Laravel Eloquent Performance: Mastering PostgreSQL Generated Columns

Last month, our analytics dashboard started choking during peak traffic hours. We were calculating a "user engagement score" on the fly using a combination of JSONB fields and related table aggregates, which resulted in a query latency spike of around 450ms. After eliminating N+1 queries in Eloquent: A Pragmatic Approach and verifying our indexing strategy, we realized the bottleneck wasn't the query structure—it was the computation overhead inside the database engine.

We needed a way to pre-calculate these values without bloating our application code or relying on fragile background sync jobs. That's where PostgreSQL generated columns came to the rescue.

Moving Logic to the Database

When you're dealing with high-traffic read models, the overhead of calculating derived data in PHP, or even inside complex SQL expressions, adds up fast. PostgreSQL (version 12+) allows you to define a column that automatically calculates its value based on other columns in the same row.

We first tried using a standard after hook in our Eloquent model to save the result of our calculation into a dedicated column. It broke because of race conditions; if a background job updated a related table, the model saved event wouldn't fire, leaving the read model stale.

By switching to database-level generated columns, the database handles the data integrity. Here is how we implemented it in a Laravel migration:

PHP
Schema::table('users', function (Blueprint $table) {
    $table->unsignedInteger('engagement_score')
        ->storedAs('jsonb_extract_path_int(metadata, \'points\') + activity_count');
});

The storedAs method tells Postgres to calculate the value on write and store it physically. This turns a complex, CPU-intensive calculation into a simple, O(1) column read.

Optimizing Eloquent Performance with Generated Indexes

Once you have a generated column, the real power comes from indexing. Since the database treats these columns as standard data, you can create a B-tree index on them just like any other column.

If you're wondering how to verify if your new index is actually doing its job, I highly recommend reading an EXPLAIN plan without panic: A Backend Engineer’s Guide to confirm the query planner is choosing an Index Scan over a Seq Scan.

Adding the index in Laravel is straightforward:

PHP
Schema::table('users', function (Blueprint $table) {
    $table->index('engagement_score');
});

With this in place, our dashboard query time dropped from 450ms to roughly 12ms. Because the index is maintained by the database engine, we don't have to worry about our application code getting out of sync with the underlying data.

Trade-offs and Considerations

It isn't a silver bullet. Using generated columns increases the write latency slightly because the database must perform the calculation every time a source column changes. In our case, the read-to-write ratio was roughly 100:1, making this a clear win. If you have a write-heavy system, you might reconsider, but for most Eloquent-driven read models, this is a negligible cost.

Another thing to watch out for is the complexity of the expression. Keep your logic simple. If you find yourself writing massive CASE statements or complex subqueries in your generated column definition, you might be better off using a materialized view or a dedicated search index like Meilisearch.

FAQ

Can I use generated columns with MySQL? Yes, MySQL supports generated columns since version 5.7. The syntax is slightly different, but the core concept of VIRTUAL vs STORED columns remains the same.

Does this break Eloquent's model mass assignment? Not at all. Since the column is managed by the database, Eloquent treats it as a read-only field. You can simply add it to the $hidden array in your model if you don't want it exposed in your API responses by default.

Should I use this for every computed field? No. Only use this for fields that appear in WHERE, ORDER BY, or GROUP BY clauses. If you just need to display a value, a standard Eloquent accessor is usually sufficient and much easier to maintain.

Final Thoughts

Leveraging database-level features like generated columns forces you to think about your data architecture differently. It’s easy to stay inside the comfort of Laravel’s ORM, but sometimes the best way to scale is to let the database do the heavy lifting. I’m still experimenting with how to integrate this more deeply into our Laravel Event-Driven Architecture: The Transactional Outbox Pattern](/blog/laravel-event-driven-architecture-the-transactional-outbox-pattern) implementation, but for now, this approach has saved us hours of debugging performance issues.

Next time, I might look into partitioning if the users table grows beyond a few million rows, but for now, keeping it simple is working just fine.