Materialized Views

Materialized views need to be refreshed to stay up-to-date. You can choose between manual or automated refresh strategies:

🔄 Manual Refresh

Run the following command to refresh a materialized view manually:

REFRESH MATERIALIZED VIEW view_name;

⏰ Scheduled Refresh

Automate the refresh process using tools like pg_cron in PostgreSQL, database triggers, or external schedulers like cron. This ensures the materialized view stays updated without manual intervention.

🛠️ Making the Right Choice

Use normal views when you need real-time data and can tolerate slightly slower query performance. Opt for materialized views when speed is critical, and you can work with slightly stale data.