PostgreSQL Window Functions for Advanced Analytics

🗄️ Slow query? Stop guessing. EXPLAIN ANALYZE shows you exactly what Postgres did, not what you think it did. 🔍 Seq Scan on a big table = missing index. Simple as that. #PostgreSQL #SQL #Database #Backend #WebDev

Do you know how to master data retrieval and logic in PostgreSQL? FROM, SELECT, and Logical Operators are the three building blocks behind every SQL query you have ever written. I illustrated the full picture. Follow Nitin Rawat for daily PostgreSQL content 🔔 #PostgreSQL #SQL #LearnSQL #BackendDevelopment #Database #SQLForBeginners

You think your data is relational because you already visualize it in a normalized form. But most data starts as a document — a form, a message, an event. 🌱 If you store the document as-is, consistency is natural. You don't need foreign keys, and you rarely need multi-statement transactions. 🧩 If you normalize it, you must recreate that consistency with foreign keys, joins, and transactions. 💡 The real question for your OLTP database isn't #NoSQL vs #SQL, or #PostgreSQL vs MongoDB. It's whether you store the application's data aligned with its domain model — or normalize it to make it application-agnostic.

Your “Fast” SQL Query Isn’t Fast ⚡. It’s Lucky 🤞🏻. It works locally. It passes code review. Then production exposes it. I’m starting a new blog series named "Dating Databases ❤︎" where we uncover what really happens inside database engines. In my latest article, I break down how "EXPLAIN ANALYZE" reveals what your query actually does ; not what you think it does. Because sometimes the query isn’t slow. Our understanding of it is. Read the article here: https://lnkd.in/dCm8K9tj This is just the beginning we’re going deeper into database internals next. Stick around. #SQL #Databases #BackendEngineering #Performance #SystemDesign #PostgreSQL #MySQL

PostgreSQL DBAs — stop writing SQL just to explore your database. These psql meta commands will save you time every single day: \l → databases \dt → tables \d table → structure \timing → query speed \x → expanded view \? → everything No complex queries. Just backslash and go. 🚀 📖 Want more commands like these? Explore the full cheat sheet here 👇 🔗 https://lnkd.in/gMZkBhC5 #PostgreSQL #mafiree #DBA #Database #SQL #DataEngineering #DevTips #BackendDev #OpenSource

SELECT age + 5 AS new_age FROM users WHERE new_age > 30; Will it: ✅ Run successfully ❌ Throw an error 👇 Comment your answer before reading further. 💡 Hint: Think Execution Order in PostgreSQL In PostgreSQL, a SELECT query is logically processed in this order: 🥇FROM 🥈 WHERE 🥉 GROUP BY 🏅 HAVING 🎯 SELECT 📊 ORDER BY ✂️ LIMIT #Database #SQL #PostgreSQL #Backend

I put together a short presentation covering a few PostgreSQL design basics that can save a lot of pain later. It covers: 🎯 normalization 🎯 keys and relationships 🎯 SQL JOINs 🎯 delete behavior 🎯 many-to-many tables The focus is on practical schema design, not just writing queries. #PostgreSQL #SQL #DatabaseDesign #Normalization #BackendDevelopment #SoftwareEngineering

Structured my PostgreSQL notes into a visual quick reference. Blending database fundamentals with clean design. Always improving. #PostgreSQL #SQL #DataAnalytics #LearningInPublic #Database #ContinuousLearning

Changed just one word in a PostgreSQL function… and got a 3,000× speedup ⚡ Here’s what happened 👇 I had a simple UPDATE on a primary key — something that should take <1ms. Reality: ~498ms per call 9,500 calls ~80 minutes wasted 😅 After digging deeper, the culprit was surprisingly subtle: 👉 The function parameter was declared as NUMERIC 👉 The actual column type was BIGINT PostgreSQL was silently casting types on every call, which prevented the planner from reusing the optimal index plan inside PL/pgSQL. No errors. No warnings. Just a performance killer hiding in plain sight. The fix? One line: NUMERIC → BIGINT Result: Before: ~502ms/call After: 0.12ms/call 🚀 Key takeaways: 1️⃣ Enable pg_stat_statements in production, whenever required → You won’t see issues like this otherwise 2️⃣ Always match function parameter types with column types → Implicit casts are not “free” 3️⃣ Don’t rely only on EXPLAIN ANALYZE for ad-hoc queries → The planner behaves differently inside functions Sometimes, performance problems aren’t about complex queries or missing indexes… They’re about tiny mismatches with massive impact. iMocha Vishal Madan Sujit Karpe #PostgreSQL #Performance #DatabaseOptimization #BackendEngineering #TechLessons #Engineering

If you’ve ever wondered how Postgres magically handles thousands of concurrent reads and writes without turning your database into a locking mess… this one’s for you. Read the full post here: https://lnkd.in/gxpvGWpd #PostgreSQL #MVCC #Database #SQL #Databases