5 Secrets for Making PostgreSQL Run BLAZING FAST

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5 Secrets for Making PostgreSQL Run BLAZING FAST

Stop Complaining About Slow Queries — Fix Them Instead

Mark Henry

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I once worked with a team that blamed every single performance issue on PostgreSQL.

“It’s too slow!” they cried.

The real problem? They were treating PostgreSQL like a giant Excel sheet with a fancy logo.

No indexes. No query tuning. No clue.

PostgreSQL isn’t slow — you are.

And today, I’m going to show you how to flip the script.

If you want your database to sprint instead of crawl, here are five secrets that separate amateurs from pros.

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1. Index Like Your Life Depends On It

Let’s be blunt: if you’re running queries without proper indexes, you’re basically asking PostgreSQL to do a full table scan every time.

That’s like searching for your car keys by flipping every cushion in every house on your block.

:backhand_index_pointing_right:Action step

  • Use EXPLAIN ANALYZE on your slow queries. If you see Seq Scan, you probably need an index.
  • Create B-Tree indexes for equality and range filters:

CREATE INDEX idx_users_email ON users(email);

  • Use GIN indexes for JSONB and full-text search:

CREATE INDEX idx_articles_content ON articles USING GIN (to_tsvector(‘english’, content));

But here’s the reality: over-indexing is a sin too.

Each insert/update now has to maintain that index. Be surgical, not sloppy.

2. Vacuum Isn’t Optional — It’s Life Support

PostgreSQL doesn’t overwrite rows. It creates new versions.

That’s great for concurrency but terrible if you don’t clean up. Without vacuuming, your database bloats like a pufferfish.

:backhand_index_pointing_right:Action step

  • Ensure autovacuum is enabled (it is by default—don’t be the person who turns it off).
  • For high-churn tables, tweak autovacuum_analyze_scale_factor and autovacuum_vacuum_scale_factor so cleanup happens faster.

Example:

ALTER TABLE orders SET (
autovacuum_vacuum_scale_factor = 0.05,
autovacuum_analyze_scale_factor = 0.02
);

This makes sure orders doesn’t balloon into a performance nightmare.

3. Write Queries for Humans, Then Optimize for PostgreSQL

Stop writing SQL like it’s a high school essay. Clarity first, then optimization.

Reality: ORM-generated queries are often garbage.

They SELECT *, join everything under the sun, and filter later. That’s like ordering the entire menu just to eat one french fry.

:backhand_index_pointing_right:Action step

  • Only SELECT the columns you need.
  • Push filtering to the database instead of doing it in the app.
  • Break down monsters: sometimes two smaller, well-indexed queries are faster than one monstrous join.

Example of good practice:

SELECT id, name FROM users WHERE active = true LIMIT 50;

Short. Focused. Fast.

4. Tune PostgreSQL Like a Race Car, Not a Prius

The default PostgreSQL settings are conservative.

They’re meant to run on a potato. If you’ve got real hardware, unlock its potential.

:backhand_index_pointing_right:Key parameters to adjust

  • shared_buffers: Usually set this to 25–40% of your RAM.
  • work_mem: Increase if you’re doing big sorts or joins, but don’t go wild.
  • effective_cache_size: Tell PostgreSQL how much OS cache you have.

Example:

shared_buffers = 8GB
work_mem = 64MB
effective_cache_size = 24GB

This isn’t copy-paste gospel. Measure. Adjust. Repeat.

Tuning is science + art.

5. Monitor Like a Paranoid Control Freak

You can’t improve what you don’t measure. Flying blind is for pigeons, not databases.

:backhand_index_pointing_right:Action step

  • Use pg_stat_activity to see active queries.
  • Check pg_stat_statements to find your top resource hogs.
  • Use tools like PgHero or pganalyze for a friendlier dashboard.

A query running 100ms might not sound bad, until you realize it’s being executed 10,000 times a minute.

That’s death by papercuts.

Finally

PostgreSQL can be blazing fast. But it won’t fix itself.

Index smartly, vacuum religiously, write cleaner queries, tune your configs, and monitor like your job depends on it — because it does.

Your database is only as good as the discipline of the team managing it.

Don’t be the team that blames PostgreSQL when the real culprit is neglect.

What’s your favorite PostgreSQL performance hack?

Drop it in the comments, share this with your dev buddy who keeps saying “Postgres is slow,”

or save it for the day you inherit a 500GB database that’s crawling.

Because trust me you’ll need it.

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