How to Optimize PostgreSQL Queries: Fixes for Fast Performance (Weekly Quick Tip Series)
Practical PostgreSQL performance tuning tips, delivered weekly with examples you can apply immediately.
Why This Weekly Series Exists
You know that moment when you’re debugging a slow query, your coffee is getting cold, your manager is asking for the report, and PostgreSQL is just… staring back at you?
Yeah.
We’ve all been there.
So I want to do something different for you.
👉 Every week, I’ll send you tiny PostgreSQL or MySQL or MariaDB or other database engine performance tuning tip the kind of tip that instantly makes you a better engineer without reading a 400-page database manual.
Why I’m Doing This
Because PostgreSQL is massive.
SQL is massive.
And once you add indexing, caching, query design, and data modeling… it becomes a lot.
But here’s the truth nobody says out loud:
Most of your biggest performance improvements come from the smallest ideas.
Tiny habits.
Tiny techniques.
Tiny insights that save you hours and make you a better engineer without any extra overwhelm.
A single small tip can:
save you hours
make your SQL cleaner
simplify your decisions
improve your engineering intuition
unlock features you didn’t know existed
help you avoid slow-query traps
make PostgreSQL feel less mysterious
That’s what this series gives you:
tiny, powerful shortcuts you can apply instantly.
Every tip will be designed to help you naturally understand:
how to optimize PostgreSQL queries without overthinking
smart ways to reduce full table scans
simple SQL performance tuning tips that actually matter
small indexing decisions that follow real PostgreSQL indexing best practices
shortcuts to improve SQL query speed with indexing and caching
when to use features like materialized views in PostgreSQL
and how caching fits into caching strategies for PostgreSQL applications
Much more…
Not subscribed yet? Subscribe now and don’t miss my next tip!
🔥 Your First Quick Tip Drops Next
Quick Tip #1 The Stop Using SELECT * Wake-Up Call
One of my customer once said his query was slow because the server is old.
I checked the query:
SELECT * FROM big_table;Classic rookie move.
If you’re looking for SQL performance tuning tips for beginners, this is the one nobody forgets once it burns them.
We changed it to this:
SELECT column_you_need
FROM big_table
WHERE indexed_column = value;Suddenly the query became hundreds of times faster.
This is one of the easiest ways to stop using SELECT * for better database performance.
Why this works (simple explanation)
Less data = less work.
PostgreSQL doesn’t need to load unnecessary columns.Indexes = shortcuts.
Using the right indexed column in your WHERE clause leverages PostgreSQL indexing best practices to avoid scanning the entire table.
If you want to reduce slow queries in PostgreSQL, this tiny change alone works wonders.
Quick Tip #2 Cache Smart in PostgreSQL
Here’s a real-life example.
A system kept running this query:
SELECT customer_id, COUNT(*)
FROM orders
GROUP BY customer_id;Every dashboard refresh triggered a scan.
That’s the opposite of caching strategies for PostgreSQL applications.
So we fixed it using three simple steps:
1. Use Materialized Views
When you run repeated aggregates, materialized views in PostgreSQL let you compute once and reuse the result.
2. Add the Right Indexes
Indexes help PostgreSQL keep hot data in memory, which improves query speed dramatically.
This ties directly into PostgreSQL indexing best practices.
3. Use Redis for Rarely-Changing Data
When data isn’t changing often, caching it reduces disk scans the fastest way to improve SQL query speed with indexing and caching.
Why this matters
Disk is slow.
Memory is fast.
Caching and indexing help PostgreSQL stay in memory and avoid unnecessary work.
This is exactly how you reduce slow queries in PostgreSQL without touching your hardware.
Let me ask you something
What’s the slowest query you’re dealing with right now?
Add your comment to this post or drop me an email I might break it down in next week’s issue.
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