🔍 1. Use Indexing Wisely — Not Blindly
✅ What It Does:
Indexes speed up data retrieval by creating a quick lookup structure. Perfect for WHERE clauses, JOIN conditions, and ORDER BY.
🧪 Example:
-- Create an index on frequently filtered column
CREATE INDEX idx_users_email ON users(email);
⚠️ Common Mistake:
Over-indexing! Every insert/update operation becomes slower.
🛠️ Best Practices:
- Use
pg_stat_user_indexes
to find unused indexes. - Composite indexes help with multiple conditions:
CREATE INDEX idx_orders_customer_status
ON orders(customer_id, status);
🧠 2. Decode Queries with EXPLAIN ANALYZE
Before optimizing, you need to understand what your query actually does.
🧪 Example:
EXPLAIN ANALYZE
SELECT * FROM orders WHERE user_id = 42;
This tells you if it’s doing a sequential scan (slow) vs an index scan (fast).
⚠️ Common Mistake:
Ignoring cost and actual execution time. Always look at actual time
instead of just cost
.
✅ Best Practice:
- Use tools like PgHero or auto_explain in dev/staging.
- Log slow queries for analysis.
🪓 3. Eliminate the N+1 Query Problem
This common ORM issue causes 1 parent + N child queries, hammering performance.
🧪 Example (Sequelize):
// BAD: Causes N+1
const posts = await Post.findAll();
for (const post of posts) {
const comments = await post.getComments();
}
✅ Fix It:
// GOOD: Eager load
const posts = await Post.findAll({
include: [{ model: Comment }]
});
⚠️ Mistake:
Failing to use eager/lazy loading appropriately.
🧬 4. Join Smartly (and with Purpose)
Joins are powerful — but misuse can slow things down.
🧪 Example:
SELECT o.id, c.name
FROM orders o
JOIN customers c ON o.customer_id = c.id;
⚠️ Mistake:
Joining large tables unnecessarily or without indexing the join key.
✅ Best Practices:
- Use INNER JOIN instead of LEFT JOIN when possible.
- Always index foreign keys.
🧰 5. Sequelize Performance Tips
🔹 Use attributes
to fetch only necessary fields:
User.findAll({ attributes: ['id', 'name'] });
🔹 Disable logging in production:
const sequelize = new Sequelize(..., { logging: false });
🔹 Use raw queries when you hit ORM limits:
await sequelize.query("SELECT COUNT(*) FROM users WHERE active = true", { type: QueryTypes.SELECT });
📦 6. Stored Procedures & Functions = Reusable Logic + Speed
✅ Use-case:
Move complex business logic to the DB for faster execution.
🧪 Example:
CREATE OR REPLACE FUNCTION active_user_count()
RETURNS INT AS $$
BEGIN
RETURN (SELECT COUNT(*) FROM users WHERE active = true);
END;
$$ LANGUAGE plpgsql;
Call from Sequelize:
await sequelize.query("SELECT active_user_count()");
⚠️ Caveat:
Use stored procedures sparingly; they’re harder to debug and test.
🖼️ 7. Data Views — Precomputed Results for Fast Reads
🧪 Example:
CREATE VIEW top_customers AS
SELECT customer_id, SUM(amount) AS total_spent
FROM orders
GROUP BY customer_id
HAVING SUM(amount) > 10000;
Use it like a regular table:
SELECT * FROM top_customers;
✅ Benefits:
- Simplifies frontend queries.
- Improves performance for complex analytics dashboards.
🧹 8. Vacuum & Analyze — Housekeeping You Shouldn’t Skip
PostgreSQL doesn’t auto-clean up dead tuples.
✅ Command:
VACUUM ANALYZE;
Or use auto-vacuum — but monitor it.
⚠️ Mistake:
Ignoring bloat in high-transaction tables like logs or sessions.
✅ Best Practices:
- Schedule
VACUUM FULL
for rarely updated large tables. - Monitor with
pg_stat_user_tables
.
🏁 Final Thoughts
Database optimization isn’t just the DBA’s job anymore. As a full-stack developer, you own performance too.
🔑 Golden Rule: Don’t optimize blindly. Measure first, optimize second.
📚 TL;DR Cheat Sheet
Technique | Best Use Case | Tool/Command |
---|---|---|
Indexing | Fast WHERE / JOIN / ORDER |
CREATE INDEX , pg_stat_*
|
EXPLAIN ANALYZE | Query bottleneck diagnosis | EXPLAIN ANALYZE |
Avoid N+1 | ORM optimization | Sequelize include
|
Smart Joins | Data stitching | Indexed foreign keys |
Stored Procedures | Reuse heavy logic inside DB | CREATE FUNCTION |
Views | Dashboard / report optimization | CREATE VIEW |
Vacuum & Analyze | Space and stats maintenance | VACUUM ANALYZE |
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